Measuring Marketing: The 100+ Essential Metrics Every Marketer Needs, Third Edition [3rd ed.] 9781501507304, 9781501515767

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John A. Davis Measuring Marketing

John A. Davis

Measuring Marketing

The 100+ Essential Metrics Every Marketer Needs Third Edition

ISBN 978-1-5015-1576-7 e-ISBN (PDF) 978-1-5015-0730-4 e-ISBN (EPUB) 978-1-5015-0722-9 Library of Congress Cataloging-in-Publication Data A CIP catalog record for this book has been applied for at the Library of Congress. Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http://dnb.dnb.de. © 2018 John A. Davis Published by Walter de Gruyter Inc., Boston/Berlin Printing and binding: CPI books GmbH, Leck ♾ Printed on acid-free paper Printed in Germany www.degruyter.com

Praise for Measuring Marketing, Third Edition This book is a go-to resource for marketers looking to better measure the effectiveness of their efforts. The depth of information and approaches it provides helps professionals go beyond the ‘usual suspects’ we use for metrics, and challenges us to explore new methods for determining how well we’re performing. Even better, many of the techniques shift our view of measurement from being a passive reporting tool to using it to be a more forward-looking tool for change. —Lisa Bodell CEO, futurethink Author, Why Simple Wins There is a quote, attributed to Albert Einstein: "Not everything that can be counted counts, and not everything that counts can be counted." In this book of marketing metrics, John Davis provides a brilliant insight into the metrics that do count in marketing. Each metric is explained succinctly so that marketing managers can understand and apply them to their business in a practical way. In a world of disruptive technology and fast changing consumer preferences, knowing what should be measured and how it should be measured is critical. This book should be compulsory reading for all marketing managers who want to stay ahead of the competition. —Professor Mark Farrell Head, Graduate School of Business and Law RMIT University, Australia Creating sustainable value is crucial for today’s companies, and marketing plays a central role in this effort. With so many tools available, from traditional to digital and social media, as well as sophisticated sales organizations and new distribution channels, measuring performance can get quite complicated. John Davis’s book, Measuring Marketing, is the perfect solution, offering clear descriptions and examples of how to measure the value contributed by the various marketing investments. Measuring Marketing is an excellent resource that every marketer and CMO should use. —Hari Nair Group Chief Strategy & Innovation Officer Sime Darby, Kuala Lumpur Malaysia

vi  Praise for Measuring Marketing, Third Edition John has delivered a comprehensive, end-to-end view of how to measure and create value. His expertise and approach are increasingly critical for any business to remain competitive. —Thomas McCabe Chief Country Officer, USA DBS Bank John Davis is a recognized expert in the field of marketing science. Measuring Marketing combines advances in the academic analysis of quantifying marketing impact together with deep industry insights to ensure…application to today’s marketing organisations and companies. —Steve Leonard CEO SGInnovate, Singapore One variation of a managerial maxim goes that you can’t manage what you can’t count. John Davis has provided a cartograph of just how to do this. This book sits as comfortably on the aisle of financial analysis books as it does on the aisle of marketing books. —Pakpoom Vallisuta Chairman of The Quant Group Board member of The Board of Visitors, Fuqua School of Business, Duke University



To Barb, Katie, Chris, Bridget, whose inspiration and love is immeasurable.

About the Author John A. Davis is Regional Managing Director-Asia for Duke CE, based in Singapore. His career encompasses senior leadership roles in business and academia. His expertise includes: brand/marketing/customer strategy, leadership development, and innovation, and he has worked with clients in a wide range of sectors in designing and delivering custom leadership solutions to help their organizations prepare for growth opportunities and challenges over the next several years. Prior to joining Duke CE, John was Dean and Professor of Marketing at SP Jain School of Global Management Dubai-Singapore-Sydney, Professor of Marketing and Department Chair at Emerson College; Interim Marketing Department Chair at University of Oregon; and Professor of Marketing Practice and Director for the Centre of Marketing Excellence at Singapore Management University. He received the ‘Best Professor of Marketing’ by Asia’s Best B-School Awards, the BAC Teaching Award from University of Oregon, and ‘The Most Inspiring Teacher’ from Singapore Management University. As a former Fortune 500 executive, he led marketing teams at Nike, Informix and Transamerica. As an entrepreneur he has started two award winning companies: a boutique hotel firm and a brand strategy consultancy. Measuring Marketing: The 100+ Essential Metrics Every Marketer Needs (3rd edition) is John’s 10th book. He has also written The Market Oriented University with Dr. Mark Farrell; Sports Marketing: Creating Long-Term Value, with Jessica Zutz Hilbert; Competitive Success; The Olympic Games Effect (2nd edition); Magic Numbers for Sales Management; Measuring Marketing (2nd edition); and Magic Numbers for Consumer Marketing. His articles have appeared in numerous publications, including: Harvard Business Review online, Dialogue Review, International Advertising Journal, and EFMD Global Focus. He speaks regularly at global conferences, including TEDx, BrandFinance Global Forum, World Knowledge Forum, and YPOs. He has also been interviewed by global media, including: CNBC, CNA, New York Times, ESPN. John’s wife Barb and their three children Katie, Chris and Bridget embody all that is good in the world. John and Barb have two dogs, Milo and Ninja, who spend most of their time acting goofy. Ninja likes running at full speed and jumping onto furniture at random times, and Milo watches closely, hoping that Ninja gets in trouble.

Contents Part 1: Corporate Financial Metrics  1 Chapter 1: Revenue  3 Chapter 2: Gross Profit  7 Chapter 3: Value-to-Volume Ratio  9 Chapter 4: Net Profit  13 Chapter 5: Earnings-Based Value  17 Chapter 6: Return on Sales  23 Chapter 7: Return on Assets  25 Chapter 8: Return on Equity  27 Part 2: Marketing Planning Measures  31 Chapter 9: Market Share  33 Chapter 10: Relative Market Share  35 Chapter 11: Market Growth  37 Chapter 12: Market Demand  39 Chapter 13: Market Penetration  41 Chapter 14: Program/Nonprogram Ratio  47 Chapter 15: Program/Payroll Ratio  49 Chapter 16: Causal Forecast  51 Chapter 17: Time Series Analysis  57 Part 3: Brand Metrics  63 Chapter 18: Brand Equity  65 Chapter 19: Brand Scorecards  71 Chapter 20: Brand Premium  75 Chapter 21: Brand Contribution and Review Analysis  81 Part 4: Customers Metrics  85 Chapter 22: Net Sales Contribution  91 Chapter 23: Time-Driven Activity-Based Costing  93 Chapter 24: Segment Profitability  95 Chapter 25: Customer Profitability  99 Chapter 26: Share of Customer  101 Chapter 27: Return on CustomerSM  105 Chapter 28: New Customer Gains  109 Chapter 29: Customer Acquisition Costs  113 Chapter 30: Cost Per Lead  117 Chapter 31: Retention Rate  121 Chapter 32: Churn Rate  125

xii  Contents Chapter 33: Consumer Franchise  129 Chapter 34: Customer Equity and Customer Lifetime Value  133 Chapter 35: Customer Brand Value  137 Chapter 36: Customer Losses  139 Part 5: Product/Offering Metrics  143 Chapter 37: Usage  145 Chapter 38: New Product Purchase Rate  147 Chapter 39: Marketing Cost Per Unit  151

Part 6: Price Matrics  153

Chapter 40: Price  155 Chapter 41: Mark-Up Pricing  159 Chapter 42: Target Return Pricing  163 Chapter 43: Sales Price Variance  165 Chapter 44: Markdown Goods Percentage  169 Chapter 45: Profit Impact  171

Part 7: Advertising/Promotion Metrics  175 Chapter 46: Share of Voice  177 Chapter 47: Recall  179 Chapter 48: Recognition  183 Chapter 49: Reach  185 Chapter 50: Frequency  187 Chapter 51: Gross Rating Points  189 Chapter 52: Cost Per Gross Rating Point  193 Chapter 53: Response Rate  195 Chapter 54: Conversion Rate  199 Chapter 55: Advertising-To-Sales Ratio  201 Chapter 56: Promotion Profit  203 Part 8: Direct Marketing Metrics  207 Chapter 57: Direct Marketing Revenue Goals  209 Chapter 58: Direct Marketing Profit Goals  213 Chapter 59: Direct Marketing Gross Profit  215 Chapter 60: Direct Marketing Net Profit  217 Chapter 61: Direct Marketing Return On Investment  219 Part 9: Digital/Social Metrics  221 Chapter 62: Gross Page Impressions (Or Gross Page Requests)  223 Chapter 63: Word of Mouth  225 Chapter 64: Total Clicks  1

Contents  xiii

Chapter 65: Click Through Rate  229 Chapter 66: Cost Per Click  231 Chapter 67: Cost Per Action  235 Chapter 68: Pay Per Lead  237 Chapter 69: Activity Ratio for Social Media  239 Chapter 70: Deductive Social Media Return on Investment  241 Chapter 71: Resolution Time  243 Chapter 72: Social Media Profitability  245 Chapter 73: Bounce Rate  247 Chapter 74: Return On Advertising Spend  249 Part 10: Place/Distribution Metrics  251 Chapter 75: Cost Per Sales Dollar  253 Chapter 76: Transactions Per Customer  255 Chapter 77: Transactions Per Hour  257 Chapter 78: Average Transaction Size  259 Chapter 79: Avergage Items Per Transaction  261 Chapter 80: Hourly Customer Traffic  265 Chapter 81: Returns to Net Sales  267 Chapter 82: Inventory Turnover  269 Chapter 83: Percent Inventory Carrying Costs  271 Chapter 84: Gross Margin Return on Inventory Investment  273 Chapter 85: Sales Per Square Foot  277 Chapter 86: Sales/Profits Per Employee  279 Chapter 87: Retail Close Ratio  281 Chapter 88: Retail Margin Percentage  285 Chapter 89: Percent Utilization of Discounts  287 Chapter 90: Shrinkage to Net Sales  289

Part 11: Sales Metrics

Chapter 91: Net Sales Contribution  297 Chapter 92: Absolute Index  299 Chapter 93: Relative Index  303 Chapter 94: Percent of Sales  305 Chapter 95: Independent Sales Representative Analysis  309 Chapter 96: Turnover Rate  311 Chapter 97: Recruiting  315 Chapter 98: Breakdown Approach  317 Chapter 99: Workload Approach  321 Chapter 100: Sales Performance Quotas  327 Chapter 101: Average Sales Per Call  335 Chapter 102: Close Process and Close Ratio  337

xiv  Contents Chapter 103: Cost Per Call  341 Chapter 104: Break-Even Sales Volume  343 Chapter 105: Sales Productivity  347 Chapter 106: Four Factor Model  351 Chapter 107: Sales Variance Analysis  355 Chapter 108: Sales Volume Variance  361 Chapter 109: Sales Enablement  365 Chapter 110: Net Promoter Score®  367

Introduction Some of you might recall a time when marketing was defined as advertising, slogans and logos from mostly ‘creative’ professionals, designed to embed memorable imagery and messages into the minds of target audiences in the hope they might be inspired to purchase. In those halcyon days of yesteryear, marketing was viewed by accountants primarily as a cost. When business cycles were down, marketing spending declined as well, reducing the organization’s connection to customers precisely when they need it most. This seems remarkably quaint and simple, perhaps even simple-minded, compared to today’s hyper-dynamic business world in which marketing is replete with digital and social media, conventional media, and all manner of instantaneous, crowd-based communication tools. Times have changed and are always changing. Admittedly, that’s a “Master of the Obvious” statement. Marketing has evolved over the years into a vital component of an organization’s overall strategy. Indeed, in my work with companies and research on the qualities of top performing organizations, it is clear that marketing is a primary catalyst driving greater value and sustained contribution to long-term success. How? Through a welcome focus on customer centricity and corresponding value creation. For customers, this value creation is generated by increasing emphasis on products, services and solutions that clearly address specific customer problems and needs, as opposed to the old-world product-centric view in which companies build products and advertise them relentlessly to inspire interest and purchase. In essence, value contribution is more appropriately determined by customers and this is further evidenced by a significant shift in how organizations measure that value. In effect, organizational value is measured financially by market capitalization. For publicly-traded companies, this is the total of all shares outstanding multiplied by the share price at any given time. Interbrand and BrandFinance, two leading global brand consultancies, point out that brand value is a significant percentage of market capitalization. In 2016, David Haigh, CEO of BrandFinance, stated that global total enterprise value is $89 trillion, 47% ($42 trillion) of which is attributed to brand.i My research shows that top performing companies define a brand as the entire organization as seen through the eyes of its stakeholders and not as an ad, logo or slogan. This begs the question of what organizations must do to build a valuable, and value-contributing, brand. The brand framework below summarizes the four core elements at the center that comprise a top performing brand: – Destiny: Why do we exist? – Distinction: What makes us truly unique as seen through the eyes of the market? – Culture: Who is needed to help us build our reputation? – Experiences: How will we connect with people?

xvi  Introduction Each of the four core elements is further defined by sub-components that help define them.

 Haigh, David. BrandFinance. BRICS IP Forum. November 2016. P.5. Retrieved June 3, 2017 from http://www.adamsadams.com/wp-content/uploads/2016/11/Why-Valuation-is-Key-to-Brand-Protection-David-Haigh.pdf i



Part 1: Corporate Financial Metrics Marketers have an array of challenges, responsibilities, demands, and expectations to perform their jobs successfully. They have a strategic role in today’s most successful organizations, helping to guide their companies toward achieving longterm strategic objectives. Therefore, the days of marketing being defined as creativity, advertising, and public relations are gone in today’s VUCA (volatility, uncertainty, complexity, and ambiguity), globalizing business world. Success is predicated by being astute detectors of trends and marketing influences, quickly synthesizing volumes of data, responding to rapidly changing markets and their underlying dynamics, building complex business and customer relationships, and doing all of this profitably. Marketing plans must align with corporate strategy, providing detailed insights about customer needs, how these needs will be addressed, and the probable impact to the company if the plan succeeds. Financial measures provide solid indications of overall corporate success and the results from marketing investments in customer understanding, solutions development, business model evolution, and the commercialization of promising new ideas. Marketers must therefore pay close attention to corporate-level measures and have a clear understanding of how marketing contributes to the firm’s overall success, such as the connection between their pricing strategy and the impact on revenue under different assumptions and alternative scenarios, thereby demonstrating the financial implications of their marketing choices. The financial measures described within this section are familiar to any business professional not living under a rock. Nevertheless, these measures provide marketers with a sensible review of key financial performance and the impact

DOI 10.1515/9781501507304-001

  Part 1: Corporate Financial Metrics their marketing efforts have on overall company performance. This section discusses: 1. Revenue 2. Gross profit 3. Value-to-volume ratio 4. Net profit 5. Earnings-based value 6. Return on sales 7. Return on assets 8. Return on equity

Chapter 1 Revenue Measurement Need Companies need to measure the money received from the production and sale of products and services during a specified period of time.

Solutioni Revenue is the total income from the sale of products and services, as represented by the following: R = P × Qt Where R = revenue P = price of products or services Qt = quantity in time period t Price refers to the actual price received for all products and services sold, not a budgeted or projected price. In a product-based business, quantity is simply the number of units sold. In a service-based business, revenue may be calculated by multiplying the hours worked by the billable hourly rate. Or, revenue may be calculated based on an agreed fixed fee for a contracted amount of time. Strategy consulting firms, for example, typically charge fixed fees in combination. Since services can have more complicated revenue and cost models, we illustrate by assuming a client has hired a consulting firm for strategy work and has allocated $2 million for a six month engagement with the output expected to be specific recommendations and implementation plans for how the client can more effectively grow its business (see Table 1.1).

  Chapter 1: Revenue Table 1.1: Cost Matrix Team Engagement team

Team size

Compensation

Managing partner



$,,

Associate partner



Engagement manager

% time of team members

% time of project in  year

Total cost

%

%

$ ,

$ ,

%

%

$,



$ ,

%

%

$,

Associate



$ ,

%

%

$ ,

Analyst



$ ,

%

%

$ ,

Staff



$

%

%

$ ,

Subtotal



$,,

,

$,

Other Cost

# of team members

# of days

Cost per day

Total cost

Travel

.



$

$,

Accommodation

.



$

$,

F&B

.



$

$ ,

Other

.



$

$ ,

Subtotal

$,

Assumptions: – Team members: 6 full time + 1 50% time + 1 15% time = 6.65 – 3 days per week at client – 26 week engagement (6 months) – Travel: $600 per ticket – Accommodation: $200 per day – F&B: $100 per day – Other (additional support costs, overhead): $100 per day Totals Revenues

$,,

Costs

$ ,

Net

$,,

% margin

%

Impact  

A 60% margin is quite healthy. Understanding the sources of the revenue and costs provides business leaders with an overall sense of the strength of their business.

Impact Revenue is the first indicator, and often a lead driver, of performance measurement. Revenue is included in this book because it is comprised of two ingredients vital to marketing: price and quantity; in other words, how much and how many. Revenue is, of course, merely a starting point and marketers must resist the temptation to focus only on top-line growth, because the levers that determine their ultimate financial success are clearly impacted by the costs incurred to earn those revenues. Revenue must be evaluated in the context of the total performance of the business and, for comparison, the market and the business’s key competitors. Furthermore, understanding revenue ought to inspire management to consider its sources more carefully (i.e., customers, products, price, competitors, market conditions) and how it can leverage its current level of business into additional growth.  Lisa Bigelow, How to Calculate Revenues Using a Balance Sheet. N. D. The Finance Base. Retrieved May 1, 2017 from http://thefinancebase.com/calculate-revenues-using-balance-sheet-1075.html; John W. Shoen, What’s the Difference Between Revenue and Income? 2013. NBCNews.com. Retrieved May 1, 2017 from http://www.nbcnews.com/id/7477449/ns/business-answer_desk/t/whatsdifference-between-revenue-income/#.WZF5yHcjHR0; Chizoba Morah, How Do Companies Calculate Revenue? N. D. Investopedia. Retrieved May 1, 2017 from http://www.investopedia.com/ask/answers/09/how-companies-calculate-revenue.asp i

Chapter 2 Gross Profit Measurement Need A high gross profit is one component of financial performance, which indicates costs are under control. Marketing costs can be difficult to fully control since investments in pricing, advertising, and broader communications can have an unpredictable longterm impact, even in today’s data-driven digital world. A tactic to grow market share through price reduction may also drive revenue growth, but at the sacrifice of profitability levels. Since marketers are accountable for results, they must understand whether their efforts contribute to gross profit.

Solution Gross profit is a company’s total revenue minus the costs it incurred when producing the product that generated the revenue. More simply, it is total sales less total costs (or cost of goods sold), as shown below:i Pg = R – C Where Pg = gross profit R = revenue C = costs Look at these figures from Singapore Airlines, as illustrated in Table 2.1. Table 2.1: Singapore Airlines Gross Profit Figures Period Ending

March , 

March , 

March , 

Total Revenue

US$,,

US$,,

US$,,

Cost of Revenue

US$,,

US$,,

US$,,

Gross Profit

US$ ,,

US$ ,,

US$ ,,

Source: Adapted from Yahoo! Finance. Income Statement Summary for Singapore Airlines. Retrieved June ,  from https://sg.finance.yahoo.com/quote/CL.SI/financials?p=CL.SI

  Chapter 2: Gross Profit Interestingly, Singapore Airlines’ gross profit during this period has increased even though total revenue has declined. The pace of cost reduction has exceeded the pace of revenue decline, suggesting operations are being run more efficiently despite the decline in total revenues.

Impact On the surface, gross profit does reveal details about the performance of a company except to suggest whether its performance is generally positive, or cause for concern. Gross profit is calculated before accounting for operating expenses including: selling, general, and administrative expenses; research and development; and nonrecurring expenses. Therefore, a company could have a positive performance trend with gross profit increasing each year, but the operating expenses might have increased substantially during that time (perhaps to pay for the effort to grow revenues and gross profit), which would severely affect net profit or net income. Marketers are often responsible for selling costs. Therefore, change in gross profit performance may signal that expenses are growing too quickly, not quickly enough, or are being improperly directed. Data for gross profit is found in the company income statement within the larger financial reporting effort, and follows the total sales minus the cost of the sales figures.  J. K. Shim, J. G. Siegel, and A. J. Simon, The Vest-Pocket MBA. Upper Saddle River, NJ. Prentice- Hall, Inc., 1986), 18; Investopedia. Gross Profit. Retrieved May 19, 2017 from http://www.investopedia.com/terms/g/grossprofit.asp

i

Chapter 3 Value-to-Volume Ratio Measurement Need Determine how efficient the marketing efforts are compared to the competition.

Solutioni The value-to-volume ratio (VVR) measures the firm’s estimated share of total market gross profits (either for the company overall or a specific product) compared to the firm’s share of the total dollar volume sold in the market or the product category: VVR =

% Pgm %Vm

Where VVR = value-to-volume ratio %Pgm = estimated percentage share of total market gross profits %Vm = percentage share of market total dollar volume Airbus and Boeing are the two dominant commercial aircraft manufacturers. In 2017 their respective revenues and gross profits were as follows: Airbusii

Boeingiii

Revenues

US$,,,

US$,,,

Gross Profits

US$ ,,,

US$,,,

Boeing’s VVR was:

.693 .547 = 1.267 or 126.7%

VVR =

Boeing’s %Pgm of .693 was calculated by dividing its gross profit by the combined gross profit of both airlines:

  Chapter 3: Value-to-Volume Ratio US$13.8b US$19.9b

= .693 Boeing’s %Vm of .547 was calculated by dividing its gross revenues by the combined revenues of both airlines: US$94.5b US$172.6b

= .547 Now let’s look at Airbus’s VVR:

.306 .451 = .678 or 67.8%

VVR =

Airbus’s %Pgm of .306 was calculated by dividing its gross profit by the combined gross profit of both airlines: US$6.1b US$19.9b

= .306 Airbus’s %Vm of .451 was calculated by dividing its gross revenues by the combined revenues of both airlines: US$78b US$172.6b

= .451

Impact Boeing’s ratio is 126.7% compared to Airbus’s 67.8%. Figures below 100% signal several possible concerns: costs are too high, prices are too low, or both. Conversely, Boeing appears to be highly effective at leveraging its investment. The VVR calculation signals areas of the company that need improvement, or that are being effectively utilized. Marketers can use the data to adjust their marketing program accordingly in order to drive the right financial levers that improve the VVR. If the VVR is below 100%, then marketing needs to review pricing, improve perceived value, and consider changing the product to conform more closely to market needs.

Impact  

If the ratio is higher than 100%, it likely indicates a marketing leading position. Therefore, marketing has an opportunity to capitalize on the company’s efficient performance by touting its success. Data for the VVR figures are derived from internal company reports and external industry information. Publicly traded companies will have access to broader market and competitor data from which to gather relevant statistics. Most of the leading financial sites such as Bloomberg, Yahoo!Finance, the Financial Times, the Wall Street Journal and any of the leading broadcast and cable sources, will have up-to-date market data.  i Patrick LaPointe, Marketing by the Dashboard Light. Patrick LaPointe in cooperation with the Association of National Advertisers, 2005. ii Airbus’s figures were calculated using 2017 data from parent company EADS, as reported in Yahoo!Finance. Retrieved May 22, 2017 from https://finance.yahoo.com/quote/AIR.PA/financials?p=AIR.PA iii Boeing’s figures were calculated using 2017 data from Yahoo!Finance. Retrieved May 22, 2017 from https://finance.yahoo.com/quote/BA/financials?p=BA

Chapter 4 Net Profit Measurement Need Determining whether and how much marketing contributes to the bottom line, after total costs have been subtracted from total revenues.

Solution This is the final profit after taxes; selling, general, and administrative expenses; research and development; nonrecurring; and other income statement take-outs, including operating expenses, interest, and taxes.i Pn = (V × Mc) – Em – Eo – IT Where Pn = net profit (in dollars) V = customer volume (in units sold) Mc = margin per customer (in dollars) Em = marketing expenses (in dollars) Eo = operating expenses (in dollars) IT = interest and taxes (in dollars) Margin per customer is calculated as follows: Mc = Rc – Cv Where Mc = margin per customer Rc = revenue per customer Cv = variable cost per customer Customer volume is calculated as follows: Vc = MD × MS Where Vc = customer volume MD = market demand MS = market share

  Chapter 4: Net Profit To illustrate, fictional company Global Publishing markets business books targeted to ambitious Young Presidents Organization (YPO) members (Note: YPO is a membership organization for top CEO/Managing Director/President/Board Chair leaders under the age of forty-five). Global Publishing has the following statistics: V = 400,000 Mc = $50 Em = $1,500,000 Eo = $500,000 IT = $6,500,000 NP = (CV × Mc) – Em – Eo – It NP = (400,000 x $50) – $1,500,000 – $500,000 – $6,500,000 = $11,500,000 Therefore, Global Publishing has a healthy net profit of $11.5 million

Impact Net profit helps business professionals understand how profitable their company is after accounting for additional, below-the-line expenses resulting from their business development efforts, including marketing. Net profit is a good measure for determining how effective a company is with turning revenues into real profits while keeping costs under control. This data is found in the income statement, usually at the aggregate level. Marketers must work with their finance and accounting colleagues to review accounts receivable to determine the number of customers the company has and to calculate the margin per customer. Marketing and operating expenses will normally be captured at the departmental level. Interest and taxes are tracked by finance and accounting. A key challenge is determining the customer-volume and customer-margin figures accurately, including having a detailed understanding of the organization’s actual customer base, the customer’s purchasing specifics (to help determine average margin), and a good description of the operating expenses associated with customer growth activities. Another important point is to understand what net profit might be indicating. An increasing net profit is generally good news and may signal that the company and/or its products are making more in profit per dollar of sales than in previous years. The reasons may include greater operational efficiencies that have helped to reduce costs

Impact  

as a percentage of sales. Or, perhaps it reflects a favorable tax situation, which is certainly good (although it may also mask inefficiencies in the operation). Increasing net profit can also indicate that customers perceive the price/value relationship for the company’s products favorably and, therefore, it is able to command a price premium over the competition. Increasing net profits may also highlight management strengths, since good managers are usually more effective at leveraging the budgets and investments they oversee, and they know where to deploy resources to maximize returns. Conversely, a declining net profit signals that the company is making less profit on each dollar of sales than previously due to increased taxes, operational inefficiencies and/or costs that are rising faster than sales. Decreasing net profit is a warning sign that the company’s control of its costs is diminishing and investigation followed by correction action will be needed. Similarly, there may also be factors beyond the control of management, such as rising materials/suppliers costs. Or, perhaps the company is no longer able to command the prices it once did for its products due to improved competitor offerings that are giving consumers greater choice. Leaders today are finding themselves reacting to changes occurring much faster than they can otherwise respond to. Therefore, it is incumbent on them to be adept curators of external trends and market signals since these often indicate where emerging obstacles are. The astute marketer will also realize that net profit is an important measure, which can be a source of competitive advantage. Having a thorough understanding of one’s relative net profit will be a key gauge in determining long-term competitive opportunities. If the company is able to command higher net profits than its competitors, then it will have greater flexibility to invest in growth opportunities, whether those are in adjacent or new markets, and corresponding marketing programs that not only build awareness but cultivate deeper and more loyal customers.  Adapted from R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education Inc., 2005), 473–475; Investopedia, What Is the Difference Between Gross Profit Margin and Net Profit Margin? Retrieved May 2, 2017 from http://www.investopedia.com/ask/answers/021215/what-difference-between-gross-profit-marginand-net-profit-margin.asp

i

Chapter 5 Earnings-Based Value Measurement Need Earnings are affected by many factors, including marketing investments. Understanding the mechanics of earnings-based value will help marketers recognize the connection between their marketing activities and company earnings. This is important for publicly-traded companies since shareholders want the value of their investment to increase, and earnings are instrumental in determining share price.

Solutioni Publicly-traded companies are evaluated on the performance of their stock, since it is a direct measure of value creation (or destruction) for investors. Earnings-based value is a series of calculations that help assess the value of a company and, indirectly, suggests the impact of product and marketing investment decisions on market demand. It includes using several key financial variables: earnings per share (EPS), price/earnings ratio (P/E), price/earnings growth ratio (PEG), and the year-ahead price/earnings growth ratio (YPEG). Each of these metrics build from one to the next in order to determine final earnings-based value. To facilitate a clearer understanding of earnings-based value, we must define earnings. Earnings are the same as net profit, and they are evaluated using EPS as follows:

EPS = Where

P So

EPS = earnings per share P = profits So = shares outstanding Next, we need to determine whether EPS is good, bad, or inconclusive. Earnings must be compared to the company’s share price using the P/E ratio. The P/E ratio is an indicator of a company’s growth and, indirectly, its value. The P/E ratio takes the stock price and divides its earnings from the past year (or four quarters):

P/E = Where

SP EPS

  Chapter 5: Earnings-Based Value SP = share price EPS = earnings per share The result is called the multiple, and while it is an acceptable component measure value, it is incomplete and should not be relied upon as a determinant of overall financial performance. Companies with a low P/E ratio may appear to be a good value and worthy of investment, but the P/E ratio is based on past performance and is not a good indicator of future potential. Since managers and investors are looking for future growth potential, a low P/E could also be interpreted as a company with a poor chance for future success.

PEG Ratio The PEG ratio compares historical earnings growth to the P/E ratio.

PEG =

P/E EPS (historical growth)

Where PEG = price/earnings growth P/E = price/earnings ratio EPS = earnings per share (historical growth) Theoretically, as long as your P/E ratio does not exceed your growth rate, your company is reasonably valued. A PEG of .5 to 1.0 is considered good or fair value, whereas a PEG of greater than 1.0 indicates the company may be overvalued. The PEG ratio is used by analysts when evaluating growth companies, which are defined as those where revenues and earnings are growing faster than the average company in the market.ii

YPEG Ratio The YPEG ratio has the same basic assumptions as the PEG ratio, but incorporates projected future growth rates and not PEG’s historical earnings growth rates. YPEG is more commonly used to evaluate companies with lower rates of growth, which tend to be mature firms and/or companies in slower growth markets. Overall, the same logic applies to the PEG ratio: .5 to 1.0 is good and greater than 1.0 is a potential problem. The YPEG ratio equals the current P/E ratio divided by the future earnings growth rate:

Solution  

YPEG =

P/E EPS (future growth)

Where YPEG = year-ahead price/earnings growth P/E = price earnings ratio EPS = earnings per share (future growth)

Illustration EPS A company called Good Forever (GF) has five million shares outstanding and has earned $2.5 million in the previous twelve months. GF’s trailing EPS is 50 cents: $2,500,000 5,000,000 shares = .5 By itself, EPS is relatively unhelpful and only becomes more important as management includes it into the rest of the earnings valuation analysis. P/E Ratio Now we assume that GF has a stock price of $50 per share. Using the P/E ratio, we find:

$50 .5 = 100

P/E =

The P/E is 100. If GF competes in a rapidly growing industry, such as sharing economy firms like AirBNB and Uber, then a P/E of 100, while generally considered high, may be normal for this market. However, it would also suggest an expensive company and stock.

  Chapter 5: Earnings-Based Value PEG Ratio Assuming GF’s historical growth rate is 25%, this gives us the following:

PEG = 25 =

P/E EPS (historical growth) 100 4.0

The PEG is 4.0. This indicates that GF is valued four times higher than it should be, thus it appears to be overvalued. YPEG Ratio Completing our GF illustration, but assuming that it is now a more mature firm and that growth is expected to be closer to 10% in the coming years, produces the following result:

YPEG = 10 =

P/E EPS (future growth) 100 10.0

The YPEG is 10.0, an indication of a significantly over-valued company in this case.

Impact Earnings-based value is used to help managers and investors value a company, when comparing value to time, particularly as it relates to profitability. An increase in earnings-based value may indicate whether a company’s products are accepted in the market, if it can command premium margins, and if market share is growing profitably. However, one must recognize that earnings-based value does not directly describe these factors. Rather, it serves as an indicator of the underlying factors contributing to earnings performance. Marketers have a responsibility to ensure their decisions result in positive growth, increased market awareness, and profitable product lines. Earnings-based values are complex and make certain assumptions that must be considered in the context of the company’s historical performance, that of its industry competitor set, and the future potential of the firm. Earnings-based values reflect only a subset of the potential value of a firm, brand, or product because businesses are more than an earnings stream. Earnings, in their simplest form, are merely a measure of value during a

Impact  

particular period of time and are not always correlated with examples of market success or failure, which can be frustrating to business leaders. Economics assumes a rational customer in many of its theories, yet in reality many customer decisions are the result of a unique alchemy of intuition, experience, and individual logic. Similarly, earnings-based valuations assume that the ideal world is one in which the P/E ratio and the EPS growth rate are equal, or should be very close to equal. However, there are numerous factors that affect the performance of companies and the perceptions of their products beyond the concept of fair value. Publicly-traded companies include this information in their annual reports in the sections called “Notes to Financial Statements” or “Notes to Consolidated Financial Statements.”  i The Motley Fool: How to Value Stocks: Earnings-Based Valuations. Retrieved May 9, 2017 from https://www.fool.com/how-to-invest/how-to-value-stocks-earnings-based-valuations.aspx ii Nasdaq, PEG Ratio. Retrieved June 6, 2017 from http://www.nasdaq.com/symbol/amzn/peg-ratio

Chapter 6 Return on Sales Measurement Need Understanding the amount of profit produced relative to each dollar of sales.

Solutioni* Return on sales (ROS) is a measure of a company’s ability to generate profits from sales, effectively described as the profit resulting from each dollar of sales. It is represented as follows:

ROS = Where

Pnbt S

ROS = return on sales Pnbt = net profit before tax S = sales Our hypothetical company, Global Publishing (from Chapter 4, “Net Profit”), is quite successful. Its business generated $300 million in sales and, from our earlier net profit calculation, it generated $11.5 million in profits. Calculating the return on sales ROS reveals the following:

= ROS

$11,500,000 = 3.8% $300,000,00

The results are low and suggest that Global Publishing needs to figure out how to improve its margins. Conversely, their market characteristics may also suggest that a ROS of 3.8% is reasonable. To understand if their ROS is reasonable given the market, or a signal of under or over performance, marketers must have a broad contextual understanding of the market in which they compete and the relative performance of their main competitors. If their competitors’ ROS is in the 1–2% range, then Global Publishing is performing well.

  Chapter 6: Return on Sales

Impact ROS is one indicator of the value derived from the firm’s marketing efforts. It is most effectively used when reviewed over time, rather than for a single period, since a larger historical data record can provide greater confidence to business professionals about variations from historical and industry trends. ROS does vary significantly by industry and, at times, within industries. An increase in return on sales may signal improved operational efficiency (i.e., lower expenses). On the other hand, it may reflect a change in a company’s pricing strategy. Therefore, marketers must understand which business levers impacted ROS before drawing conclusions. Higher prices may have led to the increased ROS; but are the increased prices sustainable over the long term? Is the company adding sufficient value to justify the increased price? In the following example, as Global Publishing grows it may want to focus more on increasing its margins to take advantage of the efforts made to produce its current offerings. To do this, the company needs to know if it can get the same or greater impact from investing in other marketing vehicles that are more cost effective and efficient. Data for ROS can be found in the income statement since its main components, total sales and net profits before tax, are captured here. *Note: ROS can also be calculated based on Pnat (net profit after tax). Whether before-tax or after-tax profits are used, the convention should be applied consistently across all return ratios (return on assets, return on equity). The formula is as follows: ROS = Pnat S For more information, see R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education Inc., 2005), 478.  Accounting Tools, Return on Sales. Retrieved May 3, 2017 from https://www.accountingtools.com/articles/return-on-sales.html; My Accounting Course, Return on Sales- ROS. Retrieved May 4, 2017 from http://www.myaccountingcourse.com/financialratios/return-on-sales; Investopedia. Return on Sales—ROS. Retrieved May 4, 2017 from http://www.investopedia.com/terms/r/ros.asp i

Chapter 7 Return on Assets Measurement Need The cost of operations has a direct impact on profits. Inefficient operations can place undo stress on company resources, including people and equipment. Management must measure the usefulness and productivity of operating assets due to the cost of the initial investment made to develop them, as well as the ongoing costs. Marketing is accountable since the plans they develop must be feasible from an operational and manufacturing standpoint.

Solutioni Return on assets (ROA) is a measure of efficiency based on a company’s ability to generate profits from its existing assets.

ROA = Where

Pnbt A

ROA = return on assets Pnbt = net profit before tax A = assets (assets are invested capital, comprised of debt and equity) Continuing with our Global Publishing example from previous chapters, our hypothetical management team wants to understand its effectiveness in getting as much productivity and profitability out of their assets as possible. The company’s assets are quite valuable, as is true for many firms in the “content” business, and Global Publishing is sitting on a rich treasure trove of book titles and educational programs. Let’s assume its total assets are valued at $425 million:

= ROA

$11,500,000 = 2.7% $425,000,000

  Chapter 7: Return on Assets

Impact ROA will show significant variation when different industries are compared. Heavy manufacturing and capital-intensive industries (e.g., commercial aircraft manufacturing, utility plants, and earth moving equipment) will have a lower ROA, simply because a significant investment in expensive assets (factories, machinery, equipment) is necessary for them to do business and compete successfully. Furthermore, these capital-intensive assets require significant additional investment in maintenance and replacement, which further decreases the ROA. Less capital-intensive businesses, such as management consulting, software firms, and accountancies, will have a much higher ROA since these investments (people, ideas) do not require building factories, purchasing expensive maintenance contracts, or replacement costs resulting from equipment failure, breakdown, or obsolescence. The income statement will contain information on the net profit before tax, and the balance sheet will contain information on assets. In considering this 2.7% ROA figure from our Global Publishing example, a marketer may wonder whether this is good or bad. Generally speaking, the higher the number, the better. As described above, some industries may see any number greater than 1% as a good ROA figure. Alternatively, a technology company may see 8% or more as a reasonable indicator of effectiveness for that sector. Just be aware that ROA by itself is a helpful indicator, but it is better to appraise it in the context of the company’s industry and competitor set. Management may feel good about its own 8% ROA, but if the competitors are at 11% or 12%, then they may have to take a closer look at their business to understand why their performance is below that of the industry. *Note: ROA can also be calculated based on Pnat (net profit after tax). Whether before-tax or after-tax profits are used, the convention should be applied consistently across all return ratios (return on sales, return on equity). The formula is as follows: ROA = Pnat A For more information, see R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education Inc., 2005), 478.  Amy Gallo, Harvard Business Review, A Refresher on Return on Assets and Return on Equity, April 4, 2016. Retrieved May 1, 2017 from https://hbr.org/2016/04/a-refresher-on-return-on-assets-andreturn-on-equity; Investopedia, Return on Assets—ROA. Retrieved May 1, 2017 from http://www.investopedia.com/terms/r/returnonassets.asp?ad=dirN&qo=investopediaSiteSearch &qsrc=0&o=40186; Inc., Return on Assets (ROA). Retrieved May 1, 2017 from http://www.investopedia.com/terms/r/returnonassets.asp?ad=dirN&qo=investopediaSiteSearch &qsrc=0&o=40186 i

Chapter 8

Return on Equity Measurement Need Companies are funded by shareholders whether publicly held (ownership of the company is widely dispersed among members of the public in the form of shares of stock, and the company’s financial performance is subject to specific transparent reporting requirements), or privately held (ownership is usually kept to a much smaller group of investors and the company’s financial performance is not publicly reported). Owners are interested in knowing how much profit is generated from their investment, management is responsible for the effective use of the investor’s capital, and marketers must ensure that the product and customer expenditures are effectively directed to grow revenues responsibly and profitably.

Solutioni Return on equity (ROE) is a measure of efficiency based on a company’s ability to generate profits from its stockholders’ equity.

ROE = Where

Pnbt E

ROE = return on equity Pnbt = net profit before tax E = book value of shareholder (owner’s) equity Global Publishing, our example from Chapters 4 and 7, needs more insight about the effectiveness of its business activities. The board of directors is under pressure from investors and financial analysts because, as it turns out, their 2.7% return on assets (ROA) is well below the industry average. They run another calculation, this time based on owner’s equity. Global Publishing has $92 million in owner’s equity. This is plugged into the equation to calculate the ROE:

= ROE

$11,500,000 = 12.5% $92,000,000

The same question as in previous measures should arise: is this a good or bad figure? The answer remains, it depends, as discussed below.

  Chapter 8: Return on Equity

Impact If Global Publishing’s ROE of 12.5% is above average for the industry, then the stockholders and board of directors will probably be satisfied temporarily. However, the low ROA and return on sales (ROS) ratios are causes for concern because they indicate management must focus on improving operating effectiveness and profitability to avoid significant changes in the future, including senior leadership and strategic direction. The implications from measuring ROE have limitations, however, because the ratio calculates the amount of invested capital as assets minus liabilities (this is the traditional definition of owner’s equity) and does not fully account for all invested capital. There is also debt, in the form of both short-term and long-term financial capital. Therefore, a more complete analysis must include the return on invested capital since it provides investors and the board of directors a clearer picture of the effectiveness of invested capital in generating profits. ROE, ROS, and ROA each use net profit before tax (NPBT) in the numerator as the dependent variable. However, in practical terms, NPBT is an imprecise figure at best, since it is the result of each company’s internal tracking and measurement systems. While these systems do following generally accepted accounting and financial guidelines, there is room for interpretation in each of the cost/expense areas as well as in the approach a company uses to recognize revenue. ROE can overstate (or understate) economic value due to several factors: 1. Capitalization policies: companies use different accounting methods to determine when and at what rate to capitalize an investment, whether short term or long term. If the total amount of investment capitalized is larger, then ROE is likely to be lower or understated. The converse is true as well. 2. Depreciation policies: there are rules that govern the life of an asset or investment, but these are subject to some interpretation as well. Faster depreciation rates compared to straight-line methods will yield a higher ROE, possibly distorting the actual value. 3. Leverage: companies will borrow money under the assumption that they can earn higher rates of return from investing it than the cost of the borrowing, which can distort the ROE calculation since it may tempt management to finance growth with greater leverage. 4. Project lifespan: if an invested project has a long lifespan, then the ROE is likely to be overstated since the equity resources are assumed to be productively used for a longer period of time. 5. Growth rates: if a company is growing rapidly, their ROE will be lower. 6. Lag: there is usually a lag between the investment made and when the resulting cash flow turns positive. The longer the time lag, the larger the distortion of the impact of ROE.

Impact  

Since marketing is no longer simply a department focused on advertising and is now a strategic function of the business, marketers are expected to understand the implications their investment decisions will have on ratios and what the figure indicates about their marketing plans, programs, and asset deployment. While precisely linking each individual market or product investment to a ROA, ROS, or ROE result is challenging, there is no question that marketing’s activities have a direct impact on attracting customers and, thereby, financial performance for the firm. The data for ROE is found in the balance sheet liabilities section, while the income statement will describe the net income before tax. *Note: ROE can also be calculated based on Pnbt (net profit before tax). Whether before-tax or aftertax profits are used, the convention should be applied consistently across all return ratios (ROA, ROS). The formula is as follows: ROE = Pnbt E For more information, see R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education Inc., 2005), 478.  Amy Gallo, Harvard Business Review, A Refresher on Return on Assets and Return on Equity, April 4, 2016. Retrieved May 1, 2017 from https://hbr.org/2016/04/a-refresher-on-return-on-assets-andreturn-on-equity; Investopedia, What Is ‘Return on Equity-ROE’. Retrieved May 1, 2017 from http://www.investopedia.com/terms/r/returnonequity.asp; Financial Times, Definition of Return on Equity ROE. Retrieved May 1, 2017 from http://lexicon.ft.com/Term?term=return-on-equity—roe i



Part 2: Marketing Planning Measures A company’s success is predicated on developing unique offerings that customers perceive as valuable, most often based on customer needs, distinguishing from competitor efforts and engaging with customers through a wide range of media and channels to create compelling experiences. Part of a marketer’s responsibility is estimating market potential and determining share of the total market. Marketers must also anticipate how demand is impacted by changes to the offerings. The market performance measures are used to help marketers assess their market position relative to competitors and customers and the potential impact their offerings might have, providing clearer guidance about how the company is performing and what opportunities and challenges exist. The measures in this section are: 9. Market share 10. Relative market share 11. Market growth 12. Market demand 13. Market penetration 14. Program/nonprogram ratio 15. Program/payroll ratio 16. Causal forecast 17. Time series analysis

DOI 10.1515/9781501507304-002

Chapter 9 Market Share Measurement Need Market share is used by marketing managers to measure their firm’s relative market position vis-à-vis competitors in its market.

Solution Market share describes a company’s sales (units or dollars) as a percentage of total sales volume in a specific industry, market, or product area. Market share is calculated with the following formula:

M it =

Sit Σ Sit

Where Mit = company i’s market share in time t expressed in percentage terms Sit = sales of company i in time t (in units or dollars) ΣSit = sum of all sales in time t (in units or dollars) To illustrate, Singapore Airlines had approximately US$11 billion in revenues in FY2016 (S$15.228 billion)i out of total global airline market revenues of US$736 billion.ii Singapore Airlines’s global market share is approximately 1.5%, calculated as follows: US$11b = 1.5% US$736b

Impact Market share is one way to assess a company’s success in penetrating the market, and it is often used as a goal for an upcoming business planning time period (i.e., 1–2 years). Marketing managers typically include market share as part of their marketing plan strategies and objectives. If marketing managers are responsible for a specific product, product line, or product category, then corresponding market share goals may also be established. Marketing managers need to analyze their market share indepth to better understand the sources of their market share performance. If market

  Chapter 9: Market Share share changes occurred over a specified period of time, were they ahead of schedule or behind schedule? If market share increased, are the share changes sustainable? If market share declined, what factors may have influenced this? Competitor innovation? Competitor pricing? Price discounts? Customer dissatisfaction? Reputation changes (perhaps due to quality differences)? Changing customer preferences? Market share may also be the by-product of an aging category that smarter and/or more agile companies are quickly abandoning, with remaining competitors showing increased share, but in a declining market. Market share data is found in several sources: – The company’s own finance or accounting departments will have the latest financial performance results for comparing against market results. – Total market performance can be found from industry trade reports, consulting firms, market research specialists, and business magazines. Marketing managers should compare data from multiple sources because of differences in data collection time periods, precision of measurement criteria, reporting time periods, and the collection methodology.  CAN/le, SIA’s Full-Year Net Profit Surges Nearly 119% to S$804 million. Retrieved May 28, 2017 from http://www.channelnewsasia.com/news/business/sia-s-full-year-net-profit-surges-nearly-119-tos-804m-8000360 ii Corporate Communications-IATA, Another Strong Year for Airline Profits in 2017, Press Release No. 76, August 12, 2016. Retrieved May 28, 2017 from http://www.iata.org/pressroom/pr/Pages/201612-08-01.aspx i

Chapter 10 Relative Market Share Measurement Need The need is how to measure a company’s performance compared to its leading competitor.

Solution Relative market sharei provides insight on how a brand or specific product is performing compared to the largest competitor’s performance in a specific brand or product category.

Relative Market Share (%) =

(

Brand’s Market Share revenues or units

(

)

Largest Competitor’s Market Share revs or units

)

For example, in the luxury car market in 2016 BMW and Mercedes had the following unit sales: – BMW had 2 million units; and – Mercedes had 2.23 million units. Therefore, BMW’s relative market share to Mercedes is:

2,000,000 (units) = .89 ii 2,230,000 (units) $94.16b (revenues) = .867 iii 2,230,000 (units) $108.6b BMW’s relative market share is lower in revenue terms than in units, suggesting that it has relatively lower prices per car compared to Mercedes.

Impact Brands with a larger share vis-à-vis its main competitor may also command higher profits and/or a premium position. Understanding this relative comparison can help refine brand building investments.

  Chapter 10: Relative Market Share Relative market share data is similar to market share Chapter 9, and can be found in the following sources: – Internal finance and accounting data. – External industry reports and independent/third party research firms.

 Paul W. Farris, Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein, Marketing Metrics: 50+ Metrics Every Executive Should Master (Upper Saddle River, NJ: Pearson Education, 2006), 19–20. ii Matthew Curtin and William Wilkes, Mercedes-Benz Takes Checkered Flag in 2016 Luxury-Car Sales Race. WJS Blogs, January 9, 2017. Retrieved May 28, 2017 from https://blogs.wsj.com/briefly/2017/01/09/mercedes-benz-takes-checkered-flag-in-2016-luxurycar-sales-race-at-a-glance/ iii Yahoo! Finance. Retrieved May 28, 2017 from https://sg.finance.yahoo.com/quote/BMW.DE/financials?p=BMW.DE; Forbes. Retrieved May 28, 2017 from https://www.forbes.com/companies/mercedes-benz/ i

Chapter 11 Market Growth Measurement Need Market share (Measure 9) and relative market share (Measure 10) help marketers compare their firm’s performance to that of the market and the leading competitor, respectively. To understand whether their company’s growth is faster, equal to, or less than market growth reveals insights about the dynamics of the firm’s growth compared to the rest of the market. This provides a useful clue about the relative responsiveness and effectiveness of the company’s performance, with implications affecting future marketing plans regarding customer segments, product/solution choices, channels, marketing communications programs and, even more broadly, company operations.i

Solution Market growth is determined by measuring total sales from all firms in the market and comparing this figure to the market growth in preceding time periods. This is calculated with the following formula:ii Gm = RI RL Where Gm = % market growth RI = dollars/units increase this year RL = dollars/units last year To illustrate, if the total market is $500 million this year and was $400 million last year, then the market growth rate is 25%. This was calculated by dividing the revenue increase, $100 million, by total revenues last year, $400 million: $100m $400m = .25 or 25%

  Chapter 11: Market Growth

Impact The market growth rate helps provide insight into the potential impact external forces are having on overall market performance. However, as business school students know from their finance courses and business leaders know from practice, there are no guarantees that historical growth rates will continue into the future. Marketers must measure their own company’s growth first, for two reasons: – To see what the growth trend has been over the past few years and determine whether their current pace is above or below the recent historical average. – To have a basis for comparison versus its competition and to see whether the firm’s growth is ahead of or behind the market’s. Market growth is one indicator of the relative dynamism of the company and the larger marketplace. The resulting calculation should compel marketers to do more research to understand market potential (the total number of potential customers in the target market), customer penetration levels (how many are actual customers vs. potential), the rate of customer entry/exit, and how their company’s growth compares to the rest of the market. Demographic changes, purchase behavior patterns, product innovations, and lower interest rates are examples of such factors that influence market growth. Once marketers understand these factors, they can use this information to develop plans for new products, communication campaigns, and price changes to create a competitive advantage for their products. Market data is obtained from: – Industry trade publications, independent market-research firms, product analysts, reputable business magazines, government reports, and trade associations. Be aware that to measure growth, a marketer must be quite clear about what is being measured and why. Is it growth of total market revenues? Or growth of total market dollars available for purchasing? Or is it the rate at which new customers are being acquired? Or the rate at which the 3–5 most significant competitors are growing? The answer depends on the specific market growth question being asked.  April Maguire, How to Determine and Use Your Market Growth Rate, Intuit QuickBooks. Retrieved May 22, 2017 from https://quickbooks.intuit.com/r/growing-your-business/determine-use-marketgrowth-rate/ ii R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 72, 73. i

Chapter 12 Market Demand Measurement Need Chapters 9 and 11 described market share and market growth, which are both key measures in a marketer’s performance assessment “toolbox.” Marketers need to measure total demand since it helps indicate whether there is additional opportunity for growth.

Solution Market demand describes the total demand for a particular product and/or service. It is the sum of existing/repeat customers plus new customers and can be used to measure company-level and market-level demand.i It is represented by the formula:ii Mdt = Prt + Pnt Where Mdt = market demand during time period t Prt = repeat or replacement purchases in time period t (in dollars) Pnt = new purchases in time period t (in dollars) Let’s assume that a Southeast Asian dried foods manufacturing business sells its products direct to retailers. In 2016, purchases from their existing/repeat retail customers totaled $5 million while purchases from new customers amounted to $2 million. Market demand for their product is $7 million. $5,000,000 + $2,000,000 = $7,000,000

Impact Market demand helps marketers understand the sources of customer demand for their products and services and can be an early indicator of the effectiveness of marketing and sales programs. However, it would be wise to investigate the market more deeply before reaching conclusions from market demand data alone. Market demand is an important measure, particularly in combination with market growth (Chapter 11), since an increase in both measures would suggest that a company is reaping benefits

  Chapter 12: Market Demand from its marketing efforts to take advantage of a rising market as represented by both retaining existing customers and capturing new ones. Market demand can also be a useful starting point for establishing sales objectives at the strategic and tactical levels. Strategic sales objectives include revenue targets at the market and segment levels. Tactical sales objectives would focus on more detailed expectations at the individual customer account level. Measuring market demand will thus help sales management establish appropriate sales targets for their field sales team. Data for demand, repeat purchases, and new purchases can be found in industry trade journals, industry research reports, general business magazines with special issues devoted to specific industry sectors, and the marketer’s own statistically valid research into market trends. Internally, data can be found in financial reports at the individual account level.  i InvestorWorlds. Retrieved May 25, 2017 at http://www.investorwords.com/16542/market_demand.html ii R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 77.

Chapter 13 Market Penetration Measurement Need To understand the company’s efforts to increase sales via market share growth (i.e., more customers in a given time period) and/or increased usage of its products and services (i.e., more sales to existing customers in a given time period) compared to total market sales volume of comparable offerings in that same period of time.

Solutioni Market penetration measures the sales volume of the company’s products to a target segment relative to the total target market sales for a defined period of time. p M=

Where

Si × 100 Ti

Mp = market penetration Si = sales to target segment in time i Ti = total market sales in time i Target segment is a predefined target customer group in a specific market area within a specific time period. Total market sales describes the added opportunities available to the same companies for the same products under the same conditions. Market penetration is influenced by type of product, pricing, new marketing appeals, and competitor actions. Some products lend themselves to significant short-term added potential, such as consumer nondurables (i.e., food, beverage, and grocery products). To illustrate, discounting popular grocery items can drive temporary demand and increase the total dollars spent in the market than would otherwise have “naturally” been spent. In contrast, other products have lower short-term added potential, (i.e., sports and entertainment events). Sports and entertainment events have a narrower appeal (everyone needs food, not everyone needs to attend a professional football match). Additional marketing spent on promoting the event will generate increased costs per remaining seat. A corollary measure is known as the market share index. Market share index sheds light on which areas of the company’s marketing need adjustment to improve

  Chapter 13: Market Penetration market penetration. It is closely related to market share, providing more specific information about the factors that influence customer purchase decisions and, ultimately, market share. The market share index formula is:ii Msi = Pa × PP × Bi × A × Ppur Where Msi = market share index Pa = product awareness (the number of people aware of your product in your target market compared to the overall population in the target market) Pp = product preference (is the product appealing?) Bi = intention to buy (is the price attractive?) A = availability of product (where can the product be found?) Ppur = product purchase (is buying the product a positive experience?) Beginning with market penetration, assume we are analyzing the market for traditional sushi in Sydney. The market is highly fragmented, meaning multiple competitors are vying for market share, but no single sushi restaurant dominates. Current demand indicates a market totaling $10 million in sales annually. However, past industry marketing efforts indicate that price promotions boost business by 25%. Therefore, the market potential is $25,000,000 ($20,000,000 × .25 = $5,000,000. This result is added to the $20,000,000 current demand to determine potential demand). Therefore,

= Mp

$20,000,000 = × 100 80% $25,000,000

The result shows a market penetration of 80%. For most markets, this result would be quite high, suggesting that acquiring the remaining potential customers would be increasingly expensive on a per-customer basis. However, let’s assume that, based on current market dynamics, a price promotion at this time will lead to business increases of 75%. Therefore, the market potential is $35,000,000 ($20,000,000 × 0.75 = $15,000,000. This result is added to the $20,000,000 current demand to determine potential demand), as follows:

Solution  

= Mp

$20,000,000 = × 100 57% $35,000,000

Market penetration is now 57%, which suggests there is more room for all sushi companies in the market to improve their growth. Now let’s look at growth opportunities for individual companies in this highly fragmented market. Using the second formula for market share index, let’s assume that a sushi company’s market research reveals the following statistics: Pa = Product awareness = 52% (48% are unaware) Pp = Product preference = 76% (24% find it unattractive) Bi = Intention to buy = 55% (45% do not intend to buy) A = Availability of product = 40% (60% product not available) Ppur = Product purchase = 38% (62% had a disappointing purchase experience) Plugging these figures into the formula reveals that our sushi restaurant has a market share index of 3.3%: Msi = Pa × Pp × Bi × A × Ppur Msi = 0.52 × 0.76 × 0.55 × 0.40 × 0.38 = 0.033 = 3.3% The sushi restaurant has data indicating that the overall sushi market is only 57% penetrated by all competitors and that their own share is 3.3%. Therefore, with the right mix of promotions, their market share has significant upside potential. Had the market penetration rate been closer to 100%, the task of improving share grows significantly since all companies are vying for a limited set of remaining customers. A helpful framework when conducting market penetration analysis is the Ansoff Matrix, conceived by Igor Ansoff in his 1957 Harvard Business Review article “Strategies for Diversification.”iii Ansoff describes growth opportunities in a simple two-bytwo matrix, with products across the horizontal axis and markets along the vertical access, as shown in Figure 13.1.

  Chapter 13: Market Penetration

Figure 13.1: Strategic Growth Choices

The Ansoff Matrix is a useful framework because it provides clear guidance on the marketing growth choices if market penetration is the objective—growth opportunities are limited to existing products in existing markets, and a corresponding set of activities available to successfully penetrate existing markets. The activities are: 1. Increase market share in the existing market—attract customers within the segment who are either buying competitor products or who fit the target profile but have not yet committed. Marketing tactics, such as advertising, revised pricing, short-term promotions, and/or increased investment in customer relationship development and personal selling can help inspire additional interest and purchase. The challenge is the expense of regularly creating fresh and new marketing campaigns that resonate with the market. 2. First mover advantage—typically represented by an innovative product that attracts the market’s attention before the competition has a chance to enter, allowing the firm to capture a dominant market share initially. Maintaining a longterm majority share is challenging without substantial investment in continuous marketing and research and development (the latter also begins to shift the company from a market penetration to a product development growth strategy), and

Impact  

even those added investments are not a guarantee of ongoing success. Technology markets, including software and consumer electronics, often use this approach. 3. Deep price penetration—an aggressive, low-price strategy designed to steal share aggressively from competitors by undercutting them on price. A classic example from the 1980s in the United States, was when Japanese chip manufacturers flooded the market with below-cost chips to gain market share. The primary challenge is how to raise prices to improve profitability when customers have been trained to expect a lower price. 4. Increase product usage from current customers—done by developing new uses for the product and/or creating customer loyalty plans. Examples include the airline and hotel industries. The challenges are the cost of staying current on customers’ data, the accounting liability of accumulated points programs or frequent flyer miles, and the cost of finding new personalized marketing approaches.

Impact Market penetration helps companies assess success selling to a target segment in a given time period. The market share index analyses “go-to-market” efforts. For example, in the above analysis, 76% of the people who are aware of the sushi restaurant’s product prefer it, which is a reasonably strong level of preference for the product. Interestingly, only 52% of the market is aware of the product. Therefore, the company can focus its marketing efforts on communications to increase awareness. If the sushi restaurant succeeds in increasing awareness to 75%, then their market share index increases from 3.3% to 4.7%. Msi = 0.75 × 0.76 × 0.55 × 0.40 × 0.38 = 0.047 = 4.7% Another area of improvement is in the buying experience. Only 38% of the buyers had a good buying experience. Therefore, point-of-sale training that teaches how to improve customers’ purchasing experience might be a viable solution. Assume the company does this and is able to improve these numbers so that 62% of the buyers report a positive experience. Keeping the aforementioned increase in awareness and factoring in the improved buying experience yields a market penetration of 7.8%: Msi = 0.75 × 0.76 × 0.55 × 0.40 × 0.62 = 0.078 = 7.8%

  Chapter 13: Market Penetration Be aware that understanding each variable in the market share index has its own challenges. Product awareness describes the percentage of customers in the target market who are aware of a company’s product. If awareness is low, then it indicates there is potential to increase awareness. At the same time, it will be expensive to increase awareness since more will be invested in advertising, sales promotions, and other marketing communication efforts. Improving the buyer’s satisfaction at the time of purchase will also cost money. However, if the goal is to improve penetration and beat the competition, then these would be sensible investments. As the Ansoff Matrix shows, the cost to improve market penetration is likely to be higher due to investments in pricing, advertising, and promotions. Firms focusing on market penetration may maintain consistent success due to their unique relationship with customers, developed over many years, therefore reducing the need to seek growth in the other quadrants. However, success invites competition, so it is a matter of time before competitors enter, forcing you to weigh the merits of pursuing the other quadrants. To determine potential market demand, marketers must conduct and analyze customer research, evaluate trends, establish product pricing, determine distribution, and create promotional campaigns to generate awareness. Sales management works directly with customers, developing relationships, understanding customer profiles, and determining specific solutions to address customer needs. Once a customer base is established, the challenge is how to continue growing this increasingly valuable asset. Collecting the data for the market share index requires marketers to conduct research to gather relevant data for each of the formula’s variables. The data can be gathered from surveys, with the exception of product preference and availability of product. Product preference can be calculated using a technique called conjoint analysis.iv Availability of product is determined through an analysis of your own distribution asking: – Is the product available and easy to buy? – What is the number of actual distribution points compared to the total number of distribution points? This provides a percentage of share or penetration.

 i P. Kotler, M. L. Siew, H. A. Swee, and C. T. Tan, Marketing Management: An Asian Perspective. (Upper Saddle River, NJ: Prentice Hall, 2003), 137 ii P. Kotler, M. L. Siew, H. A. Swee, and C. T. Tan, Marketing Management: An Asian Perspective. (Upper Saddle River, NJ: Prentice Hall, 2003), 137. iii H. I. Ansoff, ”Strategies for Diversification,” Harvard Business Review 35, no. 2 (September– October 1957). iv H. I. Ansoff, “Strategies for Diversification,” Harvard Business Review, 35, no. 2, (September– October 1957).

Chapter 14 Program/Nonprogram Ratio Measurement Need Organizations must understand how efficient their marketing is given the investments being made, serving as an indicator that the amount invested is being used properly applied to the intended marketing program designed to yield the desired outcomes.

Solutioni The program/nonprogram ratio (PNPR) compares the amount of money spent on marketing activities to the amount spent on the overhead and administrative inputs needed to support those activities. The result is a measure of efficiency, with higher ratios (closer to 1) indicating a more efficient operation.

Pt TSt

PNPR = Where

PNPR = program/nonprogram ratio Pt = marketing program dollar spending in time period t TSt = total support dollar spending in time period t Note: Total support dollar spending is comprised of program and nonprogram expenses.

To illustrate, assume a developer of apps has marketing program expenses of $217,000 and their nonprogram expenses were $63,000, for a total expense of $280,000. Their PNPR is 77.5%.

PNPR =

$217,000 $280,000

=.775 or 77.5% The app developer’s nonprogram activities are related to the administrative costs including telephone, legal and postage.

  Chapter 14: Program/Nonprogram Ratio

Impact Since a higher PNPR ratio is desirable, marketers would use the result to set goals for the next budget period, proposing programs for increasing the ratio’s percentage. PNPR is frequently used in nonprofit activities,ii although the logic certainly applies to for-profit as well. The challenge is determining the actual variables that comprise program and nonprogram activities. Therefore, marketing and finance should agree on a clear set of definitions, which are agreed upon with senior management. This will ensure the metric measures the same variables each time. For example, a marketer may define program activities as marketing communication designed to sell a specific product. This would include promotions, related advertising, pricing, and discount programs. Correspondingly, nonprogram activities might include legal and accounting costs plus an allocation of payroll for administrative tasks unrelated to the programs.iii  i P. LaPointe, Marketing by the Dashboard Light (2005), 99. ii Porte Brown Accounting Advisors. Retrieved May 11, 2017 from http://www.portebrown.com/Consulting-Blog/kpi-of-the-week-program-efficiency-ratio iii Guidestar. Retrieved May 11, 2017 from https://www.guidestar.org/Articles.aspx?path=/rxa/news/articles/2004/why-ratios-arent-thelast-word.aspx

Chapter 15

Program/Payroll Ratio Measurement Need The program/nonprogram ratio (Chapter 14) compares the costs of program-specific marketing activities to costs incurred in support (overhead, administration, and legal). Further insight can be gained by focusing specifically on the ratio of program expenses to payroll, and removing overhead and administrative costs.

Solution The program/payroll ratioi compares the amount of money spent on program-specific marketing activities to the payroll costs of supporting those activities.

PPR = Where

Pt MPt

PPR = program/payroll ratio Pt = marketing program dollar spending in time period t MPt = marketing payroll dollar spending in time period t Note: Marketing payroll dollar spending is salary, benefits, and related payroll costs.

To illustrate, assume a retail chain had $1 million in total marketing expense to support three stores, of which $325,000 was program spending and $675,000 was payroll, then the PPR is 67%:

PPR =

$325,000 $675,000

= ~ 48% In this example, as marketing program expenditures are increased (assuming payroll remains constant), the percentage increases, indicating increasing efficiency.

  Chapter 15: Program/Payroll Ratio

Impact A lower program/payroll ratio percentage means most expenses are for payroll activities. Organizations with this imbalance are not likely to last long, since salaries are being paid to managers who are underinvesting in marketing programs designed to reach customers. Since the goal is marketing efficiency through effective market outreach, marketers have a fiduciary and ethical responsibility to be transparent in their budget requests. Business-to-consumer (B2C) companies typically invest more in programs and similar value-creating marketing communication activities compared to business-to-business (B2B) firms. B2B organizations usually have higher sales and business development costs, since more of their market outreach is sales driven, characterized by one-to-one selling and relationship development. The chief financial officer and accounting departments track the program and payroll costs, so marketers can partner with their colleagues to gather regular information about the program and costs. Marketing budgets will differ from actual costs for many reasons, including changes to marketing program execution versus plan, timing and term differences related to changes in the marketing plan, changing personnel on the marketing team, and marketing “give backs” in the form of rebates and similar mechanisms used to provide customers with compensation when expectations are not met as promised.  i P. LaPointe, Marketing by the Dashboard Light (2005), 99.

Chapter 16 Causal Forecast Measurement Need Managers may seek to understand how many products produce (the dependent variable, or the “output”) under given demand conditions (the independent variable, or the “input”).

Solutioni A commonly used technique in causal forecasting is linear regression. In the linear regression method, when the dependent variable (usually the vertical, or y axis on a graph) changes as a result of the change in another variable (plotted as the horizontal, or x axis), it reflects a causal relationship and is represented by a straight line drawn through closely-related data points on the graph. Linear regression helps illustrate if there is a trend to the data, and is represented by a line formula: y = a + bx Where y = dependent variable a = intercept b = slope of the line x = independent variable To calculate the line formula, both the slope of the line (designated as b above) and the intercept (designed as a” above) must be calculated. The slope of the line describes the effect of the independent variable, x, on the dependent variable, y (i.e., changes in y if x changes by one unit). If there is no relationship between the dependent and independent variables, then the slope of the line would equal 0. The intercept describes where the linear regression line intersects with the y axis. The formulas are: Intercept = a = Y – bX Slope= b=

∑ xy – nXY ∑ x ²– nX ² 

Where a = intercept b = slope of the line X = ∑x = mean of x

  Chapter 16: Causal Forecast Y = ∑y = mean of y n = number of periods Once the slope of the line is determined, the strength of the relationship between the dependent and independent variables must be measured. This is known as correlation and is represented by:

r=

n ∑ xy − ∑ x ∑ y [n ∑ x ² − ( ∑ x )²] [n ∑ y ² − ( ∑ y )²] 

Where r = correlation coefficient n = number of periods x = independent variable y = dependent variable Finally, when forecasters need to calculate the percentage of variation in the dependent (y) variable that is attributed to the independent (x) variable, then the coefficient of determination is used (which measures the relationship between the dependant and independent variables). If the independent variable is changed, then what impact does that have on the dependent variable? Do the two variables “go together”? The closer the relationship, the larger the coefficient of determination, up to 1.0 (or – 1.0 for negative relationships). It is calculated by: r = r2 We use the following example to illustrate how these various formulas work together (see Table 16.1): – restaurant steak house – forecasting food sales o how many meals will be sold each week – forecasting inventory o perishable food o nonperishable food

Solution  

Table 16.1: Example Data Table Week

Number of meals served x

Quantity of beef ordered (lbs.) y

xy

x

y







,

,

,







,

,

,







,

,

,







,

,

,







,

,

,







,

,

,







,

,

,







,

,

,







,

,

,





,

,

,

,

,

,

,

 Total

,

A linear regression is then calculated as follows: X = 1,110/10 = 111 Y = 1,362/10 = 136.20

= b

∑ xy – nXY = ∑ x ² – nX ²

(155,365 ) – (10 )(111)( 136.20 ) (127,400 ) – ( 10 )( 111) ²

b = .9983 a = Y–bX = 136.20 – .9983(111) a = 25.3887 These results are plugged into the original line formula: y = a + bx y = 25.3887 + .9983(x) For x, the forecaster should select the number of meals to be served (using this example) to calculate y. Let’s select 130, as that is the approximate average number of meals served per day: y = 25.3887 + .9983(130) y = 155.17

  Chapter 16: Causal Forecast Therefore, 155 pounds of beef should be ordered. Next, the correlation coefficient is calculated to determine the strength of the relationship (also known as “interdependence”) between x and y.

r=

r=

n ∑ xy – ∑ x ∑ y

( ) ( ) 10 ( 155,365 ) – ( 1,110 )( 1,362 ) [10 ( 127,400 ) – ( 1,110 ) ²]10 ( 190,140 ) – (1,363)²] 

[n ∑ x ²– ∑ x ²[n ∑ y ²– ∑ y ²]

r = .9783 r2 = .9571 r=

r= r=

r= r=

n ∑ xy − ∑ x ∑ y

( ) ( ) 10 ( 155,365 ) – ( 1,110 )( 1,362 ) 10 127,400 ) − ( 1,110 ) ²  10 ( 190,140 ) − ( 1,363 ) ²   (  

n ∑ x ² − ∑ x ²  n ∑ y ² − ∑ y ²    

1,553,650 – 1,511,820 [1,274,000 – 1,232,100] [1,901,400 – 1,857,769] 

41,830 1,828,138,900 41,830 42,756

r = .9783 r2 = .9571 The results suggest there is a strong relationship between the number of meals served and the quantity (in lbs.) of beef ordered. Therefore, this restaurant can feel confident that its forecast will be accurate.

Impact Causal forecasts help business professionals plan for the future by measuring the relationship between two types of variables—dependent and independent. As demand conditions change, so too should the amount of product produced. In other words, the value (size, quantity, amount) of the dependent variable is directly influenced by the independent variable (market demand). A change in a product or marketing program can affect buyer behaviors (a price reduction might lead to increased purchases, albeit such a tactic often has short-lived benefits). Or, an emerging trend may signal

Impact  

a market opportunity, changing the performance of the business as a result. Causal forecasting enables managers to measure the possible impact to their business (and/or customers or other value chain participants) from these changes. For example, companies such as Nike or Adidas, both of which make athletic footwear, would be interested in forecasting how many basketball shoes to produce to sell to teen basketball players worldwide over the next three years. By reviewing census data of the teen population and surveys of growth trends in teen basketball, the companies project the potential demand for their respective products. Assuming the teen population is forecast to grow (independent variable), as is the interest in basketball, then it is plausible to project an increase in sales (dependent variable). Other examples include: – travel to ski resorts increases in winter months if weather permits; – toll roads collect more tolls during peak commute times; – demand increases for air conditioning during summer months; – increases/decreases of ice cream sales due to temperature changes; and – more workers needed at restaurants on busy nights. The result also suggests that the costs of the product can be reasonably projected. By extension, the final price offered to the customer can be determined as well. Prices should be set based on the strategic objectives for the positioning of this restaurant, its image (premium, mass market, value), cost factors, and the projected amount of business in the future. For sales people, causal forecasts are useful, particularly with controllable activities such as short-term promotions, where the outcome can be reasonably anticipated. Causal forecasting is not useful in every situation. It works best when the correlation between the dependent and independent variables is strong. Data is gathered from market research conducted by the company directly and/or an independent research firm. Historical data can be used to build a trend analysis, which serves as a guide to future potential as well. Of course, no prediction is ironclad, and as business school students know well, a company with a ten year track record of consistent double-digit growth is not guaranteed to grow at the same pace in year eleven, even despite its track record.

 Causal-Based Forecasting: Relevance Behind the Screens, Accenture. Retrieved May 2, 2017 from https://www.accenture.com/sg-en/insight-interactive-causal-forecasting-relevance-summary; Rob J. Hyndman and Anne B. Koehler, “Another Look at Measures of Forecast Accuracy” (October– December 2006); L. Lapide, “New Developments in Business Forecasting,” Journal of Business Forecasting Methods & Systems 18, no. 2 (Summer 1999); J. Scott Armstrong (Ed.). Principles of Forecasting, A Handbook for Researchers and Practitioners, University of Pennsylvania. Retrieved May 2, 2017 from http://morris.wharton.upenn.edu/forecast; G. Cachon and C. Terwiesch, Matching Supply with Demand: An Introduction to Operations Management, International Edition i

  Chapter 16: Causal Forecast  (New York: McGraw-Hill, 2006); Forecasting. Retrieved May 9, 2017 from www.uoguelph.ca/~dsparlin/forecast.htm

Chapter 17 Time Series Analysis Measurement Need Marketers must regularly make decisions about future marketing activities, including alignment with overall organization strategy, marketing program investments and budgets, pricing, customer development, sales projections, and production forecasts. Historical sales performance helps reveal trends that, depending on anticipated business conditions, can directly impact the marketing plan.

Solutioni Time series analysis is a useful method for using past quantitative data to predict future performance. Three popular methods are: – naïve forecast; – averaging forecasts; and – exponential smoothing.

Naïve forecast The naïve forecast assumes the next period’s demand will match the previous period. Forecasting requires that the variables are consistent in both the actual and forecast columns, as illustrated in Table 17.1 (i.e., use currency in both, or units). Table 17.1: Naïve Forecast Chart Period

Actual sales ($)

Forecast sales ($)

January



February









March April





May





June





July





August





September





  Chapter 17: Time Series Analysis

Period

Actual sales ($)

October

Forecast sales ($)





November





December





Averaging forecasts Averaging forecasts have several approaches–moving average and weighted moving average are two of the most common. Moving average Forecasters select a representative number of periods and calculate the average of those periods, with the result serving as the forecasted amount for the next period. As an example, consider a four month forecast period using the previous chart. In this case, the forecast is for total sales in the January–April timeframe divided by the number of periods (4), to arrive at May’s moving average. As illustrated in Table 17.2, May’s forecast sales are 88. The same process is repeated to determine June’s forecast sales (99), July’s (110), and so on. Table 17.2: Moving Average Forecast Period

Actual sales (thousands, $)

Forecast sales (thousands, $)

January



February



March



April



May





June





July





August





September





October





November





December





The moving average forecast helps correct the simplistic assumptions of the naïve forecast since the previous period’s sales are unlikely to be perfectly repeatable in the

Solution  

next period. Moving average helps smooth over variations attributable to seasonal patterns. The moving average of sales performance based on the preceding months reduces the chance that any single month’s exceptional performance (good or bad) will unduly influence the next month’s forecast. However, recent sales data is usually considered more reliable than older data since it may be indicative of current market conditions. Moving average forecasts do not account for this since the impact of recent data is reduced due to the inclusion of older data in the average. The weighted moving average can help overcome this bias. Weighted moving average The weighted moving average (or “simple” weighted average) assigns weights to data in different periods with, generally speaking, more recent periods receiving a higher weighting because they are representative of current conditions and, therefore, seen as more influential. The sum total of all the weights equals 1, therefore, each weight is a fraction of 1. Continuing with the same example, assigning the lowest weight to the earliest month and the highest weight to the most recent as follows: .1, .2, .3, .4 (see Table 17.3): May = January (75*.1) = February (75*.2) + March (90*.3) = April (110*.4) = 93.5 June = February (75*.1) + March (90*.2) + April (110*.3) + May (120*.4) = 106.5 July = March (90*.1) + April (110*.2) + May (120*.3) + June (120*.4) = 115 August = April (110*.1) + May (120*.2) + June (120*.3) + July (150*.4) = 131 September = May (120*.1) + June (120*.2) + July (150*.3) + August (110*.4) = 125 October = June (120*.1) + July (150*.2) + August (110*.3) + September (100*.4) = 115 November = July (150*.1) + August (110*.2) + September (110*.3) + October (90*.4) = 106 December = August (110*.1) + September (100*.2) + October (90*.3) + November (100*.4) = 98 Table 17.3: Weighted Moving Average Forecast Period

Actual sales (thousands, $)

January



February



March

Forecasted sales (thousands, $)



April



May



.

June



.

July





August





September





  Chapter 17: Time Series Analysis

Period October

Actual sales (thousands, $)

Forecasted sales (thousands, $)





November





December





Exponential Smoothingii Exponential smoothing is a more sophisticated approach to weighted moving average. It, too, is a popular forecasting technique used in computerized forecasting programs and wholesale and retail inventory ordering programs. Like the weighted moving average, exponential smoothing favors recent data over older data. A key difference, however, is the use of a “smoothing constant” called alpha, represented by ά. Alpha describes the level of smoothing deemed reasonable along with the speed of a company’s reaction to differences between forecasts versus actuals performance. As with weighted moving average, smoothing is a technique for reducing the impact of seasonality or more extreme variances from typical demand performance. It is always less than one and is based on the marketer’s experience and knowledge of what comprises a good response rate, combined with the characteristics of the product itself: Ft = Ft-1 + ά (At – Ft-1) Where Ft = new forecast At = actual demand that occurred in the forecast period Ft-1 = previous/most recent forecast Forecasters begin the analysis with a previous period, building sequentially to arrive at the forecast for the period needed. Past data and/or the initial forecast from which to develop the analysis is required. Adapting the earlier table, we develop a forecast for April. To determine this, the forecasts for February and March must first be calculated. For February, we need to know Ft-1, the previous/most recent forecast (January, in this case). We assume it was 70 and that alpha is .6. The following result occurs for February (see Table 17.4): Ft = 70 + .6(75 – 70) = 73 An identical approach is used to determine the figures for March: Ft = 73 + .6(75 – 73) = 73 [I get 74.2]

Impact  

Finally, April is calculated: Ft = 74.20 + .6(90 – 74.20) = 83.68 Table 17.4: Exponential Smoothing Period

Actual sales (thousands, $)

Forecast sales (thousands, $)

January





February





March



.

April

.

May June July August September October November December

Once the actual data for April is known, May can be forecasted, and the process continues as each month’s actual sales are included.

Impact Marketers are accountable for developing forecasts to help determine market demand for their offerings. A time series forecast utilizes historical data and serves as a starting point for determining potential future performance, which would then affect marketing investment planning decisions. Time series forecasts help marketers observe and understand seasonal variation patterns in data as well as growth rate changes. However, marketers must be alert to the pros and cons of time series forecasts: – They are never 100% reliable. – Time series forecasts tend to be more accurate with shorter time frames (i.e. it is easier to predict tomorrow than it is next month, or next year). – Time series analysis tends to assume that the future will be like the past. – They tend to be more credible when based on longer data histories (i.e., using several months or years of data is better than several days). – Newer data tends to be more reliable than older data and receives a higher weighting as a result.

  Chapter 17: Time Series Analysis When forecasting, marketers must determine if the sales trend is increasing, decreasing, or flat. Time series analysis can be helpful in answering basic trend questions as it may suggest emerging opportunities or, conversely, warning signs. But time series analysis is less useful for understanding and determining the causes that underlie trends. How do anomalous events such as external market disturbances (natural or man-made disasters), aggressive new marketing campaigns, or competitive behavior affect demand? What are the reasons for the seasonal variation? Time series analysis is a good first step toward developing a better forecast, but marketers must consider these other influences when developing their marketing plans. The data for time series is found in historical business reports from finance, field sales, and production. As leaders in their respective organizations, marketers must turn on their proverbial antenna to detect weak signals in the market place as these, often more than historical patterns, will provide important guidance for factors that may impact their business planning assumptions.  i Hossein Arsham, Time-Critical Decision Modeling and Analysis. Retrieved May 22, 2017 from http://home.ubalt.edu/ntsbarsh/stat-data/Forecast.htm#rgintroduction; Reference for Business, Forecasting. Retrieved May 22, 2017 from http://www.referenceforbusiness.com/management/ExGov/Forecasting.html; Bob Namvar, “Economic Forecasting—How the Pros Predict the Future,” Graziadio Business Review 3, no. 1 (2000). Retrieved May 23, 2017 from http://gbr.pepperdine.edu/001/forecast.html; Qualitative Forecasting, Tutor2u. Retrieved May 22, 2017 from http://www.tutor2u.net/business/marketing/sales_forecasting.asp ii G. Cachon and C. Terwiesch, Matching Supply with Demand: An Introduction to Operations Management, International Edition (New York: McGraw-Hill, 2006).



Part 3: Brand Metrics Brands are the entire organization as seen through the eyes of stakeholders. Stakeholders comprise employees, customers, value chain partners, shareholders, community groups, and even the market and society at large. In this regard, a brand embodies a much broader and multidimensional definition, including products, services, reputation, experiences, partners, employees, and even more. This may strike many as overly expansive, giving brands greater credibility and influence than they historically had. But the twenty-first century is clearly not the same as the twentieth century, and the now seemingly quaint and neatly contained business definitions are inadequate to describe today’s hyperdynamic business world defined by rapidly advancing digital tools, social media, and a complete flipping of the locus of control from companies to customers. As a result, companies in almost every industry must take their branding efforts more seriously than ever before, because of the additional value conveyed by a brand. In sheer value-creation terms, even if the offering is identical to a lesser-known competitor, a well-known brand can command a higher price. With the growing complexity of markets and the expansion of product choices, brands play an increasingly important role. Brands are a form of trust between customers and companies, between the market and organizations, and between society and the institutions that structure and define our conduct. Today’s marketing strategies involve developing brand experiences that go far beyond a product or price. A brand experience describes the multifaceted effort by companies to connect to customers with entertainment, lifestyle, communication, and relationship development. Each of these components is seen as part of the customer’s overall use of, and attachment to, products and services.

DOI 10.1515/9781501507304-003

  Part 3: Brand Metrics Nike’s Niketown stores, Apple stores, Emirates pre/during/postflight experience, Alibaba’s Annual Singles Day, Singapore’s Changi Airport, and Bangchak’s retail petrol stations in Thailand are a microcosm of the examples of organizations that have focused on customer experience as a driver of meaningful and valuable reputation differentiation. Each shapes the customer’s perception and strengthens their relationship with the brand. For marketers, branding has evolved from a simple effort of developing a logo and slogan to a multidimensional experience designed to engage with communities of people all over the world. In business, brands are strategic assets, and companies must shift their attention from selling ordinary products to creating extraordinary experiences that inspire emotional value for customers. When brand experiences are delivered thoughtfully and well, the by-product is improved financial gain. Brand measures, particularly brand equity, help companies understand the complexity in measuring brands and brand performance. Even with the measures within, business professionals must recognize that brands are not easily measured, nor is there a universal standard for brand valuation. It is naïve to assume brands can be distilled down to a few perfectly precise measures. Brands are complex strategic assets comprised of tangible and intangible inputs. The metrics discussed in this section are: 18. Brand equity 19. Brand scorecard 20. Brand premium 21. Brand contribution and review analysis

Chapter 18 Brand Equity Measurement Need Business leaders must know the value their brand contributes to their company and/or products beyond book value. Organizations that are known for having positive reputations typically command higher valuations and prices than their lesserknown competitive counterparts, and measuring this helps company leadership understand the sources of their market strengths. This requires today’s companies to be deeply attuned to the needs of their customers, beyond classic segmentation, targeting, and positioning theory. To attract and create loyal customers, a company must be customer-centric. This is more than smiling and being friendly. Customer centricity is an explicit investment in being customer-driven and organizing the company’s resources to support this effort. Talking directly to customers to understand their needs, pains, and gains can positively affect the company’s reputation with the market and lead to more distinctive offerings and more sophisticated customer engagement and communication. Since marketing is a strategic asset in today’s business world, company leaders must understand the total value marketing adds to the business at both the tactical and strategic levels as this accounts for the impact of the brand in the market place. Measuring brand equity has several statistically valid approaches, each helping calculate the intangible value associated with the concept of “brand.” Interbrand, a global brand consultancy, uses a proprietary methodology, the results of which are popularized in their annual Global Brands Scorecard study. Their approach values assets based on how much they are projected to earn in the future.i The challenge is clearly identifying and valuing the intangible factors that are the sources of brand equity. Products often elicit an affective and emotional response from consumers. Singapore Airlines has a highly regarded reputation for consistently superior service in all travel classes, and is consistently among the very top of the annual airline ratings. Its customers know and trust Singapore Airlines and will pay a premium for the superior service offered. Mental images appear when particular companies are mentioned. One of the most significant business trends of the past decade has been design thinking, as represented by IDEO, a U.S.-based consultancy. When IDEO is mentioned, the image of creative, techie, breakthrough thinking is conjured. When electric cars are discussed, Tesla quickly comes to mind. These rapid and varied responses reflect the reputation of the entity. But what is the value of this reputation? While not an easy question to answer, the following simple technique serves as a helpful guide.

  Chapter 18: Brand Equity

Solution: MacInnis and Park Brand Brand Equity Methodologyii Deborah MacInnis, professor of marketing at USC’s Marshall School of Business, and C. Whan Park, the Joseph A. DeBell professor of marketing at USC’s Marshall School of Business, describe brand equity “as the financial value of brand reflecting its efficiency in attracting and retaining customers.” Table 18.1: Industrial and Marketing Accounting Systems

Source: MacInnis, Deborah; Park, C.W., “Making the Most of Your Brand: Leveraging Brand Equity Through Branding Strategies”, March 2004. Retrieved May 30, 2017 from http://www.marketingprofs.com/4/macpark2.asp.

They describe a marketing accounting method similar to industrial accounting, but with marketing costs substituted for the cost of goods sold. When marketing costs are subtracted from total revenues, a gross magnitude of brand value figure results (Table 18.1). Calculating the return on marketing (brand value divided by marketing costs) helps determine the effectiveness of marketing investments made on behalf of the brand (see Table 18.2).

Solution: MacInnis and Park Brand Brand Equity Methodology  

Table 18.2: Example 1 of Brand Valuation

Source: MacInnis, Deborah, and C. W. Park. “Making the Most of Your Brand: Leveraging Brand Equity Through Branding Strategies”, March 2004. Retrieved May 30, 2017 from http://www.marketingprofs.com/4/macpark2.asp

A brief look at companies A and B in case 1 shows they have identical brand values, but Company A has a higher return on marketing costs, a sign that Company A is more Table efficient with its marketing expenditures (see Table 18.3). Table 18.3: Table 18.3. Example 2 of Brand Valuation

Source: MacInnis, Deborah and C. W. Park, “Making the Most of Your Brand: Leveraging Brand Equity Through Branding Strategies”, March 2004. Retrieved May 30, 2017 from http://www.marketingprofs.com/4/macpark2.asp.

  Chapter 18: Brand Equity Case 2 shows that Company A has a larger brand value than Company B, but Company B has a better return on marketing costs. If this were to continue over time, Company B would eventually overtake Company A in brand value (assuming the other figures remain in the same relative proportions). MacInnis and Park’s basic brand value calculation is an initial pass at determining the magnitude of gross brand value. It is reasonable to assume that brand value would be attached to a company’s marketing efficiency—companies with better marketing efficiency (higher ratio of brand value to marketing costs) should be rewarded with a higher brand value than companies with a lower marketing efficiency. The converse is likely true as well. Finally, MacInnis and Park mention that this analysis is useful when evaluating the same brand in the same industry. But if the brand valuation objective is to compare your brand with that from a different industry, then the formula must be adjusted to reflect differing growth rates in each industry. The rationale is that growth rate differences between industries can distort brand-to-brand comparisons since one industry may be growing overall and, thereby, lifting the value of most companies within (a simple example is the prebubble property market of 2007–2008 in the United States and United Kingdom), while a brand being compared to another industry may be affected by a slowdown in its industry (e.g., global newspaper industry). In either case, individual brand values are distorted by larger industry forces. Therefore, adjusting the formula by adding growth rates would be useful: Marketing Efficiency × Total Revenues ÷ 1+ (1 + growth rate) × Marketing Efficiency

Impact This approach borrows from classic accounting techniques and, consequently, serves to succinctly illustrate the concept of brand equity. The MacInnis and Park methodology also demonstrates the challenge in precisely determining brand value. As with any model, the challenge is in determining the best possible estimates. With MacInnis and Park, calculating the marketing efficiency, or the return on investment on marketing costs, is affected by a few not entirely controllable factors: the response of customers to a marketing communication effort, assumptions the company makes about its marketplace and its customers, and the reaction of competitors and how their strategies might impact on or even disrupt your plans. There are several online sources available for those interested in learning more about brand equity: – Futurebrand: www.futurebrand.com – Interbrand: www.interbrand.com and www.brandchannel.com

Impact  

– – – –

Brand Finance: www.brandfinance.com Landor: www.landor.com Young and Rubicam’s Brand Asset Valuator: www.yrbav.com

 R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, Inc., 1997, 2000, 2004, 2005), 220–223. ii Deborah MacInnis and C. W. Park, “Making the Most of Your Brand: Leveraging Brand Equity Through Branding Strategies,” March 2004. Retrieved October 9, 2011 from www.marketingprofs.com http://www.marketingprofs.com/4/macpark2.asp i

Chapter 19 Brand Scorecards Measurement Need To identify and assess the intangible factors within brand equity.

Solutioni Brand assets and liabilities are scored compared to the average brand in that market. Roger J. Best suggests thinking of brand equity as the analog to the owner’s equity in the balance sheet. The difference is that brand equity is determined by subtracting brand liabilities from brand assets, and a scorecard for each is used.

Brand Assets Brands are comprised of five primary assets: 1. Brand awareness: how aware are consumers of your organization and/or its offerings? 2. Market leadership: what is your market share? 3. Reputation for quality: are you perceived as offering superior quality? 4. Brand relevance: are your offerings relevant to the customers you target? 5. Brand loyalty: do customers remain loyal to your offering over time? A marketer would compare their individual brand to the average brands in the market. Each of the five categories of brand assets are scored on a 1–20 point scale (20 being most valuable), with a maximum score of 100 for all five assets combined.

  Chapter 19: Brand Scorecards Table 19.1: Brand Asset Scorecard Brand Assets

Below average ()

Somewhat below ()

About average ()

Somewhat above ()

Top performer ()

Brand asset score

Brand awareness Market leadership Reputation for quality Brand relevance Brand loyalty Total brand assets

Brand Liabilities There are five brand liabilities: 1. Customer dissatisfaction: how high are customer complaint levels? 2. Environmental problems:* are your environmental practices poor? 3. Product or service failures: is product quality low? 4. Lawsuits and boycotts: is your company facing legal problems? 5. Questionable business practices: are there ethical lapses? *Note: Corporate social responsibility (CSR) is increasingly important as a determinant of reputation. Does a company ignore the communities in which it operates? Does the company consider investment in sustainable business practices a poor use of invested capital? If so, then a low CSR score would likely follow.

Similar to brand assets, marketers would want to score their companies and/or products on the chart below (see Table 19.2).

Solution  

Table 19.2: Brand Liabilities Scorecard Brand assets

Below average ()

Somewhat below ()

About average ()

Somewhat above ()

Top performer ()

Brand liability score

Customer dissatisfaction Environment Product failure Lawsuits Questionable practices Total brand liabilities

The final step is to subtract brand liabilities from brand assets. The difference provides a simplified view of brand equity, albeit a subjective one as well. Figure 19.1 reinforces the brand balance sheet metaphor in a diagram.

Figure 19.1: Calculation of Corporate Equity and Brand Equity

  Chapter 19: Brand Scorecards

Impact Marketers can use this brand scorecard for a quick assessment of their brand equity relative to their average competitor and derive a score that indicates the relative strength of the brand. Best’s framework helps address the intangibles at a general level and serves as a useful starting point for further analysis, but the question of a clear definition of each intangible’s source of equity remains. Marketers should dig deeper to decode the five brand assets and five brand liabilities to determine where their brand is vulnerable, and where their strengths can be further leveraged. The data is gathered from market research reports about the brand’s reputation in the market, surveys and interviews with customers and other key stakeholders, and a transparent accounting of the brand’s self-view.  R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, Inc., 1997, 2000, 2004, 2005), 220–223. Cited in John Davis, Measuring Marketing: 103 Key Metrics Every Marketer Needs (Singapore: John Wiley & Sons (Asia) Pte. Ltd., 2007), 236–240.

i

Chapter 20 Brand Premium Measurement Need Building a strong, well-regarded and trusted brand is often first among equals for business leaders today since significant additional measurable value can be captured and delivered by having a premier reputation. This distinction is also known as a brand premium, a concept that means customers believe the products are different and offer unique value that is relevant to their needs. When a brand’s unique value is clear and meaningful to the customer, it can typically command a premium price, versus the less-differentiated offerings from the competition. The challenge is determining what is “unique” and whether that uniqueness warrants a premium price.

Solutions We will highlight two approaches to brand premium:

Approach A A brand premium is the price that can be commanded above the “normal” expected market price as a result of one or more distinctions: – A strong brand name, recognized superior quality or performance; – A product with unique features or an entirely new product. Yeti, which makes high end coolers for outdoor activities, commands a premium for its products. For example, its Tundra 350 Cooler, has a retail price of US$1,400, and many of Yeti’s other premium coolers are priced in the $200-$400 range. Yeti commands premium prices higher than the average cooler maker (which range in price from a few dollars for truly cheap Styrofoam coolers to subpremium brands costing approximately US$100):i BP = Pab – Pac Where BP = brand premium Pab = average retail price of a branded product

  Chapter 20: Brand Premium Pac = overall average retail price for that product category To illustrate using the cooler market example, a premium branded cooler that charges an average price of $400 in a category where the average retail price is $100, commands a positive price premium of $300. BP = $400 - $100 = $300

Approach B If that same premium branded company were charging $90 for their branded shirt and the average retail price for that category remained at $100, then the company would have a negative brand premium of -$10—an unenviable situation.

Impact Brand premium is closely correlated with corresponding pricing strategies. Skimming, for example, is a price strategy pursued by marketers to charge the highest possible price for uniqueness or innovation relative to current substitutes. Skimming strategies are targeted to exclusive, high end customer markets where there are a sufficient number of customers to sustain the business, but not so many as to attract competitors. Products with a superior image and reputation can be good candidates for skimming. Skimming pricing helps convey and reinforce a strong brand image and, overall, positively impacts brand equity. The brand premium formula introduced earlier implied that a premium is simply the difference between a branded product’s price and its competitor’s price. To fully understand brand premium, company market research should focus on consumer perceptions of their brand in comparison to competitors’ offerings. Factoring in the company’s reputation, perceived quality and relative market position will further sharpen the marketer’s understanding of their brand’s premium position. However, it is important to recognize that these are qualitative assessments, with interpretation and judgment as guides. Rigorous quantitative precision in determining premium price can be tricky since market perception and customer experience plays a substantial role in understanding whether a brand premium is possible and sustainable. While many pricing models are influenced by costs, premiums are affected more by brand image, reputation, and equity. Specifically, the value of a brand directly affects the credibility associated with the premium charged for its products. Mercedes

Impact  

and BMW can charge a price premium for their cars because their brands are consistently associated with a higher perceived value. Lexus was launched as a new brand, not linked to Toyota, in part due to the association the Toyota brand reputation had with entry-level and mid-market cars. Rolex is widely considered a top-quality watch. Despite the addition of gold and diamonds in some models, many of Rolex’s components (mechanisms that make the watch work) are very similar to those used in other watch brands, whether at the luxury or commodity ends of the spectrum. So what are Rolex customers buying? They are buying prestige, image, tradition, reputation, and association with a sociodemographic audience that is among the top 1% of income earners. How has Rolex been so successful in capturing this audience and in convincing them that its watches are worth the money? Rolex watches have a highly regarded decades-long global reputation for quality luxury watches. We never read about quality control issues or product recalls from Rolex. Concomitant with quality is implied expertise in workmanship. Rolex has figured out over the years how to build an extremely reliable watch with nearly flawless components that has been a favorite of “ultra-successful” people for years. This suggests its customers believe in Rolex’s promise of quality, find its high-status image appealing, and are not disappointed by the product once they use it. Clearly, quality is part of Rolex’s premium, but so is its reputation for being worn by the most discriminating customers. Rolex’s customers get a psychological reward for wearing a Rolex. Does that warrant its premium image? Psychologically, people prefer to associate with others similar to them, and/or aspire to be like other people whom they perceive as being successful. But beyond quality and discriminating customers, there are still other factors that contribute to Rolex’s premium image: tradition and brand associations (golf, yachts, luxury cars) that serve to reinforce the reputation. Each of these ingredients collectively create the premium image Rolex enjoys. The challenge, of course, is how to maintain this image. As watch aficionados know, there are watches considered to be ultra-premium. A listing of the top twenty luxury watch brands ranked Rolex #7, with Audemars Piguet #1. Audemars Piguet makes only 36,000 watches per year, whereas Rolex makes 2000 watches per day.ii Most of the great luxury brands took years to develop their reputations. Many great luxury brands are considered one of a kind. The company’s management must have tremendous focus, dedication, and a clear understanding of the company’s purpose and heritage to consistently uphold these values, especially in difficult business conditions. Furthermore, despite the tradition associated with many luxury products, tradition alone will not sustain them indefinitely. Rigorous work goes into the details of the world’s leading premium products. The service at Four Seasons or Banyan Tree is the result of years of training of employees, devotion to mission, a clear understanding of customers, and a commitment to retaining the best employees, who understand all of this. Similarly, the prestige associated with Rolls Royce and Rolex is the result of dedication to first-rate quality. The bottom line is that these firms are

  Chapter 20: Brand Premium passionately committed to protecting their reputations, retaining the absolute loyalty of their customers, and maintaining the mystique of their products. It is part of their brand DNA. However, maintaining a premium price is tricky for the same reasons that sustaining a premium image is challenging. Branded products sold below full price risk dilution of their brand image. Interestingly, while it is hard to recall an instance when there has been a Rolex discount, Mercedes and BMW regularly offer financing or even direct-from-sticker discounts (despite their luxury positions). Each of these companies attracts a high end customer and each has been largely successful in maintaining its image over time. But clearly each would suffer if a prolonged program of price discounting were codified. Cunard Line,iii a respected luxury cruise line that is over 175 years old, confronted pricing challenges in the early 1990s following the First Gulf War. At the time, Cunard operated seven ships, five of which were five-star vessels and the other two four star. Cunard had 50% of the five-star market but, for the first time in its 160-year history, it was facing dwindling demand and competitive discounting. Customers traveling on a Cunard ship expected and received an extraordinarily high level of service. However, increasing evidence suggested that the culture of cruising was changing and passengers were finding the more family-oriented atmosphere of the emerging cruise lines to be attractive. Cunard wrestled with this, and responded by offering promotions, effectively discounting their original service. These promotions came in several forms: a shopping spree at Harrod’s, travel on the Concorde, reduced fares for the second passenger, and even a one-day sale. The promotions dented Cunard’s reputation, which was further hampered by an incident in 2006 when its Queen Mary 2 ship suffered damage to one of its propellers, forcing a delay in its scheduled Latin American cruise. As the ship continued on its journey after repairs, it announced the elimination of several ports of call along the way in order to make up time in the schedule. Passengers were incensed. After an initially slow response to its passengers, Cunard offered a 50% refund, but the announcement at sea and the subsequent poorly handled public relations had angered passengers who felt the refund was insufficient. Cunard eventually relented and agreed to a full refund for those who sought it. The question is whether this situation harmed Cunard’s former superior reputation permanently, or temporarily. Either way, the worldwide media coverage tarnished Cunard’s image for a few days.iv Fast forward to today and Cunard focuses exclusively on five-star, ultra-luxury cruising with the Queen Mary, the Queen Elizabeth, and the Queen Victoria ships. Cunard obviously concluded that protecting its prestigious upper-class legacy was more important than chasing the discounted four-star and family-cruise approaches.

Impact  9  Stores. Premium Outdoor Lifestyle Brand YETI’s First Store Sets the Scene for Sales. Retrieved June 23, 2017 from http://stores.org/2017/06/12/creatively-setting-the-mood/; Coolers on Sale. Yeti Coolers on Sale-Are They Worth it? Retrieved June 21 from http://www.coolersonsale.com/ ii Johnny Mannah, TheTrendSpotter.Net. 20 Top Luxury Watch Brands You Should Know. Retrieved June 17, 2017 from https://www.thetrendspotter.net/2016/01/20-top-luxury-watch-brandsknow.html iii S. A. Greyser and R. F. Young, “Cunard Line Ltd.: Managing Integrated Communications” Case # 9594-046. The President and Fellows of Harvard College (1994). iv BBC News. QM2 Passengers to Get Full Refund. Retrieved May 11, 2017 from http://news.bbc.co.uk/1/hi/world/americas/4652724.stm i

Chapter 21 Brand Contribution and Review Analysis Measurement Need To help maximize brand value, marketers need to determine each brand’s tangible and intangible contributions to the company’s market capitalization. As a consequence, investment decisions, resource allocation, repositioning, and even divestments can be more easily determined.

Solutioni The following tool provides management with a snapshot review of financial and nonfinancial criteria of each brand’s contribution. Financial (annual) Revenues (attributed to the brand) Subtract Brand-Specific Marketing Costs Gross Brand Contribution

$ _____________________ $ _____________________ $ _____________________

-------------------------------------------------------------------------------------------------------------------Brand contribution as % of firm’s total revenues

_____________________ %

Brand contribution as % of firm’s total profits

_____________________ %

Brand contribution as % of firm’s total customers

_____________________ %

Brand market share

_____________________ %

-------------------------------------------------------------------------------------------------------------------Brand value increase/decrease

$_________& % _________

--------------------------------------------------------------------------------------------------------------------

  Chapter 21: Brand Contribution and Review Analysis Brand

1 = poor

Market awareness Contribution to company reputation Reputation with customers Reputation with suppliers Reputation with employees Ability to extend/stretch Clear differentiation

1 1 1 1 1 1 1

Product

1 = poor

Quality Reliability Relevance to customers Clear connection to product category Addresses specific needs Compares favorably to competitors

1 1 1 1 1 1

Brand Management

2 2 2 2 2 2 2

2 2 2 2 2 2 Yes

5 = excellent 3 3 3 3 3 3 3

4 4 4 4 4 4 4

5 5 5 5 5 5 5

5 = excellent 3 3 3 3 3 3

4 4 4 4 4 4

5 5 5 5 5 5 No

Strong team ______ _______ Good decision making ______ _______ Realistic business plans ______ _______ Proactive ______ _______ Profitable business ______ _______ *improved over prior years? ______ _______ Handles crises well ______ _______ Flexible ______ _______ Communicative ______ _______ Measures results ______ _______ Good internal reputation ______ _______ Good industry reputation ______ _______ Retraining needed ______ _______ *explain briefly __________________________________________________________ Strategic Good growth prospects *Revenues *Profits *Customers

Yes

No

______ ______ ______ ______

_______ _______ _______ _______

Solution  

Favorable economic conditions Advances firm’s strategic objectives Relevant to brand’s market segments Favorable market trends Overlap with firm’s other brands *Is this a problem? Growth potential in new geographies Growth potential to new customer segments Customer Number of customers Market share New segments Revenues per customer Profits per customer Share of customer wallet Needs fulfilled Market Growth potential Competitive threats Supplier strength Regulatory restrictions Environmental concerns Sociocultural benefits Marketing + Receiving appropriate advertising support Influential customers Consistent marketing communications Clear brand message – Unplanned additional sales force effort Uneven channel support Confusing and/or overlapping offerings Product quality problems Unreliable suppliers Unexpected competitor moves

_______ _______ _______ _______ _______ _______ _______ _______

______ ______ ______ ______ ______ ______ ______ ______

Gain?

Loss?

_______ _______ _______ _______ _______ _______ _______

______ ______ ______ ______ ______ ______ ______

High

Low

_______ _______ _______ _______ _______ _______

______ ______ ______ ______ ______ ______

Yes

No

_______ _______ _______ _______

______ ______ ______ ______

_______ _______ _______ _______ _______ _______

______ ______ ______ ______ ______ ______

  Chapter 21: Brand Contribution and Review Analysis Marketing (cont.) Social media Company press Industry press Customer support and satisfaction Word of mouth Net promoter scores Corporate Overt senior management support External corporate crises/challenges Shareholder support Employee turnover Internal operations challenges Budget support for growth plans

Favorable ______ ______ ______ ______ ______ ______ Yes ______ ______ ______ ______ ______ ______

Not Favorable _______ _______ _______ _______ _______ _______ No _______ _______ _______ _______ _______ _______

Impact Beyond determining resource allocation, the Brand Contribution and Review Analysis can serve as a brand dashboard, useful in strategic planning, including relationships among and between brands in a multibrand company. Management can also gain a stronger sense of which brands are capturing customer attention and if that implies changing trends and/or investment opportunities. Positive responses should be explored further for opportunities to exploit. Negative responses should lead to additional investigation to determine severity. Data for the Brand Contribution and Review Analysis would be captured from internal financial reports, customer surveys and customer relationship management profiles, sales performance reports, and research about market trends.  i John A. Davis, Competitive Success—How Branding Adds Value (John Wiley & Sons, 2010), 83–86.



Part 4: Customers Metrics A key expectation of marketers is to clearly analyze and describe the markets they are targeting and the customers within. Marketers need to evaluate and defend why they believe the markets they wish to enter are attractive. Senior management is likely to ask: – Is the market opportunity large enough to justify the financial and resource commitments marketers are recommending? – Is the market growing at an attractive rate? – Can the company build leading and/or defensible share of market? – Does each of the segments offer attractive profit potential? The role of marketing is to help the company grow by attracting and retaining customers by identifying and analyzing four areas: 1. Customer needs 2. Segments 3. Targets 4. Positioning

Needs Successful customer development requires that marketers begin with research to identify and understand needs that exist in the market. This initial research will enable marketers to determine if the needs can be successfully addressed by their company. There are two common types of needs that research helps uncover:

DOI 10.1515/9781501507304-004

  Part 4: Customers Metrics 1.

Articulated: o These needs are clearly described by customers to the marketer, such as, “I would like this car to have leather seats.” The customer is able to easily convey their needs based on existing experiences with products. Understanding articulated needs helps companies improve existing features, extend product lines, or offer valueadded enhancements, such as VIP service. 2. Latent: o Identifying latent needs can reveal entirely new opportunities through new products and new markets. Innovation is an important ingredient in successfully tapping into latent needs. The challenge for marketers is that latent needs are hidden and unknown. They are much harder to identify since customers have difficulty imagining true innovation versus offering the incremental improvements described by articulated needs. In their book, Blue Ocean Strategy, W. Chan Kim and Renée Mauborgne discuss “The Four Actions Framework,”1 which provides guidance for companies seeking wholly new opportunities outside conventional strategic planning approaches. Among the companies they cite, Cirque du Soleil stands out as a company that created an entirely new market and customer base: those seeking a unique entertainment blend of live music, theatre, art, and acrobatics mixed with select circus themes (sans animals!) to create an unparalleled experience. Guy Laliberté, founder of Cirque du Soleil, did not conduct the classic marketer’s retinue of focus groups, surveys, test markets, or even ROI to develop the company and its products. It simply happened. In a similar fashion, the original Polaroid camera developed by Edwin Land was not the result of extensive market research or consumer testing. No consumers approached him to articulate that instant photography was what they needed, other than his daughter casually telling him that it took too long to develop film. When Polaroid cameras came out, they revolutionized photography, despite the lack of evidence to support pursuing and marketing a significant innovation.

The marketer’s efforts to identify and understand their customer base directly influences how a company’s offerings are developed and communicated to maximize their appeal to the target audience.

Part 4: Customers Metrics  

Segmentation The next step is identifying segments comprised of groups of customers that share a common set of characteristics, including similar needs. The absence of such segments, or highly fragmented, hard to service customers in challenging locations, suggests the lack of a viable market, and the marketer should therefore abandon further planning on that specific product or project. Market segmentation differs slightly between consumer and business markets. Consumer market segments are evaluated using four segmentation bases (see Figure P3.1):

Figure P4.1: Consumer Segmentation Bases Source: Keller, Kevin Lane. Strategic Brand Management, 3rd ed. Upper Saddle River, NJ: Pearson Education, 2008, p. 99.

Business (or Industrial) describes customers that are other companies buying products for use in their businesses, and business-to-business (B2B) is the term that describes the transaction of businesses selling to other businesses. B2B marketers also want to understand common characteristics of their business buyers so they can develop specific approaches to each business segment (see Figure P3.2). i

  Part 4: Customers Metrics

Figure P4.2: Business Segmentation Bases Source: Keller, Kevin Lane. Strategic Brand Management, 3rd ed. Upper Saddle River, NJ: Pearson Education, 2008, p. 102.

Targets After identifying segments with common characteristics, marketers identify or target those segments that are the most attractive financially, in terms of size and growth prospects, and that match the company’s core competencies well.

Positioning Positioning is how marketers influence customers’ perceptions of a product or service. With the growth of marketing vehicles such as social media, the Internet, and mobile communications, there are multiple entry points through which to influence target customers, but added complexity as well. Perceptions are not created overnight. They take a combination of direct customer experience with the product, word of mouth, and years of market acceptance and use. The following metrics are reviewed in this part: 22. Net sales contribution 23. Time-drive activity-based costing

Part 4: Customers Metrics  

24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36.

Segment profitability Customer profitability Share of customer Return on customer New customer gains Customer acquisition costs Cost per lead Retention rate Churn rate Consumer franchise Customer equity and customer lifetime value Customer brand value Customer losses

 John A. Davis, Competitive Success—How Branding Adds Value (New York: John Wiley & Sons, 2010), 239.

i

Chapter 22 Net Sales Contribution Measurement Need Part of marketing’s responsibility is to target customer segments, understand their challenges, and develop meaningful solutions that resonate with them, thereby satisfying latent and/or articulated needs. Since each customer segment has different characteristics, addressing their unique needs can be expensive; therefore, marketers must measure the specific sales contribution of each customer segment being targeted.

Solution Net sales contribution calculates the financial sales contribution of an individual segment to the total sales for all segments, expressed as a percentage. The formula for net sales contribution is:

Sni =

Si ∑ St

Where Sni = net sales contribution for segment i Si = sales from segment i ∑St = total sales from all segments The results help reveal whether the investment in attracting each segment fell short, met, or exceeded expectations, which will serve as a guide for planning future sales and marketing strategies.

Impact Measuring net sales contribution helps marketers understand each segment’s contribution to total sales. As a general measure of performance, it serves as a useful starting point for further analysis when marketers wish to clarify the underlying factors of each segment’s contribution, particularly as measured against the marketing plan for the time period under review. Marketers would want to review their business performance versus the plan. Assuming their business performed better than expected, marketers would also review the net sales contributions of each

  Chapter 22: Net Sales Contribution product versus the original plan to determine any variances. If product sales departed significantly from the plan, then the marketer must be able to explain the underlying causes, including a segment by segment review to determine whether the marketing plan needs adjusting.

Chapter 23 Time-Driven Activity-Based Costing Measurement Need Ensuring that targeted customers are profitable is often perceived as a pricing tactic. However, focusing solely on pricing is one-dimensional because it minimizes such add-on features as product enhancements, additional service, and training. Effectively measuring customer profitability includes accounting for the inputs that support customer-related activities. Robert S. Kaplan, a professor at Harvard Business School, has pioneered much of the research about activity-based costing (ABC), as well as the balanced scorecard. ABC is designed to help management measure the indirect costs involved in supporting their customers. Kaplan suggests that some companies have struggled to successfully measure costs using ABC due to implementation challenges (including development costs) and the complexity of their own operations, which were not always adequately captured by ABC. His solution is time-driven activity-based costing (TDABC).

Solutioni TDABC measures two factors: (1) the cost per hour of each department working on customer, product, or service-related activities; and (2) the specific time devoted to the activities themselves. Let’s use enterprise software companies to illustrate TDABC. Enterprise software is usually part of a packaged solution that includes services, such as engineering support, designed to help customers answer questions, particularly in the early stages of implementation. If the engineering support costs $300 per hour and the length of time needed to service customer “A” is 45 minutes, then the cost is $225: TC = Ch × Tu Where TC = total cost Ch = cost per hour Tu = time in units TC = $300 × .75 hour = $225

  Chapter 23: Time-Driven Activity-Based Costing

Impact TDABC helps marketers understand the indirect costs that go toward supporting and communicating the pricing and differentiation strategies they have employed. While the enterprise software example is simplistic, the lesson is powerful and useful in helping marketers understand the true profits resulting from each customer. Kaplan’s approach can help companies reveal previously unknown drivers of poor customer profitability. For example, while a customer’s purchase of your products may be growing, that does not necessarily mean that profits are increasing. The cost to service that customer may have increased as well, perhaps due to the temptation to add product features or services to keep the customer from defecting to a competitor. Yet the additional cost to support those services and features is not captured by a corresponding increase in prices, resulting in reduced profitability. To understand customer profitability, it is important to know all costs, not just those that are fixed. TDABC is a useful approach for identifying the specific indirect costs of each activity related to creating that customer in the first place.  i R. S. Kaplan, “A Balanced Scorecard Approach to Measure Customer Profitability,” Harvard Business School Working Knowledge, August 8, 2005; Robert S. Kaplan and Steven R. Anderson, “Time Driven Activity Based Costing,” Harvard Business Review, November 2004. Retrieved May 1, 2017 from https://hbr.org/2004/11/time-driven-activity-based-costing

Chapter 24 Segment Profitability Measurement Need Customer segmentation describes the process of organizing the market into smaller groups of customers who share common characteristics and/or have similar needs, to which marketing then tailors its solution and communications. Marketers need to pay close attention to the segment’s profitability, not just the top line revenues it generates.

Solution Segment profitabilityi measures whether a customer segment is profitable. Three formulas are used, and each contributes to understanding segment profitability overall:ii 1. Cnm = {Ds × Ss × (Ppu x M)} – Em where: Cnm = net marketing contribution Ds = segment demand Ss = segment share Ppu = price per unit M = percentage margin Em = marketing expense 2. Marketing ROS = Cnm / S × 100% where: Marketing ROS = marketing return on sales S = sales

= 3. ROI where

Cnm × 100% Em

ROI = return on investment We look at the following hypothetical example. KL Bikes is based in Malaysia and manufactures bicycles. We further assume that demand for bicycles across Southeast Asia is three million units per year. KL Bikes has been in this market for twenty years and has developed a strong reputation for reliable and affordable bicycles targeted at

  Chapter 24: Segment Profitability the entry-level bicyclist. It has been able to garner a 25% market share in what is otherwise a fragmented industry. KL Bikes are built of quality parts but have few extra features, thus selling for $50. By contrast, premium bikes with composite materials, sophisticated gear technology, and state-of-the-art shocks sell for as much as $10,000. Bicycle manufacturing is expensive because of the number of parts that are put together by hand. KL Bike’s main facilities are located in Pedang, Malaysia, where wages are lower. Consequently, KL Bike’s costs are slightly more manageable than most competitors’ in the industry, which helps it maintain 15% margins. It focuses its marketing efforts on point-of-purchase displays and promotional giveaways such as seat covers and reflectors. Its total marketing expenses are 10% of sales. These figures are plugged directly into the formulas: Cnm = {Ds × Ss × (Ppu × M)} – Em = {3,000,000 × 25% x (50 × 15%)} – $3,750,000 = $1,875,000 This means that KL Bike’s efforts to target the entry-level bike buyer have a net marketing contribution of $1,875,000. Now, we bring in the other two formulas to fully measure the attractiveness of this segment:

Cnm × 100% S $1,875,000 = ROS × 100% $37,500,000 ROS =

= 5%

Cnm × 100% Em $1,875,000 = ROI × 100% $3,750,000 ROI =

= 50% KL Bike’s ROS is 5% and its ROI is 50%. While these results may be consistent with the bicycle industry overall, KL Bike would have to compare its figures with those of specific competitors in the subsegment of entry-level bicycles to help determine if this is a good performance. Of course, the company will have its own performance expectations and key performance indicators.

Impact  

Impact The decision to target a segment is influenced by: (1) whether the segment has the potential to achieve a specific or desired level of profitability, and (2) whether the company has the capability to deliver on expectations. The first formula, net marketing contribution, helps marketers understand a segment’s profit potential and its general attractiveness as an opportunity. Marketing ROS describes the return on total sales, which is dependent on net marketing contribution. It is an important indicator of the efficiency of the business’s operations. A lower marketing ROS signals either a decrease in pricing or an increase in expenses, and is an indicator of the effectiveness of the sales effort. Finally, marketing ROI measures the total return on the marketing investment, indicating whether the expenditures on marketing are yielding maximum results. Segment profitability can help companies understand how different components of their marketing investments affect profitability, provide a useful guide for the direction of future marketing activities, fine tuning their efforts based on the characteristics of a given segment and corresponding results. Tailoring and tuning to each segment is one of the central challenges in marketing and a key reason why actual marketing outcomes diverge from plans. Marketers must develop their budgets and programs with an eye toward the different programs required to reach each audience before going to market. In business-to-consumer companies, marketers often pretest new products and marketing campaigns in niche markets to gain a better understanding of the potential attractiveness of the offering. Design thinking has become an important methodology for helping companies understand their customers and develop better solutions accordingly. From brainstorming, to thoughtful customer ethnography, to developing new business models, to successively approximating (also known as rapid prototyping or test and probe), and ultimately commercializing the most promising ideas, marketers can use their customer segment insights to more quickly and efficiently build momentum. Data for segment profitability are collected from market research, both primary (conducted or commissioned directly by a company’s marketing management to study the market), and secondary (trade journals that publish annual statistics, general business publications like Financial Times, Business Times, etc.). The net marketing contribution, margin percentages, marketing expenses, and price per unit should be available in the company’s account records for each customer, typically summarized in the income statement.

 i Adapted from R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 145–147. School Working Knowledge, August 8, 2005; R. M. S. Wilson and C. Gilliagan, Strategic Marketing Management: Planning Implementation and Control (Elsevier Butterworth-Heinemann, 2005), 318–320; SAP, Profitability Segment. Retrieved June 11, 2017 from https://help.sap.com/saphelp_46c/helpdata/en/35/26b68eafab52b9e10000009b38f974/content.htm

Chapter 25 Customer Profitability Measurement Need Customer profitabilityi measures whether the resources used (time, financial, effort) yield positive results.

Solution Customer profitability models measure total revenues and total costs for customers during the period of time being measured, helping drive resource allocation decisions for individual customers. Calculating revenues minus costs attributable to each customer is sufficient for determining profitability: Customer profitability = rt – ct Where rt = revenues from the customer during time t ct = costs incurred to acquire and support the customer during time t To illustrate, assume a consumer products company is interested in knowing customer profitability, but not at the individual consumer level, even though the final end user is the mass consumer. Acquiring such detailed knowledge would not be cost effective since the company is structured to deliver large volumes of product to a wide range of intermediaries and locations. Instead, investment is made in marketing programs designed to strengthen relationships with wholesalers and retailers. Wholesaler marketing programs include volume pricing, preferred terms, and rapid inventory replenishment. Retailers marketing programs include slotting allowances, which are fees paid to retailers to ensure product placement on store shelves, and co-op advertising, which is an agreement between manufacturers and retailers to share product advertising and/or promotion costs. Customer profitability in this situation is an aggregated figure, based on the revenues resulting from sales to wholesalers and the costs associated with those transactions, including any fees paid to retailers.

Impact The measurement of customer profitability is an exercise in simple calculation. Of course, one-time customers can skew this approach, since it is likely that the costs to

  Chapter 25: Customer Profitability acquire the customer are higher (versus established customers familiar with the company and its products) relative to the return (measured via increased revenues, profits, or both). Therefore, it may be more useful to review loyal customers whose cost to service and purchase patterns are better known. However, astute marketers know that customers have different values. Don Peppers and Martha Rogers, of Peppers & Rogers Group, are among the leading experts in customer profitability.ii They assert that not all customers are equal, let alone equally profitable, and their one-to-one model describes approaches for enhancing the value of every customer relationship. Most businesses experience the 80/20 rule (80% of the money comes from 20% of the customers), or a close approximation of this. Determining specific profitability per customer is challenging since costs are hard to accurately assign or allocate. Managers must take the time to understand the profile of customers contributing the most profits and develop programs that continue to develop these important relationships. To find the revenue and cost figures, marketers can begin their research as follows: 1. Revenue figures: The finance and accounting departments in most companies will have sales data and transaction records for each product for the specific period of time being reviewed, derived from actual payments received from each customer. This information is summarized in the income statement. 2. Cost figures: Determining costs accurately can be challenging due to different materials costs, labor differences, royalties paid to each supplier, support costs, and different marketing programs for each customer. The accounting department will typically aggregate all costs associated with a specific product, allocating it evenly across various customers, even though each customer may have unique purchase patterns.

 i E. Ofek, “Customer Profitability and Lifetime Value,” Harvard Business School Article, 9-503-019, August 7, 2002; SAS, Five Tips for Improving Customer Profitability from Harvard Business Review. Retrieved June 3, 2017 from https://www.sas.com/hu_hu/insights/articles/marketing/Five-waysto-improve-customer-profitability-from-Harvard-Business-Review.html ii D. Peppers and M. Rogers, “The State of Customer Experience in Retail Banking Don’t Get Left Behind,” (vol. 2, 2011), 9. Retrieved May 30, 2017 from http://www.peppersandrogersgroup.com/pdf/white-papers/wp-finserv-customer-experienceretail.pdf, “Measure the Value of Customer Experience Improvements. Customer Experience Value Analysis Connects Customer Initiatives to Tangible Financial Impact” (2014), 4–6. Retrieved May 30, 2017 from http://www.peppersandrogersgroup.com/pdf/white-papers/wp-tech-measure-thevalue.pdf; Magnus Söderlund and Mats Vilgon, “Customer Satisfaction and Links to Customer Profitability: An Empirical Examination of the Association Between Attitudes and Behavior.” SSE/EFI Working Paper Series in Business Administration No. 1999: 1 (January 1999), 2–3. Retrieved May 8, 2017 from http://swoba.hhs.se/hastba/papers/hastba1999_001.pdf

Chapter 26 Share of Customer Measurement Need Knowing the company’s share of each acquired customer’s total potential business.

Solutioni Share of customer describes sales to a specific customer as a percentage of that customer’s total purchases of that specific product type. Conceptually, it similar to market share. A more informal description is known as “share of the customer’s wallet.” The formula for share of customer is similar to market share:

Si =

Sit ΣM t

Where Si = share of customer i (in percentage terms) Sit = your sales to customer i in time t (in units or dollars) ΣMt = sum of all customer spending in time t (in units or dollars) For example, if a customer has $1 million to spend on a given solution, and a company’s sales to that customer are $100,000, then the company has a 10% share of that customer:

S=

$100,000 $1,000,000

= 10% The athletic footwear industry, for example, uses share of customer as one of the measures for evaluating the purchasing potential of their retail buyers. Buyers from large sporting goods and footwear retailers have budgets comprised of planned purchases and units that have already been ordered. The difference between these two is called “open to buy” dollars, which is the remaining money a buyer has available to spend on footwear products. Footwear sales representatives who know their retail buyers well also know the

  Chapter 26: Share of Customer amount of open to buy dollars that are uncommitted. Successfully persuading retail buyers to allocate most, or all, of their remaining budgets toward purchases of sales representatives footwear products will increase their share of customer.

Impact Share of customer measures share at the individual customer account level in terms of the percentage share of total dollars that the customer has spent with a specific company. It helps marketers assess success at persuading a customer to purchase a larger share of their products over those of competitors. Share of customer is also a valuable measure for determining sales representatives performance since it is an indicator of how successful they are in developing their customer relationships. Share of customer results can be a driver of customer relationship programs designed to improve loyalty, yet they are also an early indicator of product problems if there is a decline in average per customer purchases over time or if the customer increases purchases of the competitor’s products. Finally, share of customer assists senior management in understanding how effective and successful their field-based people are in developing their customer relationships. Share of customer information is likely to be kept in the reports of those who work closest with customers—field sales and marketing. Managers in these functions have deep customer knowledge and direct account responsibility, which is often a combination of quantitative data and qualitative insights about the unique profiles of each customer. Top performing sales people are quite familiar with the resources and spending patterns of their customers. However, this information is rarely stored in formal accounting or financial reports since these reports are designed to review performance in aggregate and not at the individual customer level. Furthermore, the information sales people have about their customer accounts includes subjective insights, based on their personal experiences and observations from direct interactions. Most of this information is not useful for formal accounting and financial tracking purposes, yet it is vital to a sales person’s understanding of individual customer accounts.

 i Investopedia, Share of Wallet-SOW. Retrieved May 12, 2017 from http://www.investopedia.com/terms/s/share-of-wallet.asp; BoostCompanies, Share of Customer– –Why It Matters More Than Market Share. Retrieved May 12, 2017 from https://boostcompanies.com/share-of-customer/ “Market Segmentation/Share of Wallet Understanding the characteristics of High-Potential Customers.”

Impact  3  A Case Study by Harte-Hanks Research & Analytics. Retrieved from http://www.hartehanksmi.com/content/pdf/Share%20of%20Wallet%20Case%20Study.pdf

Chapter 27 Return on CustomerSM Measurement Need Just as managers seek to understand how much profit will result from each investment within a specified period of time, marketers must understand the added value derived from their customer investments. A sizable investment in time, money, and resources is usually necessary to gather enough useful details about customers to ensure that the ensuing marketing programs are properly designed and directed to the most appropriate audience. To complete the analysis, marketers must evaluate the potential return on these customer investments. Calculating Return on CustomerSM (ROCSM) enables marketers to more confidently demonstrate that their customer investments are paying off.

Solution According to Don Peppers and Martha Rogers of Peppers and Rogers Group, a leading consulting firm focused on improving business performance through a customer-centric focus, ROCSM is another way of measuring shareholder value. The ROCSM formula is:

ROC SM = Where

πi + ∆CEi CEi − 1

πi = cash flow from customers during period i ∆CEi = change in customer equity during period i CEi –1 = customer equity at beginning of period i Peppers and Rogers illustrate this with two useful examples. The first example (see Table 27.1) shows a steady customer response rate over time to a marketing program.

  Chapter 27: Return on CustomerSM Table 27.1: Steady Customer Response Rate Year 

Year 

Year 

Year 

Total prospects ,,

,,

,,

,,

Response rate

%

%

%

%

Cost per campaign

$,,

$,,

$,,

$,,

Cash flow per campaign

$,,

$,,

$,,

$,,

Profit per campaign

$ ,

$ ,

$ ,

$ ,

Profit per year ( campaigns)

$,,

$,,

$,,

$,,

Year-end customer equity

$,,

$,,

$,,

$,,

Change in customer equity

—

—

—

—

Total value created

$,,

$,,

$,,

$,,

Return on customer

—

%

%

%

The second example (see Table 27.2) assumes a declining response rate over time. A number of factors can contribute to a decreasing response rate including consumer weariness from repeated messages or uninspiring offers. As Pepper and Rogers argue, companies risk destroying customer equity, even as they appear to be making a profit.

Impact  

Table 27.2: A Declining Response Rate over Time Year 

Year 

Year 

Year 

Total prospects

,,

,,

,,

,,

Response rate

%

.%

.%

.%

Cost per campaign

$,,

$,,

$,,

$,,

Cash flow per campaign

$,,

$,,

$,,

$,,

Profit per campaign

$ ,

$ ,

$ ,

$

Profit per year ( campaigns)

$,,

$,,

$ ,

$ ,

Year-end customer equity

$,,

$,,

$,,

$,,

Change in — customer equity

$(,,)

$(,,)

$(,,)

Total value created

$,,

$( ,)

$( ,)

$(,,)

Return on customer

—

(.%)

(.%)

(.%)

,

Impact The objectives of marketing programs and campaigns must be clearly enumerated from multiple perspectives. Depending on the business need, a marketer may be tempted to boost short-term revenues using promotional offers. This may improve sales (and perhaps profits), but the cost may be the loss of loyal customers, the destruction of customer equity, or both. The implications of declining customer equity are the marketer’s responsibility so marketing managers should plan alternative marketing communication scenarios before selecting and launching them. A promotional campaign with an attractive price offer may increase sales, but it may also dilute any brand premium.

  Chapter 27: Return on CustomerSM

Reference Peppers, D., and M. Rogers. 2005. “An Open Letter to Wall Street.” In Return on Customer: Creating Maximum Value from Your Scarcest Resource, 16–18. New York: Doubleday. Note: Return on Customer and ROC are registered service marks of Peppers and Rogers Group, a division of Carlson Marketing Group, Inc. Readers who are interested in a more comprehensive treatment of ROCSM are encouraged to review Peppers and Rogers book as footnoted above. Furthermore, their website, www.peppersandrogers.com, provides additional insight into their consulting and research work.

Chapter 28 New Customer Gains Measurement Need The need is to evaluate the success of new customer acquisition efforts. Chapter 13 on market penetration introduced the Ansoff Matrix,i which describes strategic growth choices. It is shown again below with market development and diversification highlighted, since both depend on new customer acquisition through geographic expansion and/or the addition of new customer segments. With respect to diversification, growth also comes from new products (see Figure 28.1).

Figure 28.1: Product/market matrix.

Solution New customer gain measures the number of new, unique customers acquired over a specific period of time. The measure is:

  Chapter 28: New Customer Gains New customer gain = Cet – Cbt Where Cet = number of customers at end of time period t Cbt = number of customers at beginning of time period t New customer gain provides an indication of the market’s acceptance of new products. The findings will help determine whether new strategies are needed to increase market share. Professional sports provide an interesting example on new customer gain. Most of the professional leagues around the world have programs designed to attract new fans. The National Football League (NFL) is the governing body for professional football in the United States. The NFL has thirty-two teams, and each team develops its team and market appeal based on the needs of the city in which it is located. Most teams have a variety of mechanisms to attract new fans, including different pricing programs. The different pricing programs include: – Single-game tickets (purchased for specific games, often on the game-day itself). – Season tickets (tickets paid-in-full for every home game prior to the commencement of the season). – Personal seat licenses (PSLs—a one-time purchase of a specific seat and its associated rights); PSLs theoretically allow a fan to own a specific seat forever. Clubs still charge a fan for the annual season tickets as well, but the PSL guarantees that the fan will have the same seat every year and luxury boxes/suites (larger rooms that accommodate several people and include such amenities as televisions, personalized food service, and spacious and comfortable seats. . . .). The objective of an NFL franchise (like any business, for that matter) is to maximize revenue and attract as many new fans as possible.

Impact Measuring new customer gain should compel marketers to investigate the sources of the gain to better understand how to capture additional gains in the future. Did the gains result from new marketing programs? If so, which programs yielded the greatest return? Customers may switch from one product to another in the same company. Some companies may consider this as customer gain for one product, but many others ignore such customer movements. Therefore, marketers must be clear in explaining what measuring new customer gains reveals. Marketers must also compare the actual customer acquisition costs to the additional revenues and profits generated. While start-up companies and new product launches regularly incur higher costs than revenues until they have developed their customer base and resulting revenue

Impact  

stream, it would be folly to keep spending more on new customer acquisition than business gains in new revenue for a sustained period of time. Data for new customer gains will be captured in sales reports summarizing “actuals,” as well as more detailed financial reporting.  i H. I. Ansoff, “Strategies for Diversification,” Harvard Business Review 35, no. 2 (September– October 1957)

Chapter 29 Customer Acquisition Costs Measurement Need Marketers need to determine the cost of reaching, attracting, and acquiring the customers they are targeting.

Solution Customer acquisition costs are the costs incurred to acquire new customers, calculated by dividing total acquisition expenses by total new customers. However, this simpler approach leaves out key details about the figures that determine an acquisition expense. Additional measures help clarify these costs. One method multiplies the number of times or frequency a marketing vehicle is used to acquire one customer by the cost of using that vehicle. The formula for customer acquisition costs in this case is: Cac = M × C Where Cac = customer acquisition costs M = number of mailers needed to acquire one customer C = cost to send each mailer Another method calculates it by dividing the cost of each marketing vehicle by the conversion rate it generates, as shown by this formula:

C Cr Where Cac =

Cr = conversion rate* *See Chapter 53 on the response rate and Chapter 54 on the conversion rate.

To illustrate, we assume a marketer wants to calculate the cost of acquiring customers through a traditional direct marketing campaign. We will examine both random and acquired-list mailings.

  Chapter 29: Customer Acquisition Costs Random mailing The cost of mailers is $0.35 each, and the average conversion rate is 1%, meaning one person purchases for every 100 mailers sent. The cost of acquiring each customer using a random mailing is: First formula: 100 × .35 = $35 Second formula:

$0.35 = $35 .01

Depending on the industry as well as the average order size per customer, $35 to acquire a customer may be perfectly reasonable, too low, or too high. Marketers will need to research their market and competitors to develop their own expectations.

Acquired-list mailing There are more effective ways to acquire customers than a random mailing list. For example, assume that using a list of qualified prospects will yield a probable conversion rate of 3% (three times more effective than a random mailing). This means that for every 100 mailers sent, three people will purchase. A marketer would likely decide to rent a list from a reputable list broker knowing that the names on the list have a higher likelihood of purchasing the company’s products. List brokers are in their business to make money and they expend a fair amount of effort to develop their lists through research, so they generally charge a fee. In this example, assume the broker charges $0.25 per name. The marketer can now compare the random mailing to the qualified list mailing and decide which is better. The cost of acquiring a customer using an acquired list is:

$0.60 = $20 .01 The $0.60 is the result of the cost of each mailer, $0.35, plus the cost of acquiring each name, $0.25, divided by the conversion rate expected. The upfront cost of sending out mailers is clearly more expensive when a list is rented—71% more in this example. But the overall cost of acquiring customers is reduced substantially and the company is reaching an audience more likely to respond favorably to the company’s offer.

Impact  

Impact Customer acquisition costs will vary by industry. Using the formula successfully means knowing more about the characteristics of the market being researched. For example, marketing research may reveal that sending mailers to prospective customers in the UK to promote a new product will yield one new customer for every twenty-five mailers. However, when expanding to another country, it turns out that 100 mailers are needed to acquire one customer. Marketers then have to ask a few simple questions: – Is sending 100 mailers reasonable, given the four-fold increase in costs? – What is the break-even point? – Is that new market attractive over the long term? – Is the longer-term market potential large enough to warrant the increased costs? Knowing customer acquisition costs helps determine the best way to allocate marketing program resources. Clarifying the overall goal of the proposed marketing efforts is the first step. If the goal is to raise awareness overall before refining the marketing efforts to a particular segment, then marketers must factor in these awareness-building costs since they will directly affect the receptivity to the subsequent direct marketing program. A market that has a high level of awareness will require less ongoing customer education. Conversely, if a direct marketing program is implemented in the absence of developing market awareness, then the conversion rate is likely to be much lower. Also, the costs for the marketing vehicle (the same approach described in this chapter can be used with other media) depend on the number of mailers the marketer sends and whether any additional literature is included since that increases the mailing costs. If a marketer does not know the response rates for their particular products or industry, then they must find an adjacent industry and compare their assumptions accordingly. If there are no comparable metrics, then conservatively assume rates that are incrementally better for rented lists than a purely random mailing. Not all customer acquisition efforts yield a satisfactory return despite strong market development efforts and targeted direct marketing campaigns. Companies from the dot.com era sometimes displayed a disregard for the value of thoughtfully developed marketing programs, making careless marketing investments. CDnow (acquired many years ago by Amazon.com) spent nearly $40 to acquire each new customer. Purchase patterns revealed that these customers bought only $25 of products on average.i A question that inevitably arises is how to determine the number of mailers and where to find informative data. The Direct Marketing Association (DMA) contains links to other DMA sites in many countries around the world, including Singapore, Japan, Thailand, Australia, and much of Europe, as well as North and South America, each with statistics and metrics common to that location. Once marketers have done their homework, they can begin using this formula with the confidence of knowing

  Chapter 29: Customer Acquisition Costs that the ensuing analysis is based on supportable data. Also, list rentals are just that— rentals. Marketers do not own the names in most cases. The name is “owned” once that target customer responds to the mailing. List brokers usually include several “dummy” contacts in their mailings to ensure that renters do not use their list more than once.  i Nick Wreden, Profit Brand—How to Increase the Profitability, Accountability and Sustainability of Brands (Kogan Page, 2005), 46. Retrieved May 11, 2017 from https://books.google.com.sg/books?id=JL94qlBPYVMC&pg=PA46&lpg=PA46&dq=CDNow+spent+ $40+to+acquire+new+customers&source=bl&ots=iYTpQHrhBR&sig=8AsEYlHcRQ5E-S1JS7-kpymfQk&hl=en&sa=X&ved=0ahUKEwiL89jiLDVAhVEtY8KHePgB5AQ6AEIPTAC#v=onepage&q=CDNow%20spent%20%2440%20to%20acquire %20new%20customers&f=false

Chapter 30 Cost Per Lead Measurement Need Marketers need to measure the cost of acquiring customer leads as it helps determine if their customers are profitable.

Solutioni Cost per lead (CPL) measures the cost paid to acquire each lead. A lead can be anything from an e-mail address to a complete customer profile, including name, company, job title, and all corresponding contact information. The CPL will increase as more detailed information is sought. Determining CPL requires knowing the costs underlying the total advertising costs (TAC), represented by the following:

CPL = Where

TAC TLG

CPL = cost per lead TAC = total advertising costs TLG = total leads generated TAC is comprised of direct advertising costs (DAC) and indirect advertising costs IAC) and is easily calculated: TAC = DAC + IAC Where DAC = direct advertising costs IAC = indirect advertising costs Marketers will appreciate that we do not yet have all of the required information, since both DAC and IAC are aggregates of other fees: DAC = AAF + DC + AF IAC = AO Where

  Chapter 30: Cost Per Lead AAF = all advertisement fees (placement costs, based on insertion frequency, ad size, and related specs) DC = design/development costs (fees incurred to create the campaign) AF = agency fees (salaries and nonwage expenses associated with work on the specific campaign) AO = administrative overhead (hourly wages × # of hours) To illustrate, let’s look at a timeshare purchase.ii Timeshares are joint ownership of a property. Owners use the property according to an agreed-upon schedule. Timeshare properties are located all over the world and are a particularly popular form of vacation home ownership since costs are shared, plus owners can trade their schedules with owners of other timeshares in different locations. In this example, an Australian timeshare company owns two condominiums, each with a market value of $100,000. The company wants to sell each condominium to twelve different owners (each owner would have the right to occupy their unit for one month). Twenty-four total buyers paying $8,333 each are needed. The marketing department develops two different campaigns. The first campaign is a more personalized, targeted marketing campaign aimed at a focused number of high quality leads. The second campaign is a broader program, designed to attract potential buyers to a seminar in which they hear a sales presentation that hopefully convinces them to buy. Both campaigns incur a $60 administrative cost to service each lead. Campaign 2 acquired 200 qualified leads from a third party firm specializing in providing high quality customer lists. CPL is $35. TLC is $7,000 (DAC). Twelve purchases resulted from this effort, a 6% conversion rate: – The firm’s timeshare marketing department calculated that 8 hours were used to create, develop, and track this campaign at $75 per hour. This equals $600 total AO. – TAC = $600 (IAC) + $7,000 (DAC) = $7,600 – CPL = $7,600 ÷ 200 = $38 At this point, our revised cost per lead includes the campaign costs plus total add costs. While we now have a clearer picture of the CPL, the analysis is more useful if we determine the return on investment (ROI). Administrative costs and the cost per buying customer must be included to calculate ROI: – Administrative cost = $12,000 (200 leads × $60 administrative CPL) – Cost per buying customer = ($7,600 + $12,000) ÷ 12 = $1,633 – ROI = ($8,333/$1,633) – 1 = 4.10 = 410%

Impact  

The marketer now conducts a similar analysis to evaluate Campaign 2: Campaign 2 contracted with an online ad agency for 2,000 clicks at $3 cost per click: – It took 20 hours for a staff member to set up and monitor the campaign at a cost of $60 per hour – The web-site and email design cost $1,500 to develop – Campaign 2 generated 100 leads and ten purchases (10% conversion) TAC = $1,200 set up costs (IAC) + ($1,500 web + $6,000 ad costs) (DAC) = $8,700 CPL= $8,700/100 leads = $87/lead Administrative costs = $60 × 100 = $6,000 Cost per buying customer = ($8,700 + $6,000) ÷ 10 = $1,470 ROI = ($8,333/$1,470) – 1 = 4.67 = 467%

Impact Attracting customers is one of the responsibilities of marketers. While mass market advertising offers the possibility of an extensive reach (see Chapter 49), its primary purpose is to create awareness. Alternatively, targeted marketing (also known as oneto-one marketing) is for more personalized communication since specific messages can be tailored to different customer segments. Marketers use lists comprised of their target customers, which can be acquired from third party direct marketing firms. Each name on the list is known as a lead. Acquiring customer lists, and each lead on them, is expensive due to the time, money, and people resources utilized in acquiring the information. CPL tells marketers the approximate costs of each lead. To improve accuracy, a marketer must include direct and indirect costs, and ROI should be calculated to determine whether the campaign yields positive results. The CPL in Campaign 2 was more than double that of Campaign 1. Had our marketer stopped the analysis at this point, she might have assumed Campaign 1 was more financially attractive since it created twelve buyers at a lower CPL. Our marketer may also be interested in the absolute quality of the leads generated. Campaign 1, therefore, offered better quality leads even though there were fewer leads overall. If the goal was to generate buyers, then Campaign 1 did this better than Campaign 2 and, therefore, the marketer may choose this for future campaigns even though it yields a lower ROI. However, the ROI analysis reveals that Campaign 2 had a higher return, even though the total number of actual buyers was lower, the CPL was higher, as was the TAC. Campaign 2 was also $163 cheaper per buying customer and 13.9% more efficient than Campaign 1 (467% ROI versus 410% ROI–57% difference divided by 410%). If the goal was to generate a higher ROI, then Campaign 2 would be the choice for

  Chapter 30: Cost Per Lead future campaigns. The final evaluation will be based on the goals outlined at the beginning of these campaigns. As with Chapter 29, data for CPL analysis can be found at Direct Marketing Association websites of countries targeted for the campaign.  Klipfolio, Cost Per Lead—Measure the Cost Effectiveness of Marketing Campaigns. Retrieved May 2, 2017 from https://www.klipfolio.com/resources/kpi-examples/digital-marketing/cost-per-lead ii ARDA-American Resort Development Association, Timeshare Datashare. Retrieved June 12, 2017 from http://www.arda.org/aif-foundation/research/timesharedatashare/overview.aspx i

Chapter 31 Retention Rate Measurement Need Marketing must not only attract customers so that initial sales are created, but retain customers over time since doing so is usually less expensive financially than new customer prospecting.i Therefore, knowing customer retention (CR) rates is important.

Solutionii The retention rate measures the percentage of a company’s customers it is able to retain over a specified time period. The formula for retention rate is:

Retention rate = Where

Ca Cat

Ca = number of active customers at end of time period Cat = number of active customers at start of time period t

Impact Retained customers are usually less expensive to maintain since marketing has to invest less in marketing education efforts. The marketing effort does shift to a different type of communication, typically one-to-one, relationship-driven marketing, which has its own costs. Losing a customer is expensive due to lost revenues plus the costs incurred to attract the customer in the first place. Additionally, loyalty is viewed as evidence that customers favor one company over another and is a reason to deepen customer relationships and even increase share of wallet. Finally, loyal customers usually require less investment to maintain the relationship than it costs to develop the customer at the outset. Once customers are educated about a company and its products, the company does not need to expend as much effort to explain itself as it did at the “courtship” stage. Therefore, marketers view high CR rates as a desirable objective. Retaining customers must be profitable since loyalty, by itself, may not be financially attractive without a thoughtful application of the marketing mix.

  Chapter 31: Retention Rate Werner Reinartz and V. Kumar argue that customer loyalty and profitability must be managed concurrently to ensure maximum positive results. Even then, profitability, should it result, may vary dramatically among customers. Furthermore, customers that were both profitable and loyal in the past may not be so in the future.iii The takeaway is clear: while a high retention rate is an important goal, it is not cause for celebration unless it also results in a profitable relationship. Note: An alternative approach to measuring retention rate is described by Roger J. Best, Emeritus Professor of Marketing from the University of Oregon. He uses a simple formula:

CR =1 − Where

1 × 100 N

CR = customer retention N = period of time (usually # of years) For example, if the average lifespan of a customer is ten years, then the expected retention rate is 90%:

1 × 100 10 = 1 – .10 × 100

CR =− 1

= .90 × 100 = 90% CR rates are subject to innumerable influences. Even if the customer has demonstrated past loyalty, there is still no guarantee that the customer will continue a similar relationship into the future. Particularly in today’s digital age where reputations and experiences are quickly escalated on social media, customers can shift from loyalist to antagonist on a moment’s notice. As with any business, clever competitors will always try to lure away customers, so a concerted effort with ongoing programs and activities, regularly reviewed for progress against plan, is required to achieve CR expectations. The retention rate data can be derived from retention surveys of current and former customers, which track customer defection. Alternatively, marketers may be able to find this information in their customer account summaries, which are usually found in the accounting or financial reports that summarize business activities for a given period of time. Sales management should have detailed customer account information in its reports.

Impact    i NG*Data, What Is Customer Retention? Retrieved May 30, 2017 from https://www.ngdata.com/what-is-customer-retention ii Amanda DiSilvestro, How to Calculate and Improve Customer Retention Rate. Salesforce.com. Retrieved May 30, 2017 from https://www.salesforce.com/hub/service/customer-retention-rate/ iii Werner Reinartz and V. Kumar, “The Mismanagement of Customer Loyalty,” Harvard Business Review (July 2002): 2–5.

Chapter 32 Churn Rate Measurement Need Part of marketing’s challenge is knowing how many customers they lose versus how many are retained since not all customers are loyal, profitable, or desirable.

Solutioni Churn measures customer attrition expressed as percentage of customers a business loses over a specific period of time. Churn is calculated as follows:

Churn = Where

Cbt − Cet Cat

Cbt = customers at beginning of time period t Cet = customers at end of time period t Cat = customers at beginning of time period t Churn affects companies everywhere, and rates vary, often dramatically, by sector. Mobile phone carriers in Europe have churn rates between 20%–38%. Wireless carriers in the United States could improve earnings by 9.9% if they reduced churn.ii A study in Asia showed that six countries in the region anticipated mobile phone churn rates of 24%, representing 169 million consumers who were forecasted to change carriers within eighteen months.iii

Impact It is important that marketers learn why customers left so they can reduce churn in the future through revised marketing communication programs, improved product offerings, better pricing, and more effective customer targeting. Most businesses regularly face customer churn challenges, trying to develop strategies and programs that will minimize it. It is necessary to address churn since losing a customer is often expensive in time (amount of time invested to attract and retain a customer), resources (manpower deployed to service customers), and money (actual outlay of cash spent on customer development programs). Churn rates also impact customer lifetime value analysis (see Metric 35) since a higher churn rate indicates customers are not

  Chapter 32: Churn Rate staying long with the company. This leads to higher costs since more money has to be invested to educate and attract new customers. Churn is somewhat similar to retention (Metric 31), but there are subtle differences. Churn is calculated with former/lost customers only, while retention can be determined with former or existing customers. Churn research focuses on why they left, whereas retention focuses on how to maintain and increase loyalty. Furthermore, churn is subject to interpretation, blurring the differences even more with retention. Returning to the telecommunications example, different providers may use slightly different methodologies in calculating churn. When a customer moves from one geography to another, and consequently changes telephone numbers, yet remains with the same provider, the provider might count this move as churn. This phenomenon occurs regularly in the United States. Alternatively, when a customer’s service contract expires and that same customer selects a different plan with the same provider, this may also be counted as churn. In these two instances, the customer has remained with the provider, but individual circumstances have created the need to change their previous plan. Marketers must be clear on their definition of churn, since it affects the kind of marketing programs designed to attract and retain customers in the future. A conservative definition of churn suggests that it pertains only to customers the company has lost to a competitor as opposed to another division or product within the same firm. This definition would lead the curious marketer to explore why the customer switched to a competitor, whether it is isolated or an indication of a larger, unsettling trend and, consequently, how to improve the situation for remaining and new customers. However, large companies (such as telecommunications) often “lose” customers to another division. Corporate marketers, with broad strategic responsibilities for marketing across the entire company, may view this as retention, since the customer remains with the company overall. But divisional and/or product line marketers may count this as churn and, therefore, concern themselves with how to reduce it in the future. It stands to reason that whether a customer is lost to a direct competitor or to another division within the same firm, marketers can use this as an opportunity to improve their offerings and their running of the business. Churn numbers typically come from one of two sources: reactive, or postcustomer departure, reports; and proactive, or precustomer departure, reports. Reactive reports are generated by any of several key areas in a company, depending on its size, complexity, and customer account practices. Sales, customer support, customer service, telemarketing, and even customer account managers in accounting may track this information. As it implies, reactive reports capture customer departures after a customer has contacted the company and indicated they are leaving. It is a more straightforward metric, although it can also be frustrating since it is usually much harder to convince an already lost customer to return. Proactive efforts attempt to predict which

Impact  

customers are likely to leave, allowing marketers the opportunity to target them with new programs and incentives designed to retain them and, thereby, reduce churn.  i Brian Rogers, How to Calculate Customer Churn and Revenue Churn. Evergage. Retrieved May 9, 2017 from http://www.evergage.com/blog/how-calculate-customer-churn-and-revenue-churn/; Churn Rate, Churn Rate 101. Retrieved May 9, 2017 from http://www.churn-rate.com/ ii Aurelie Lemmens, Tilburg School of Economic and Management; Gupta Sunil, Harvard Business School. Managing Churn to Maximize Profits, September 2013. Retrieved May 9, 2017 from http://www.hbs.edu/faculty/Publication%20Files/14-020_3553a2f4-8c7b-44e6-9711f75dd56f624e.pdf iii Dentsu Media, To Stay or Go? Understanding Customer Churn Among Mobile Carriers in Asia, 2014. Retrieved May 9, 2017 from http://www.dentsumedia-network.com/dmwp/wpcontent/uploads/2015/02/Dentsu_media_MoCTS2014.pdf

Chapter 33 Consumer Franchise Measurement Need Marketers need to know which customers have the highest value to determine how best to deploy marketing resources.

Solutioni Consumer franchise identifies those customers who are regular, core buyers. They have the highest likelihood of continuing to purchase the company’s products. Additionally, less committed buyers also contribute to revenue. The following formula represents total sales derived from a combination of committed and uncommitted buyers: Sales = (P1 × N1) + (P2 × N2) Where P1 = customer probability of buying if committed N1 = number of committed buyers P2 = customer probability of buying if uncommitted N2 = number of uncommitted buyers For example, let’s assume that the hypothetical firm, Milo’s Dog Taxi Service (MDTS), has 100,000 committed customers (dog owners that hire taxis to take their dogs for a car ride) who believe in MDTS’s services. Each year 60% of these customers buy services. MDTS has another 10,000 uncommitted customers who have used their services infrequently or even just once. Since these uncommitted customers purchase non-MDTS services as well, their probability of purchasing just MDTS is 20%: Sales = (60% × 100,000) + (20% × 10,000) Sales = 60,000 + 2,000 Sales = 62,000 A marketer might be tempted to increase the sales from the committed and uncommitted buyers, investing marketing resources to convert the uncommitted buyers into higher probability committed ones. Let’s assume the marketer pursues this and converts 500 buyers:

  Chapter 33: Consumer Franchise Sales = (60% × 100,500) + (20% × 9,950) Sales = 60,300 + 1,990 Sales = 62,290 Clearly, there is an increase in committed consumer franchise buyers. However, if the marketer chooses to try to convert additional uncommitted buyers, a disproportionate share of the marketing budget would be spent on educating these uncommitted buyers. The precise conversion rate is unknown, but it is likely only some of the uncommitted buyers would convert and, of those, not all would become committed consumer franchise buyers. Therefore, the marketer might want to focus their efforts on the consumer franchise, since committed buyers have a higher probability of buying and have demonstrated their loyalty and commitment already. Let’s now assume the marketer is able to increase the probability of purchase from the committed buyers to 65%, with the uncommitted buyer efforts remaining the same: Sales = (65% × 100,000) + (20% × 10,000) Sales = 65,000 + 2,000

Sales = 67,000

Another option is to increase the number of committed buyers from competitors by focusing on customers whose characteristics are similar to those of the marketer’s committed buyers, so a portion of the marketing budget is allocated to these new customers, attracting 500 more as a result: Sales = (60% × 100,500) + (20% × 10,000) Sales = 60,300 + 2,000 Sales = 62,300 The marketer has attracted 500 new committed buyers, with the overall sales result still better than the first option of allocating marketing resources toward converting uncommitted buyers.

Impact Assuming the marketer has concluded that uncommitted buyers are not the focus of their marketing efforts, there are three ways to improve sales: 1. Increase the probability of buying from committed buyers; 2. Increase the number of committed buyers; 3. Or a combination of both.

Impact  

To increase the probability of buying from committed buyers, promotions may be most effective. The marketer knows that this buyer will purchase at least 60% of the time, so the marketing challenge is to increase this by increasing usage. Promotions are an effective method for doing so. However, the disadvantage is that promotion research shows that business usage spikes upward for the duration of the promotion but does not permanently increase the probability of converting buyers from uncommitted to committed. To sustain the desired higher probability of purchase levels, marketers will have to engage in more sophisticated marketing efforts that offer higher value, such as experiential marketing and/or on advertising, product and service enhancements, and similar value-added activities. This more sophisticated approach has the distinct advantage of attracting more committed buyers and eliminates the influence of discounts, arguably a more responsible long-term approach since it yields more committed buyers who, when purchasing, pay full price. Otherwise, the committed buyers will become trained to expect discounts and may wait to purchase when the next discount is offered. This unfortunate result has the effect of increasing the probability of purchase and, over the long term, reducing profitability. The final option, improving the probability of purchase and increasing the number of committed buyers, may sound appealing, but marketers must be aware of the potential pitfalls. First, the marketing expense will be higher since the marketer is allocating dollars both to increase the purchase probability through developing promotions and increase committed buyers through increased advertising and/or experiential marketing activities. Second, the same risk exists when the marketer tries to increase the probability of purchase through promotions––long-term margins may suffer. In effect, the marketer may actually end up with a larger pool of committed buyers, all of whom now expect discounts, making the cost of servicing each customer higher than before. Data for consumer franchise resides in the company’s sales reports, marketing communications performance summaries, and end of period financial report.  i C. Gilligan and R. M. S. Wilson, Strategic Marketing Management: Planning, Implementation & Control (London: Routledge, 2005), 527; Massimiliano Bonacchi, Kalin Kolev, and Baruch Lev, Customer Franchise––A Hidden Yet Crucial Asset, April 2013. Retrieved. May 28, 2017 from http://people.stern.nyu.edu/blev/intangibles/Customer%20Franchise%20%20A%20Hidden,%20Yet%20Crucial%20Asset.pdf

Chapter 34 Customer Equity and Customer Lifetime Value Measurement Need Marketing needs to know how much their customers are worth to their business.

Solution Measuring customer equity, which is the sum of the present values of the company’s future customer cash flows, is an invaluable marketing tool. Two methods are described here, measuring different (but related) factors in customer equity and customer lifetime value (CLTV). Given that loyal customers have already “voted” by purchasing a company’s products, the marketing opportunity lies in increasing crossselling (selling similarly priced complements) and up-selling (selling a more expensive solution or complement).i The following formula assumes a constant customer defection rate, a constant net margin, and a discount rate: CLTV= m / (k + d) Where m = constant net margin (profits – retention costs) k = discount rate d = constant defection rate This approach calculates the basic financial value of the customer. Each customer represents potential cross-selling and up-selling value, which is captured by factoring in a constant growth rate g: CLTV= m / (k + d – g) The growth rate is subtracted because it is unlikely that a customer’s long-term growth rate will remain constant. The rate of increasing cross or up-selling purchases will diminish over time as customer’s added satisfaction and enjoyment from each additional purchase is reduced. A related approach to CLTV estimates the financial value (typically, profits) of a customer’s long-term relationship with a company. While it, too, measures how much a customer is a worthwhile remaining loyal purchaser of a company’s products, it also factors a value for customer referrals, adding further value to the relationship

  Chapter 34: Customer Equity and Customer Lifetime Value developed with the referring customer. Retention remains a primary objective. However, this approach does not factor in cross or up-selling opportunities, focusing instead on new customer referrals. Example two illustrates this method.ii The marketing manager needs to be acquainted with the key data associated with their loyal customers, derived from: M = average amount of money spent per purchase; C = average costs to service each purchase; P = number of purchases per year; Y = number of years managers expect to keep this customer; A = new-customer acquisition cost; N = number of new customers referred by original customer; F = customer adjustment factor for the period of time being evaluated. F is the customer adjustment factor and is described as follows: F captures changes in a customer’s behavior over time. If you estimate that the customer will increase the money spent per visit over time (because you estimate you will increase their loyalty), then put in a higher number—say, 1.4. If you estimate the customer will decrease their spending over time, put in a lower number—say, 9. This is obviously a subjective estimate.iii Therefore, 1 is considered a steady state and no correction is needed. The subjective nature of the correction factor reveals the importance of including both qualitative and quantitative measures in the customer analysis. Next, the terms are grouped into individual equations: M – C = the average gross profit generated by the customer per visit P × Y = total number of visits over the customer's lifetime A × N = the amount of money saved by the customer's referral The lifetime value of the customers can now be determined using the formula: CLTV = [(M – C) × (P × Y) – A + (A × N)] × F To illustrate, let’s assume the management of a hotel chain wishes to determine the lifetime value of their average customer. Management reviews the guest statistics for its hotels:

Impact  

M = average amount of money spent per purchase (guest)

= $220

C = average costs to service each purchase (guest)

= $70

P = number of purchases/visits per year

=3

Y = number of years managers expect to keep this customer

= 20

A = new customer acquisition cost

= $25

N = number of new customers referred by original customer = 5 F = customer adjustment factor

= 1.3

CLTV of the average guest equals $11,830, as shown below: {($220–$70) × (3 × 20) – $25 + (25 × 5)} × 1.3 = $11,830 In this illustration, hotel management has determined that its loyal customers are likely to spend more in the future with each visit, hence the higher customer adjustment factor.

Impact Since it is usually more expensive to recruit new customers than retain existing ones, marketing’s focus should be on growing customer equity and lifetime value, especially since customer-centric measures are a key determinant of marketing effectiveness. CLTV is influenced by the data used and how the results are interpreted, as with any data analytics. For example, determining the average spending per customer is dependent on whether managers are using transactions or customers in their calculation. In retail, if a manager adds together total purchases and divides by the number of transactions, then the value of some customers may be under-represented since their separate multiple purchases would be viewed purely as if they were separate customers. On the other hand, accurately determining actual customer purchases requires a more sophisticated tool that not all retailers may have, such as loyalty cards that can be scanned with each purchase. Furthermore, loyalty cards may not be used consistently by customers, which can skew the analysis. Cost figures are also quite challenging to determine at the individual purchase level. Are managers measuring the cost of the entire operation at the time the customer made his or her purchase? Or are they isolating costs specific to that transaction? If it is the latter, they will find those costs are difficult to determine with any degree of precision. A simplistic way around this is to identify a set of costs known for each operation and the customer-specific transactions, then consistently apply these every time costs are measured. CLTV analysis can be a robust measure, but it is still not perfect. Even with more sophisticated data modeling, managers must understand that customers will not behave according to predictions.

  Chapter 34: Customer Equity and Customer Lifetime Value The important takeaway for marketing is the sizable long-term value a loyal customer represents, which should drive the planning focus to improve customer retention. The process reinforces why businesses should try to develop long-term relationships rather than short term or, worse, one-time purchase gains. The data is found in several areas. For retailers, the average customer-spending information can be found in scanner data simply by adding together total purchases and dividing by the number of customers, or transactions, depending on how sophisticated their point-of-purchase system is. Average costs can be found in the income statement or daily bookkeeping records. The forecast numbers are estimates, based either on historical experience, industry benchmarks, or perhaps even new services, products, or technologies that managers believe influence customers’ buying patterns. The customer-acquisition costs have already been discussed in the previous sections. Accurately finding out the number of new customers a customer refers to the company requires a fair amount of individual customer knowledge and/or a customer relationship management system, or even a basic database designed to track these kinds of activities. The correction factor is a subjective assessment, affected by several factors, including the manager’s experience in the business, competitor performance, and market factors. Given this, managers should be able to estimate a reasonable correction factor.

Reference Lemon, K. N., R. T. Rust, and V. A. Zeithaml. 2004. “Customer-Centered Brand Management.” Harvard Business Review (September). Note: There are more sophisticated treatments for those readers who are interested in exploring this topic further. The endnotes provide information on these: http://www-stat.stanford.edu/~saharon/papers/ltv.pdf http://hbswk.hbs.edu/item.jhtml?id=1436&t=marketing http://executiveeducation.wharton.upenn.edu/globals/documents/metrics.pdf http://www.interactionmetrics.com/customer_equity.htm http://www.businessknowhow.com/manage/client-value.htm

 i D. Reibstein, D. and R. Srivastava, “Metrics for Linking Marketing to Financial Performance.” Working paper submitted to Marketing Science Institute, October 19, 2004, 8–9. ii Allen Weiss, What Are Your Customers Really Worth? January 25, 2005. MarketingProfs. Retrieved May 30, 2017 from http://www.marketingprofs.com/5/weiss7.asp iii Ibid.

Chapter 35 Customer Brand Value Measurement Need Marketers need to determine the approximate value of the average customer to their brand.

Solution CBV = P × BR × SOP × M Where CBV = customer brand value P = penetration (% of the brand’s users vs. overall # of users in the category) BR = buying rate (the average # of units bought per customer during a specified period of time) SOP = share of purchase (i.e., share of customer wallet) M = gross contribution margin To illustrate, an app developer for smart phones and tablets has the following data: P = .12 (12%) BR = 4 (4 apps are purchased per year from a single customer) Share of purchase = .025 (2.5% Gross contribution margin = .6 (60%) CBV = 0.12 × 4 × 0.025 × .06 = 0.0072 i

In short, the customer brand value of the average customer is 0.72%, which means the average customer contributes slightly less than 1% to the total brand value.

Impact Knowing the average customer value to the brand can give guidance on future customer investments in product, marketing communication, or other offerings. By understanding where customers are in their relationship to the brand, companies can

  Chapter 35: Customer Brand Value more effectively target investments in a way that improves the customer’s relationship with the brand and increases their purchases that will have a direct impact on both brand equity and long-term brand value.  Alice M. Tybout and Tim Calkins, eds., Kellogg on Branding (New York: John Wiley & Sons, 2005), 256–257.

i

Chapter 36 Customer Losses Measurement Need For planning and budgeting purposes, marketers need to see how many customers have been lost versus retained, so that future marketing plans can be adjusted to reduce losses.

Solutioni Customer loss refers to the number of customers that stop purchasing a company’s products or services over a given period of time. The simplified formula below uses the same variables as that in the measure New Customer Gains, but the measure now focuses on customer attrition versus gain over the same period of time: Customer loss = Cbt – Cet Where Cbt = number of active customers at beginning of time period t Cet = number of active customers at end of time period t Verizon, a U.S. telecommunications company, introduced an unlimited data plan in early 2017 in response to losses of 398,000 monthly phone customers. The customer losses motivated the unlimited data plan program to stem the damage arising from these steep customer losses.ii

Impact Losing customers is expensive since money and resources have been invested to educate and attract them. Once customers have “voted” in favor of the company’s solutions (by purchasing them), a marketer’s next step is to leverage the initial purchase into a long-term, profitable relationship. Customer loss is an effective tool for assessing the continued value of an existing product to customers as it matures over time. If an existing product is losing customers or revenues, marketers are faced with three choices: (1) invest in new strategies and tactics to improve customer acceptance of the product and increase the product’s profitability as well, (2) stop doing business with unprofitable or low margin customers, or (3) remove the product from the portfolio.

  Chapter 36: Customer Losses The logic of the formula assumes that Cbt is larger than Cet, resulting in a number equal or greater than zero. The reason is simple: if Cet were larger than Cbt, then it would suggest a gain in total customers over the same period of time. Assuming customer losses are larger than customer gains during the time period being measured, marketers can begin analyzing the defections to determine if there are any patterns and their potential causes. If the customer losses occur in only one period and not over several periods, then it may be an anomalous event requiring only minor analysis to ensure the causes are limited. However, if customer losses persist, then it may signal significant problems, including: – A decline in the level of trust customers have in a company’s products – Products that are no longer relevant to the customer’s needs – A decrease in quality – The price-value relationship is no longer attractive – New competitor offerings are better/cheaper/more trustworthy/more innovative – A shift or changing trend in the overall consumer market While marketers do not like to lose customers, it is important to measure the losses and understand the causes to eliminate or at least minimize them in the future. A persistent pattern of customer losses will inevitably negatively impact cash flow unless those customers that remain are extraordinarily profitable (which would suggest the customers lost are acceptable since they were generating losses). Determining the actual causes of customer loss is, of course, easier said than done since the influencing factors can be numerous and quite complex. However, the potential complexity should not deter marketers from undertaking the analysis, since the resulting benefits will include a clearer understanding of the variables that impacted customer loss. Marketers should create a plan for retaining high profit customers and enhancing their value further. However, this can be a difficult analysis to get right since high value customers often have complicated relationships with companies across multiple business areas, from products and services to support and finance. Customers may encounter difficulty in determining high value customers due to other factors that influence the final measure. Customers may switch from one line of product to another, but within the same company. Some managers may consider this as customer loss for one product, while others may see this as a gain for the company, just in a different area. The U.S. auto industry used customer satisfaction scores for years, assuming incorrectly that it was a predictor of happiness with the product and, indirectly, an indicator of product and even financial success. Yet through the mid-1990s, while the customer satisfaction scores remained high, the repurchase rate stayed between 30% and 40%, suggesting a customer loss of 60% to 70%. Interestingly, one can easily imagine the bottom line impact if the auto industry could reduce customer losses to “only” 50% or 55%.iii

Impact    i National Business Research Institute, Customer Loss Review Surveys, N.D. Retrieved May 21, 2017 from https://www.nbrii.com/products/customer-surveys/customer-loss-review-surveys/; Thabiso Mochiko, MTN Dips on Customer Losses, May 4, 2017. Business Day. Retrieved May 21, 2017 from https://www.businesslive.co.za/bd/companies/telecoms-and-technology/2017-05-04-mtn-dipson-customer-losses/ ii Aaron Pressman, Verizon Reveals Huge Customer Losses Before Unlimited Data Plan, April 20, 2017. Retrieved May 21, 2017 from http://fortune.com/2017/04/20/verizon-customer-lossesunlimited/; Chris Mills, Verizon Is Losing Customers Like Crazy Even with Unlimited Data Plans, April 20, 2017. Retrieved May 21, 2017 from http://bgr.com/2017/04/20/verizon-earnings-customerloss-stock-price/ iii F. F. Reichheld, “Learning from Customer Defections,” Harvard Business Review (March–April, 1996): 4–5.

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Part 5: Product/Offering Metrics Products are more than a physical item or tightly defined service. Consumers see products as a promise of quality and a provider of value. The purchase of a product does not end the relationship for the company, it begins the relationship for the consumer. Customers expect the products they purchase to work, and if not, then redress is sought. The product must include warranties, replacement and return policies, customer service, technical support, and an image of assumed quality. Marketers have an obligation to develop and promote products that are reliable, foster goodwill with customers, and advance the company’s reputation and perceived value. Before launching a product, a marketer should evaluate its potential for success. For products that are global, a marketer must factor in overseas support for the product, develop distribution relationships, identify the most attractive markets, and understand the competitive conditions. The relevance of products to the overall marketing effort has taken on new significance in recent years with the burgeoning economies of Southeast Asia. For years, Japan was considered the only Asian country producing products and services that succeeded in Western markets. Toyota, Honda, Nissan, Nintendo, Sony, Mitsubishi, Fujitsu, and Panasonic were the world’s most talked about companies. Additionally, Japanese banks were well represented among the world’s top fifty financial institutions. Korea began emerging in the 1990s, with the growth of Samsung and Hyundai in particular. Now Thailand, Singapore, Vietnam, China, and India have taken center stage. New products from companies in these markets are sold around the world, and Asian companies are increasing in number in global business surveys. Marketers in these countries have observed the success of Western multinationals around the world and are copying as well as developing their own approaches to product development. This

DOI 10.1515/9781501507304-005

  Part 5: Product/Offering Metrics is creating a formidable and stimulating challenge for marketers in Europe and the United States that once dominated the multinational business environment. Marketers throughout the world know that they can market their products almost anywhere and, equally, their competition can come from anywhere as well. Developing smart products and product strategies to compete successfully begins with measuring a product’s potential before launching into new markets. The metrics in this section are: 37. Usage 38. New product purchase rate 39. Marketing cost per unit

Chapter 37 Usage Measurement Need To determine product usage at different prices.

Solutioni Using a framework for assessing the maximum financial benefits a company can produce while also yielding substantial value for the consumer. Roger J. Best, in his book Market-Based Management: Strategies for Growing Customer Value and Profitability, provides an excellent example of usage. The subject assumes a telecommunications company manufacturing a new product that delivers more value to its customers at a lower cost, but can also command a higher price, resulting in improved profits for the company. The value lies in the reduced installation, usage, and maintenance costs for the customer, even with the higher price. The reason? In Figure 37.1 you can see that the overall cost (“Lifecycle Costs,” )to the customer is $125 cheaper, even though the retail price of the product itself is $75 higher. Look at the chart closely. The benchmark comparison describes the current product offering and associated costs: $500 for usage and maintenance, $200 installation, and $300 purchase price. Each of these are paid by the customer. The next bar in the graph shows that the new solution reduces installation, usage and maintenance costs ($500 versus $700 with the current solution), yielding a maximum value of $500, assuming the new product is priced at zero. The final bar in the graph reflects the company’s new product, priced higher for the unit (so the telecommunications manufacturer recaptures economic value), but lower overall when the other costs are included.

Figure 37.1: Lifecycle Costs

  Chapter 37: Usage

Impact By creating a new product with lower costs, but also offering higher value, the marketer is able to command a premium price at a lower overall cost for the customer. Usage analysis helps marketing by visualizing the value associated with different products based on their lifecycle costs. Marketers can use this to analyze new products compared to older ones, or to compare their own product offerings to those of the competition, identifying opportunities, and/or risks in the process. Having a thorough understanding of their customers’ needs relative to their product offerings, and those of the competition, if they are included, is required to determine where the value opportunities exist. As mentioned previously, being customer-centric places a significant expectation on the company to spend more time with customers to understand their needs and challenges so that the findings help the company develop more impactful solutions. This analysis is also useful in matching products to different segments, based on their needs and usage. Some segments may use a product less, but expect the product to last longer as a result. They would opt for the lower-priced product, even if it has higher maintenance costs, since their costs are spread out over time versus up front. Conversely, higher usage segments may prefer the higher up front price in return for lower maintenance costs on the new product. Data for usage is capture in the detailed component costs for the product itself, and the service and resource costs incurred in installation, usage, and maintenance.  i R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 106–107.

Chapter 38 New Product Purchase Rate Measurement Need New product development requires time, money, and people resources, and success is never guaranteed, so being able to estimate the potential for success for a proposed new product is crucial to the final investment decision.

Solution The new product purchase rate formula, also known as a diffusion or penetration model, helps estimate the potential for success of a new product by projecting the possible penetration rate for the new offering. The new product purchase ratei is determined by the following formula: qt = r × q (1 – r)t-1 Where qt = % of total households expected to try product in period t r = rate of penetration of untapped potential q = % of total households expected to eventually try new product t = period of time To illustrate, we can look at an example using San Fransisco, California, where there are 780,971 households according to a 2010 census.ii We will assume the following variables: r = 40%. Meaning 40% of the remaining potential new buyers are penetrated. q = 20%. Meaning 20% of San Francisco households will actually buy the product. t = period of time Let’s input these figures into the formula over successive time periods (five years in this example) to demonstrate the changes in penetration rates: qt = rq (1 – r)1–1 = (0.4)(0.2)(0.60) = 0.080

  Chapter 38: New Product Purchase Rate qt = rq (1 – r)2–1 = (0.4)(0.2)(0.61) = 0.048 qt = rq (1 – r)3–1 = (0.4)(0.2)(0.62) = 0.029 qt = rq (1 – r)4–1 = (0.4)(0.2)(0.63) = 0.017 qt = rq (1 – r)5–1 = (0.4)(0.2)(0.64) = 0.010 This set of equations indicates that the rate of new product penetration for the 20% who will buy the product decreases over a five-year period. From here, sales are determined by simply taking the resulting penetration rate for each period and multiplying it by the total number of San Francisco households, then multiplying by the expected price for the first purchase (each period is essentially “first purchase” expenditures since the purchases reflect first time buyers in each period) per household. Furthermore, we will assume the first-time purchase price for this product is $50. qt = rq (1 – r)1–1 = 0.080 → .08 × 780,971 × $50 = $3,123,884 qt = rq (1 – r)2–1 = 0.048 →.048 × 780,971 × $50 = $1,874,330 qt = rq (1 – r)3–1 = 0.028 → .029 × 780,971 × $50 = $1,132,408 qt = rq (1 – r)4–1 = 0.017 → .017 × 780,971 × $50 = $663,825 qt = rq (1 – r)5–1 = 0.010 → .010 × 780,971 × $50 = $390,486 The data on households is government census data, which is collected at different times in different countries. A quick Internet search provides numerous references to household data from Canada, the United States, Australia, the UK, Japan, and Europe. China’s data is less reliable due to differences in collection techniques, uncertainty over census dates, inconsistent transparency requirements, and comprehensiveness.

Impact Predicting success is not easy and questions do remain. For example, how does one determine r, the rate of penetration of untapped potential? How do marketers determine the percentage of households that are likely to try the product in a certain time period? The answers depend on several factors: – The market in which the company competes. – The ease of determining, reaching and converting customers in the target markets. – Surveys that assess customer purchase intent. – An estimate of the remaining potential customers to be converted.

Impact  

Determining the number of potential customers requires marketers to do more research about the target markets. Predicting product adoption rates is a combination of science and art. The science comprises the data-collection techniques and subsequent analysis. The art is in deciding how much of the result should be believed, given the vagaries of consumer behavior. In other words, just because consumers say they are likely to buy your product does not mean they will behave in that way at the actual time of purchase. Intent does not necessarily lead to action or purchase. The real test will be how consumers actually respond when you introduce your products to the market. For a marketer launching a new product, this is an interesting way to gauge its potential economic lifespan, assuming of course that there are no changes in targetcustomer penetration, audience size, product features, or pricing. These latter caveats are the challenges. Furthermore, determining the potential market for your product out of the total household population and the rate of penetration is somewhat arbitrary. Marketers can mitigate some of this guesswork by gathering industry and competitor statistics for similar products and inferring the potential on their own. Therefore, a marketer’s analysis will be a mixture of observable data and qualitative judgments.  i The formula has its origin in an article by Louis A. Fourt and Joseph N. Woodlock, entitled “Early Prediction of Market Success for New Grocery Products,” Journal of Marketing (October 1960): 31–38. More recent, in-depth research has been conducted by Peter S. Faber, Bruce G. S. Hardie, and Chun Yao Huang in their article, “A Dynamic Changepoint Model for New Product Sales Forecasting,” Marketing Science 23, no. 1 (Winter 2004): 50–65 ii 2010 Bay Area Census. Retrieved May 1, 2017 from http://www.bayareacensus.ca.gov/counties/SanFranciscoCounty.htm Note: The U.S. Census is conducted every ten years, with the next census in 2020. The figures in this illustration are the most current at the time of publication.

Chapter 39 Marketing Cost Per Unit Measurement Need Each unit sold has a marketing cost associated with it that reflects the tactics used to promote the product in the market and knowing that cost is a primary responsibility of marketers who wants to lead their business and deliver results.

Solutioni The marketing cost per unit (MCPU) calculation is simple:

MCPU = Where

Emt Ut

MCPU = marketing cost per unit Emt = total marketing expense in time period t Ut = total units sold in time period t In 2016 Lenovo shipped 55.5 million PCs globally. The total market size was estimated at 260 million units, thereby giving Lenovo a 21.3% market share.ii Lenovo said it would spend $726 million on marketing in 2016.2 Using these figures, we can calculate Lenovo’s MCPU as follows: $726,000,000 $55,500,000

= $13.08 Lenovo spent $13.08 per unit to market its PCs.

Impact The MCPU should decline as a product matures. As more consumers buy a company’s product, distribution expands, word of mouth builds up the reputation, and the product becomes more familiar as a consequence. However, if the MCPU increases, then that may be a warning signal that consumers are losing interest or competitors are offering more attractive products at better prices. Marketers need to investigate the increasing costs per unit to determine the appropriate response. In Lenovo’s situation

  Chapter 39: Marketing Cost Per Unit the global PC market has been in decline for several years. In 2010 total global PC shipments were 351 million units and Lenovo shipped 34 million units for a market share of 9.7%. Its MCPU in 2010 was $2.94. While its market share has increased substantially, the overall market is declining, hence the increase in MCPU to sell PCs. Sources for MCPU data will be tracked in regular sales reports and also aggregated in period financial statements (i.e., quarterly, annually, etc.).  i Pat LaPointe, The Most Effective Metrics for a Marketing Dashboard (in Some Not-So-Obvious Forms), January 3, 2006. MarketingProfs. Retrieved May 4, 2017 from http://www.marketingprofs.com/6/lapointe2.asp ii 2016/17 Annual Report Lenovo Group Limited, p. 34. Retrieved July 15, 2017 from http://static.lenovo.com/ww/lenovo/pdf/report/E_099220170605a.pdf

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Part 6: Price Metrics A product’s image is influenced by price. High prices convey high quality and the corollary is true for low prices and low quality. At a minimum, price is a mechanism for marketers and their companies to recover their costs. More strategically, price is a signal to the market about the position and quality of the offering. The most important consideration is how price aligns with the company’s strategic objectives and contributes positively to the company’s reputation. Is the company’s strategy based on rapid sales growth? Then a low price, economy or penetration, strategy will be chosen. Is the objective profit maximization? If so, either a skimming or sustained premium price approach will be used. Is the company struggling to survive? Then crisis pricing may be used to secure as many customers as possible with the hope of converting them to higher price customers later. Pricing strategies go beyond a single price for a single product. Payment terms are a method for controlling price by reducing the upfront cost to the customer by extending the length of time over which the price is paid. Volume pricing is used to reward customers that purchase significant quantities of product. Coupons, rebates, and allowances are promotional pricing vehicles. Finally, once pricing choices have been made, market conditions will impact whether, and how much, fine-tuning is required to sustain marketplace interest and support for the products. The pricing metrics discussed in this section are: 40. Price 41. Mark-up pricing 42. Target return pricing 43. Sales price variance

DOI 10.1515/9781501507304-006

  Part 6: Price Metrics 44. Markdown goods percentage 45. Profit impact

Chapter 40 Price Measurement Need Determining the right price is one of marketing’s primary tasks. Price has a significant influence on a company’s success since revenues result from a specific number of units sold times the price charged, and price influences customer perceptions.

Solutions The matrix below outlines four price strategies (see Figure 40.1):i

Figure 40.1: Pricing Strategy Matrix

Economy pricing describes charging a small mark-up above cost. Large scale retailers are typically associated with this approach because they have the size and scale to drive prices lower when working with suppliers to secure large volume contracts. Penetration pricing describes when companies charge the lowest possible price to gain market share while still making a profit or, at a minimum, breaking even. Cost or production efficiencies allow this kind of pricing to work, but the challenge is sustaining the cost efficiencies and advantages over time. Android smart phones illustrate this, as they are priced cheaply to increase market share. Skimming is when the marketer charges the highest possible price that the market will bear relative to competitor offerings, if any. It can be used in the early stages of market development for a new product, when the quality of offerings in the overall market is low due to the

  Chapter 40: Price market’s immaturity. In contrast to Android, Apple iPhone employs a skimming pricing approach, charging a higher price. As the market matures, if the company maintains a quality edge as competitors enter, then their pricing strategy might shift to premium. Premium pricing describes the highest possible price charged over time, due to the company’s dominant market share position, unusually high quality products and corresponding image, and a unique offering in the market relative to competitors. For years, Singapore Airlines commanded premium prices for each class of service due to its longstanding reputation for consistent and often unrivalled quality. Customers paid more because the entire experience was superior to that of rivals.ii Once marketers have planned their pricing strategy, they can run a simple calculation to determine if a retail price yields a satisfactory net price once discounts and taxes are included: P = PL – D – A – T Where P = price (the final price realized) PL = list price (your target full retail price) D = discounts (percentage reduction from list price, usually based on volume) A = allowances (price reductions issued for trade-ins and/or promotional dollars from cooperative marketing activities between the manufacturer and retailer) T = taxes and tariffs Let’s assume the marketer has set a retail price target of $10. Taxes and tariffs imposed by the tax authorities, amount to 5%. The marketer decides a promotion program is needed to induce more sales, with the following offer: – discounts that average 5%; – allowances that average 2%: P = $10 – $0.50 – $0.20 – $0.50 = $8.80 Therefore, the list price of $10 nets out to $8.80 per product sold. The marketer may want to test this pricing level with a selection of consumers and choose an online survey to maximize the potential responses. Let’s assume three price variations are included in the test (see Table 40.1):

Impact  

Table 40.1: Test Results from Pricing Test Price (before discounts and taxes) Orders Revenue

$

$

$

,

,



$,

$,

$,

In this case, the middle price of $10 produces the highest number of orders while the $20 price produces the highest revenues. The marketer must decide which is more important: the number of customers or the revenue generated from a smaller group of premium buyers. The answer will depend on the marketing strategy and overall business objectives, as well as the company’s (or product’s) image and position in the market.

Impact All of the price components described could have been altered to encourage demand: lower list price, higher discounts to inspire the retailer to buy larger quantities, higher allowances to encourage more promotion and support from the retailer, and so on. Marketers have no control over taxes and tariffs, but they do need to factor them into their final pricing analysis and recommendations. If the marketer’s goal was to maximize profit and position the product as a premium, then the $20 suggested price is the most appropriate. Of course, customer perceptions of value have a direct impact here. A pricing strategy will include considering the company’s volume objectives, profit objectives, or some other set of considerations such as competitive parity. If volume is the primary goal, then the marketer will pursue unit and/or market share growth. Penetration pricing is the best approach in this case. This means setting the price low enough to capture market share rapidly. It is most often used when competitors have identical, similar, or better products. If the objective is profitability, then a skimming pricing strategy is most often used in the early market development stages, transitioning over time to a premium pricing approach. This means that a company believes its product offering is unique and innovative and, consequently, has a probable lead over the competition. Companies price at a premium level both to capture higher profits and to establish and reinforce a market-leading position. Over time, marketers may reduce the price as competition enters (which it will inevitably do, since competitors will notice a company’s success and want to get their share of it as well), but this may risk dilution of the company’s premium reputation. Alternatively, the marketer can opt for value-added changes in the product that keep its price at a premium level

  Chapter 40: Price Marketers are not limited to these approaches. It is quite possible that a blended approach may be the most sensible, whereby a firm chooses to price mid-market. Once again, this decision must be considered in the context of a firm’s overall positioning objectives. Often, a middle approach can become no-man’s land in which the products are not perceived as either premium or mass market. Consequently, the consumer does not know what the product stands for. If a reasonable benefits argument for this middle approach cannot be made, then consumers are likely to buy on the basis of either lowest cost or most unique features. Pricing data is found in the company’s business and sales plans for each product. Depending on the business sector, sales representatives may control final price (usually within preset guidelines) because they are dealing directly with the customer at the point of sale and know first-hand what the customer is seeking, and/or the customer is seeking to purchase significant volumes and would expect reduced prices as a result. Depending on each company’s accounting practices, allowances and discounts may be counted against the marketing’s programs budget, or they may be counted against the sales team directly, especially if each sales person’s compensation is tied to measures of financial performance such as profitability. It could also be a combination of these methods.  i Adapted from bdc.com, How to Price Your Product: 5 Common Strategies. Retrieved May 17, 2017 from https://www.bdc.ca/en/articles-tools/marketing-sales-export/marketing/pages/pricing-5common-strategies.aspx ii Intelligence Node, 5 of the Best Penetration Pricing Examples. Retail Intelligence Blog, December 19, 2016. Retrieved May 22, 2017 from http://www.intelligencenode.com/blog/5-best-penetrationpricing-examples/; April Maguire, 6 Different Pricing Strategies: Which Is Right for Your Business? Intuitquickbooks. Retrieved May 21, 2017 from https://quickbooks.intuit.com/r/pricing-strategy/6different-pricing-strategies-which-is-right-for-your-business/; R. J. Dolan, “How Do You Know When the Price Is Right?” Harvard Business Review (September–October, 1995): N. Usborne, “How to Determine the Best Price for Your Product or Service,” February 14, 2006, http://www.marketingprofs.com/6/usborne6.asp; Adapted from: Knowledge@Wharton Newsletter ‘How Companies Use (and Abuse) Law for Competitive Gains,’ http://knowledge.wharton.upenn.edu/article/978.cfm, which is based on G. R. Shell, “Make the Rules or Your Rivals Will”; Crown Business, 2004.

Chapter 41 Mark-Up Pricing Measurement Need Determining the right percentage to add to costs, to recover costs, and make a small profit.

Solutioni This pricing method adds a slight increase, or “mark-up,” to the product’s (or service’s) cost. It is often used in retail businesses. Companies using it would calculate their base costs for a project or product, then add a percentage mark-up to reflect the premium they believe their product or service represents. This is represented by the following formula:

MUP =

UC (1 − ROSe )

Where MUP = mark-up price UC = unit cost ROSe = expected return on sales Unit cost must be determined to calculate the mark-up pricing formula. To calculate unit cost, use this formula:

UC = Where

VC + FC US

UC = unit cost VC = variable cost FC = fixed cost US = unit sales (in units, not dollars) Retail businesses will use mark-up pricing that ensures their costs are covered and a reasonable profit is made, yet does not deter customers from purchase. Manufacturing operations have a similar approach that requires understanding certain key costs and sales estimates to calculate a cost per unit, from which the mark-up price can ultimately be determined.

  Chapter 41; Mark-Up Pricing In the following case, Company X makes Ginormatical Fladgits. The following are their expected costs and sales: – Variable costs $15 – Fixed costs $200,000 – Expected sales $40,000 Company X positions its Ginormatical Fladgits at the premium end of the market because they use premium materials, so while their costs are slightly higher than their competitors, they are able to command high prices due to the added value their products offer. Therefore, Company X expects a mark-up of 20%. Their pricing can now be calculated. First, we determine unit cost:

= Unit cost variable cost + Unit cost = $15 +

$200,000 $40,000

fixed cost unit sales

Next, we add this figure into the mark-up price equation:

Mark-up price =

unit cost (1 − expected return on sales*)

Mark-up price =

$20 = $25 (1 − 0.2)

Company X’s mark-up price to their retail accounts is $25. Their profit is $5 on each Ginormatical Fladgits they sell.

Impact While mark-up pricing is generally simple, it is not always the most effective approach to pricing. Simple, because businesses only need to estimate the mark-up desired to earn above cost, and then price accordingly. Not always effective, because businesses may not be maximizing profit or sales potential. Perhaps the customer sees Company X’s Ginormatical Fladgits as being of only mediocre value, despite the premium materials. If so, Company X is unlikely to hit its sales target. On the other hand, customers may perceive them as being of extraordinary value at $50. Company X’s marketers then have to consider whether they would sell just as many if the price were $5 or $10 higher, thereby improving their margins.

Impact  

While mark-up pricing is simple, since it is really based on covering costs plus adding a little margin, it may leave out any unique positioning opportunities that could help marketers build a more reputable, exclusive brand. Even if it was not marketing’s goal to be a high-end brand, money may still be left on the table if mark-up pricing is the primary pricing guide. Mark-up pricing is based on estimates of the total costs for a project or product and, therefore, the data can be found in the company’s marketing plans and accounting budgets for each department. Identifying the costs is the tricky part, so a company’s systems must be sophisticated enough to measure cost inputs, both fixed and variable, to the unit level. Once the costs are known, or estimated, the marketing manager’s job is to identify a reasonable mark-up price. This is most likely driven by the company’s strategic margin goals for each product line, as well as the positioning goals for each product in each product line. The reason for noting the positioning goals is that pricing has a direct impact on consumers’ perceptions of a product’s position vis-à-vis the competition. Finance and/or accounting will have information on specific fixed costs allocated to the marketing department. As with all numbers that describe or affect your marketing decisions, you should double-check accounting’s figures against your own budget figures to see what differences there are, if any. Usually, the accountants have specific rules that govern how to count certain costs and these tend to be more detailed than the basic budgets the marketing departments (or most other departments, for that matter) would submit. It is quite likely that your figures will not match the figures from accounting or finance, but that is probably as a consequence of these rules. *Note: In Chapter 6, “Return on Sales,” we learned that the formula for return on sales is:

ROS =

Pnbt S

 i Adapted from P. Kotler, M. L. Siew, H. A. Swee, and C. T. Tan, Marketing Management: An Asian Perspective (Upper Saddle River, NJ: Prentice Hall, 2003).

Chapter 42 Target Return Pricing Measurement Need When the company’s investment decisions are dictated by target rates of return, marketers must determine the best price for a given product.

Solutioni Target return price is designed to cover all costs and yield a specified or target return. Like mark-up pricing (Chapter 41), target return pricing is another cost-based approach.

TRP = Where

Cpu + R × I Su

TRP = target return price Cpu = cost per unit R = expected return I = capital invested Su = unit sales Let’s assume that a new athletic company, called All Goal, competing only in football (soccer) shoes, decides to launch a new product to compete against Adidas and Nike. Sales are expected to be 100,000 units in the first year, but the company believes a new midsole manufacturing machine is necessary to successfully ensure product quality. All Goal’s marketing manager wants to determine the target return price needed if $3 million were invested in the new midsole manufacturing machine purchased. All Goal’s products are positioned as premium. The cost per unit is $35. Senior management seeks a return on investment (ROI) of 25%. The target return for the $3 million investment, seeking an ROI of 25%, equals $750,000. Here’s how the analysis looks: .25 × $3,000,000 35 + $42.50 TRP = = 100,000

Therefore, to achieve a 25% ROI, the target return price must be at least $42.50.

  Chapter 42: Target Return Pricing

Impact Target return pricing depends on the assumptions and expectations that went into it. Marketing must determine break-even at different sales volumes to identify an accurate target return price. An important caveat: target return pricing ignores competitor pricing, customer response, and market trends, all of which can affect the final analysis. Preparing multiple scenarios are required so that an informed decision can be made. The data is found in the company finance and accounting departments. One of the formula’s variables, capital invested, is located in the balance sheet under liabilities, either as shareholders’ equity or long-term debt. Unit sales are found, in their final form, in the income statement. However, since those are typically completed at the end of business cycles (quarterly or annually), preliminary figures can be found in sales or preliminary finance reports.  i P. Kotler, M. L. Siew, H. A. Swee, and C. T. Tan, Marketing Management: An Asian Perspective (Singapore: Prentice Hall Pearson Education Asia PTE Ltd., 2003), 496.

Chapter 43 Sales Price Variance Measurement Need Understanding actual versus budgeted price helps marketers identify and address the factors (i.e., distributor demands, customer needs, market conditions, competitor actions, etc.) that cause actuals to differ from plan.

Solutioni The sales price variance formula is: SPVt = Uat × (Pat – Pr) Where SPVt = sales price variance in time period t Uat = actual units sold in time period t Pat = actual price during time period t Pr = retail or recommended price To illustrate, Glob Toys (not real!) sells a product called “SlobberChops,” which is a mechanical dog that drools perpetually after an internal water chamber is filled. The company sold 100,000 units last year at an actual price of $4 each. Suggested retail was $5: SPV = 100,000 × ($4 – $5) = –$100,000 The calculation shows that Glob Toys had a sales price variance (SPV) of $100,000, meaning that actual sales were lower than projected sales by that amount. We look at a more sophisticated treatment: Glob Toys has two products, BlobSlob (a slimy clay that can be molded into monster shapes) and SlobberChops. Glob planned their expected results as follows: Projected performance Unit sales (projected) Unit price (recommended) Unit cost (projected)

BlobSlob 100,000 $5 $3

SlobberChop 50,000 $10 $6

  Chapter 43: Sales Price Variance Actual performance

BlobSlob 120,000 $4 $3

Unit sales (actual) Unit price (actual) Unit cost (actual)

SlobberChops 60,000 $8.50 $6

In this case, costs remain the same because Glob Toys had locked in supplier prices and production costs in advance. We can now compare: Projected revenue

(100,000 × $5) + (50,000 × $10)

= $1,000,000

Actual revenue

(120,000 × $4) + (60,000 × $8.50)

= $ 990,000

Projected profit

(100,000 × $2) + (50,000 × $4)

= $ 400,000

Actual profit

(120,000 × $1) + (60,000 × $1.50)

=$

210,000

–$

190,000

Total sales variance The next step is to calculate the SPV:

SPV = {120,000 × ($4 – $5)} + {60,000 × ($8.50 – $10.00)} = –$210,000 Therefore, Glob Toys’ SPV shows the effect of price changes from projected to actual, resulting in this case in $210,000 less in total sales versus plan.

Impact While it is clear that price changes have an impact on actual financial performance versus projected, it is less obvious how to fix it in the future. The marketer could mandate a strict “no discounting” policy, with the chief executive officer and chief financial officer’s blessings, and some consumers would happily pay the full amount, but many more would simply shift to a competitor product or delay purchase to a later time period. This would exacerbate the sales variance problem since there would now be a smaller customer base and lower sales, not to mention a probable negative perception of Glob Toys’ image, particularly from retailers who want to sell the inventory quickly. They may reduce their future purchases of Glob Toys’ products, knowing that the firm is inflexible and insensitive to their needs and the market conditions that created them. Marketers in this situation have several options:

Impact  

1. Hold firm on price and risk reduced overall sales and a smaller customer base. 2. Allow pricing deviations to attract more customers, but recognize the lower sales as a result, plus reduced margins. This may increase market share for a short period of time, but it may also lock in a more permanent lower-margin performance. 3. Reduce costs to allow for greater pricing flexibility without eroding margins. 4. Increase the value-add of the products, perhaps by offering a unique loyalty program or a clear explanation for why their product is superior and why it is relevant to the customer. None of these are easy choices and a marketer may try each of these in an effort to find the best combination that maximizes sales and profits, and attracts the largest number of customers. Data for unit price will be found in manufacturing reports and aggregated financial summaries, both quarterly and annually.  i C. Gilligan and R. M. S. Wilson, Strategic Marketing Management: Planning, Implementation & Control (2005), 781.

Chapter 44 Markdown Goods Percentage Measurement Need Retailers sell products at both full retail and markdown prices. Markdowns refer to the amount reduced from the original selling price. The markdown goods percentage (MGP) describes the percentage of total net sales attributed to products sold at markdown prices. MGP also helps retailers determine their effectiveness at selling products at full price since the difference between total net sales and sales from markdown prices is full price sales.

Solutioni MGP is represented as follows:

MGP = Where

Snmt × 100 Sn

MGP = markdown goods percentage Snmt = net sales at markdown during time period t Snt = total net sales during time period t For example, if a retailer sells $10,000 per day of merchandise, of which $2,500 is attributed to markdowns, then the MGP is 25%. = MGP

$2,500 × 100 $10,000

= 25%

Impact The MGP offers a retailer insight about how its products are selling by showing the percentage of sales from both full retail and markdown pricing. If the markdown percentage is high, then it is an indication of problems somewhere in its operation that need to be addressed, including reviewing their merchandise selection and store design, comparing their pricing to the competition’s, evaluating their advertising ef-

  Chapter 44: Markdown Goods Percentage forts, and examining their inventory levels to determine if they have too much inventory on certain items. Each of these factors can contribute to a high MGP. Retail margins are notoriously low, so avoiding a high MGP is a priority for retailers and must be addressed quickly. Data is tracked through computerized systems at check out, including scan and barcode data.  i ASID Insider, Realities in Retail: Markups, Markdowns and Margins, August 21, 2015. Retrieved May 2, 2017 from http://insider.asdonline.com/calculating-retail-margins/

Chapter 45 Profit Impact Measurement Need When launching products, marketers want to calculate the potential profit when the costs of manufacturing, product, and pricing activities are included.

Solutioni Profit impact describes the effect on profits resulting from a company’s product-related expenditures. Two preliminary steps must be taken before calculating profit impact: determining the manufacturing sales price (MSP) and the contribution per unit (Cpu): MSP = Pr – Mr – Mw Where Pr = retail price Mr = retail margin Mw = wholesale margin or mark-up Contribution per unit is based on the formula: Cpu = MSP – Cv Where Cv = total variable cost Profit impact can now be calculated with the following formula: Profit impact = (Cpu × Us) – Cfc Where Cpu = contribution per unit Us = units sold Cfc = total fixed costs To illustrate, let’s assume Jakalumpur Remote is a small manufacturer of generic remote controls for use with home audio-visual equipment. The remotes have the following profile:

  Chapter 45: Profit Impact – – – – – – – –

Retail price of $10 Retail margins are 30% Wholesale margins are 8% Remote market is 35 million customers Market share is 20% Units sold are 7,000,000 Variable costs are $3 per remote Total fixed costs are $1,800,000

Step 1: Calculate MSP: MSP = Pr – Mr – Mw MSP = $10 – $3 – $.8 MSP = $6.20 Step 2: Calculate Cpu: Cpu = MSP – Cv Cpu = $6.20 – $3 Cpu = $3.20 Step 3: Calculate profit impact: Profit impact = (Cpu × Us) – Cfc Profit impact = ($3.20 × 7,000,000) – 1,800,000 Profit impact = $20,600,000

Impact The profit impact figure measures the effect marketing expenditures have on the profitability of a company, product line, or individual products. It does not fully account for marketing’s entire contribution, since it focused primarily on product cost. Much of the research on profit impact is dated, conducted in the 1970s and 1980s during an era dominated by manufacturing, under-representing the impact from nonmanufacturing activities. A more updated approach would include marketing’s expenditures to promote products (through advertising, sales programs, promotions, public relations, and pricing strategies) in the period of time measured. Although not always felt by consumers in the market at the same time, the exclusion of these marketing activities distorts the marketing contribution; yet these are necessary components for a

Solution  

successful product launch. There is a long-term, residual benefit from marketing activities undertaken today, just as there is from products produced today that are enjoyed over months and years. The Cpu information will be found in the company’s retail and wholesale pricing and margin data, within marketing and finance. The same is true with the information pertaining to units sold. Marketers may struggle to acquire timely data, but a visit to the sales department will usually provide the most recent figures since those may not have been forwarded to the finance and accounting groups yet. The fixed costs would also be in the financial figures, but could be derived department-by-department.  i R. M. S. Wilson and C. Gilligan, Strategic Marketing Management: Planning, Implementation & Control (2005), 112–115; R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 14–18, 290–292; Paul W. Farris and Michael J. Moore, eds., The Profit Impact of Marketing Strategy Project: Retrospect and Prospects (Cambridge University Press, 2004).



Part 7: Advertising/Promotion Metrics The term “promotion” is misleadingly narrow. A better term is integrated marketing communications (IMC) because it more accurately describes the important interdependence between each promotion category. The role of IMC is to provide clear marketing communications across varied media. Media choices are made based on their ability to deliver an audience that the marketer seeks and hopes to convert to paying customers. No single medium works best, so sophisticated marketers are developing multilayered campaigns that capture customers with similar (not identical) messages in different media. Not all of these vehicles are successful, so marketers must determine which media reach their target audience most effectively and then craft a campaign that appeals directly to them. More problematically, the rapid advancement of the Internet, blogs, and mobile communications have accelerated the pace at which products are known around the world. Many of the IMC components are driven by word of mouth, not impressions, Gross Rating Points, or reach. The challenge for marketers is how to manage these viral effects, because they are otherwise not controllable. Careful planning of products, pricing, market selection, media vehicles, and communication strategies is more important than ever, and the need to measure these has grown as well. The advertising/promotion section reviews the following metrics: 46. Share of voice 47. Recall 48. Recognition 49. Reach 50. Frequency

DOI 10.1515/9781501507304-007

  Part 7: Advertising/Promotion Metrics 51. 52. 53. 54. 55. 56.

Gross rating points Cost per gross rating point Response rate Conversion rate Advertising-to-sales ratio Promotion profit

Chapter 46 Share of Voice Measurement Need To measure the organization’s share of the total media expenditures in the market.

Solutioni Share of voice is calculated by:

Vs =

A ∑ At

Where Vs = your share of voice expressed in percentage terms A = your advertising spend for a given product ∑At = total of all market advertising spend for the same type of product Suppose $100 million is spent on ads for portable music players overall, and a specific company spends $5 million to promote its own player. The company’s share of voice would be 5%: Vs =

$5,000,000 $100,000,000

= 5% Measuring online share of voice has led to new tools specific to the digital world, including:ii – Search Engine Optimization (SEO) is a way of measuring the organic (unpaid) visibility ranking of the website when using a search engine. – Pay Per Click (PPC) is a fee paid by advertisers whenever their ad is clicked. – Click Through Rate (CTR) describes the ratio of users that click on links relative to the total number of users that visit a page. – Impression shareiii is the percentage of searches for keywords shown on the advertiser’s ads versus total searches. It is measured as:

  Chapter 46: Share of Voice

I=s Where

I × 100 Ie

Is = impression share I = impressions Ie = total eligible impressions

Impact Marketers hope to grow the business by investing in programs, including marketing communications that inspire customers to buy. Advertising is a specific activity within marketing communications that can have a significant influence on perception. In this regard, a high share of voice can lead to increased awareness, which, ultimately, can lead to increased sales and market share. Marketers need to be cognizant of the target audience, the time of day ads are run, and the type of publication in which they are run. Finally, the type of media, mass versus niche, attracts different audiences as well. While a high share of voice may indicate a larger amount of money devoted to advertising versus competitors, marketers need to carefully consider the relevance of the message to the actual consumers targeted. A one-time high share of voice may not indicate a meaningful or impactful share of voice. Advertising totals will be captured in the marketing plan and marketing budget. Typical company finance and accounting reports measure advertising costs as a component of total marketing expenditures. Reviewing industry trade publications, thirdparty research reports, business magazines with special industry sections, and local business journals will provide broader data and guidance. Relevant statistics may also be gleaned from press releases or sales literature from businesses that have already bought industry reports and are using the information in their publicity.

 i P. Kotler, M. L. Siew, H. A. Swee, and C. T. Tan, Marketing Management: An Asian Perspective (Upper Saddle River, NJ: Prentice Hall, 2003), 650; C. Doyle, Collins Internet-Linked Dictionary of Marketing (HarperCollins, 2003, 2005) 287. ii Kit Smith, How to Measure Share of Voice: PPC, SEO, Social Media, June 15, 2106, Brandwatch. Retrieved June 11, 2017 from https://www.brandwatch.com/blog/how-to-measure-share-of-voice/ iii Adwords Help, Google. Retrieved May 1, 2017 from https://support.google.com/adwords/answer/2497703?hl=en

Chapter 47 Recall Measurement Need To determine how effective advertising is based on whether target audiences can recall seeing or hearing an advertisement from a previous exposure.

Solutioni Recall is a test of overall brand awareness or of advertising impact. In brand awareness, recall simply measures whether a consumer can name (or “recall”) a brand or advertising campaign without further prompting. There are two types of recall, which are measured with recall tests. Consumers are asked which brands in a particular product class (i.e., soaps) they recall, and their replies tend to fall into one of two categories (and sometimes both): – Top of mind: the first brand recalled – Dominance: the only brand recalled In advertising, recall has a similar meaning, except that the consumer recall is triggered by recalling an advertisement on a given media vehicle (television, radio, internet, print) within a given time period, after the advertisement has run or been shown previously. There are two variations of recall in advertising: – Aided recall: A research technique in which a person is shown an ad, product, brand name or trademark and asked to recall the previous time they saw it. – Unaided recall, where no prompting occurs. Recall is not a formula, but a type of question, including: – Which brands in this product class do you recall? – Please describe the most memorable ad from the last television show you watched. – Do you recall an ad that had trumpet music and birds flying? – Recall is further divided into aided and unaided recall

Impact Recall is a basic measure of advertising effectiveness, but it is not a measure of preference. Recall results do not tell marketers if a consumer has decided to purchase products advertised, or whether they even have a slight preference for the brand.

  Chapter 47: Recall Qualitative research, as is some quantitative research, is subject to bias and interpretation. Recall is a reasonable test of how successful the marketing efforts have been in building awareness. But an important question to remember is: what period of time is being evaluated? A marketing campaign might be launched and sales increase 25%, and a marketer might reasonably conclude that the campaign was the reason for the increase. But that might be wrong. The competition might have made a strategic blunder, causing customers to switch away. Or, the marketing efforts of previous years might finally be bearing fruit. Recall can also reveal if a once distinctive brand identity has shifted from being associated with the company and, instead, has become synonymous with the category. Examples include: – FedEx – Rollerblade – Windsurfer – Aspirin – Cellophane – Kleenex – Escalator – Xerox Recall can signal negative association. Companies risk developing negative recall results if their products or product associations (the extended touch points in the market where their product is represented) are controversial or offensive. Recall can even affect entire industries. Prior to the 2008 financial crisis, banking and the financial services industry in general was the source of significant economic growth and vitality, particularly in the U.S. real estate sector. In post-2008, the banking industry was viewed far more skeptically and negatively, fueled in part by unethical and predatory practices that led to the global financial crisis in the first place. In essence, while recall of the banking and financial services industry is quite high, it is not the sort of recall one would wish for. Recall data is gathered through several different research techniques such as surveys, focus groups and interviews. The research can be conducted by an independent third-party market research firm, or through your own, in-house research project. In either case, survey design is important, as the way questions are asked can affect how consumers answer. Focus groups must also be planned thoughtfully and led by an expert facilitator who can keep the discussion going and on track. Much of the information gathered from these research techniques is qualitative and, therefore, harder to quantify. However, a good market researcher or marketing manager would, at a minimum, summarize the findings overall, then organize the answers into common themes. Repeated comments can then be tallied to indicate which consumer insights are most common and which are marginal or irrelevant.

Impact  1  i C. Doyle, Collins Internet-Linked Dictionary of Marketing (HarperCollins, 2003, 2005), 275; T. Ambler, Marketing and the Bottom Line (FT Prentice Hall, 2003); J. Imber and B. Toffler, Dictionary of Marketing Terms (Barron’s Educational Services, Inc., 2000), 22, 561.

Chapter 48 Recognition Measurement Need Determining whether consumers remember the company, ad, or product when they are shown its advertisement again.

Solutioni Recognition research asks: have you been exposed to this brand (or product, or ad campaign) before? This and similar questions are used to gauge the consumer’s awareness.

Impact Measuring recognition can reveal whether or not an advertising campaign is remembered by consumers. However, recognition is really the weaker cousin of recall, since it requires that the consumer be prompted directly with the name of the company, product, or description of the literal advertising message.

Note on Recognition and Recall High recognition and low recall is not ideal when viewed through the lens of advertising effectiveness because it means consumers remember the ad, product, or company only after being prompted. High recall is better. But high recognition and high recall is best, assuming the combination is a positive association, not negative. Niche brands tend to have high recall with loyal consumers, but low overall recall and recognition in the general market. The combination of high recall and high recognition can often result in positive feelings from consumers. Familiarity often leads to successful advertising and premium perceptions over less-known rivals. Of course, familiarity can also breed contempt or indifference from excessive message repetition or irritating advertising. Finally, since part of the reason companies market themselves is to build trust with consumers, their efforts to advertise and, thereby, attract attention often signaling that they believe in their products and are willing to stand by them in public. At least, one hopes that is the case. A key question that marketers must consider is: What are good levels of recall and recognition? Both recall and recognition are measures of awareness, but is an

  Chapter 48: Recognition awareness level of 30% good or bad? The answer depends entirely on the product and industry. For example, 30% awareness may be low if the metric is for a consumer products company with multiple brand names. For example, let’s look at laundry detergent. Tide, from Procter and Gamble, is well known in most parts of the world. It is the category leader, and has been for years. In asking consumers if they can name a laundry detergent brand, Tide is likely to be one of several brands mentioned, indicating good recall. Alternatively, if consumers were asked if they have heard of Tide, the likelihood of “Yes” being the answer is also quite high, indicating high recognition. Both indicate a high level of awareness. But what is that level? Let’s assume that the awareness level is 90%, which would mean that Tide is mentioned nine out of ten times in surveys that ask respondents if they can name a brand of laundry detergent (recall) or if they remember the brand called Tide (recognition). But what is the awareness level if respondents can name Tide seven times out of ten, but can remember it nine times out of ten when prompted? The answer is unclear, highlighting the challenge of precisely measuring awareness. If a competitor’s (let’s call them “Xtra Sparkle”) awareness level among consumers is 30% in this category, then clearly the competitor is cited and remembered less than Tide. Is 30% good? Compared to Tide, it is clearly not as good. Is 30% bad? Perhaps “bad” is an overstatement. This is somewhat specific to the context, and there is no set level that is considered a good level of awareness. When compared to Tide, Xtra Sparkle does not generate the same level of awareness. Alternatively, if Xtra Sparkle had been launched in the past year or two, then 30% awareness signals rapid growth and Tide might have cause for concern. Conversely, if Xtra Sparkle had been around as long as Tide, then its 30% awareness level would not be as impressive. Similar to recall (Measure 47), recognition data is from surveys, focus groups, interviews conducted by an independent third-party market research firm, or through an in-house research project.  i C. Doyle, Collins Internet-Linked Dictionary of Marketing (HarperCollins, 2003, 2005), 275; T. Ambler, Marketing and the Bottom Line (FT Prentice Hall, 2003).

Chapter 49 Reach Measurement Need To evaluate the size of the audience reached at least once during an ad campaign.

Solutioni Reach is the number or percentage of people in the target audience reached by a single exposure (advertisement) in a given period of time. An exposure is defined as an opportunity for members of the target audience to see or hear a particular ad. This does not mean that the target audience actually sees or hears the ad. For example, your company may advertise on television, but that does not mean that the target audience sees it. When a member of the target audience actually sees or hears an advertising message, this is known as an impression. Internet advertising refers to this as a view. As a brief illustration, assume that there are ten households in a particular market. Five of the households are exposed to a company’s advertisement one or more times. Since the total market is ten households, and five are exposed, the reach is 50%.

Impact As described at the beginning, reach does not actually measure impressions, only that the person was in the general location of the message. An ad in a magazine counts as an exposure to everyone receiving the magazine and whether or not they saw the ad. A 30-second television commercial counts as an exposure even if the person left for the kitchen during the ad. Therefore reach must be used conservatively, perhaps even reducing the reach number by an estimate of the probability that the ad was actually seen. Reach is a decision about how many persons in the target market should be reached by exposure one or more times. A company may prefer to use its money to reach a smaller percentage of the target market with a greater frequency. Much depends on the product and on an estimate of how many exposures are necessary to register an actual impression. Reach would be incorporated in a description of the proposed advertising campaign, including the target audience, the creative content, the media vehicle, and the costs. Media companies usually have media kits that provide data on reach, as well as other target audience profile demographics in-

  Chapter 49: Reach cluding age, income, and race. Media companies include television and radio stations, magazine and newspaper publishers, outdoor media (billboards), and online portals. Reach is set during the marketing planning process. Marketers would either contact media companies directly, or use an ad agency, to learn about each media vehicle’s reach statistics. Reach is an estimate that one must use cautiously. Media people will generally estimate reach on the high side (because they can charge more), but they are supposed to observe rules for estimation set by the Advertising Research Foundation. Knowing reach enables marketers to more effectively select the media vehicle that best captures the target audience they seek. The actual reach data may vary depending on the time of day and the program (if it is broadcast) or the content, so marketers must decide what is the most effective reach they can achieve for the proposed investment.  Laura Lake, Learn About Market Reach and Why It’s Important, The Balance, June 26, 2017. Retrieved July 11, 2017 from https://www.thebalance.com/what-is-market-reach-2295559

i

Chapter 50 Frequency Measurement Need Determining how frequently to run an advertisement.

Solutioni Frequency describes the number of times an average member of the target audience is exposed to the same ad, commercial, or program over a given period of time. To illustrate, if the five homes reached in the reach example (Chapter 49) saw a company’s ad an average of three times, then the frequency would also be three.

Impact Frequency is determined when considering advertising budget allocations, and the costs within are based on information found in media kits from the chosen media (digital, social, radio, television, Internet, print, etc.). Pricing usually decreases when more advertising exposures are purchased. For example, popular U.S. broadcast television programs shown during prime time (considered 8–11 p.m. on the East and West coasts and 7–10 p.m. in the Midwest, when families are most likely home watching television) charge premium prices, even with frequency discounts, reflecting the size and characteristics of the target audience viewing the program. This is also true for radio advertising, when peak drive time (either the beginning or end of the typical work day when people are driving to/from work in their cars) commands higher pricing than off-peak time slots. Print publications also vary their pricing based on frequency. An ad that runs once is more expensive on a per-insertion basis than if the ad were run several times in either the same or multiple issues. Furthermore, location within the publication influences price, with locations such as inside covers or the back cover considered more valuable and, therefore, more expensive. Similar to reach, frequency helps guide the marketing planning and investment process. Marketers have to decide how to split a given budget between reach and frequency. If the objective is merely to create awareness, then a marketer would choose an advertising media that reaches the broadest possible audience. However, reaching a broad audience just once may prove to be a waste or misuse of budget money. Part of marketing’s role is to develop and nurture relationships with the company’s target audiences. It is quite challenging to develop a relationship based on one exposure,

  Chapter 50: Frequency even if it has a broad reach. It places disproportionate emphasis on developing a message with widespread and lasting appeal for a world animated by consumers that are unpredictable with their preferences and behaviors. Furthermore, marketers would have significant pressure to select the right media vehicle for this single exposure, with the understandable risk that the message may be completely ignored (recall the difference between exposure and impressions in the chapter on reach). To maximize limited budget resources, a marketer may instead consider repeating advertising messages to build the potential for lasting memory (see the chapters on brand recall and brand recognition, since they relate to this). But repeating messages is only part of the solution. Marketers must still ensure the message is targeted to the right audience, is relevant to their needs, and is capable of positively affecting consumer perceptions of the product or brand being advertised. While there is no single approach that guarantees an advertising campaign will be successful, many companies test their messages with focus groups (randomly or preselected small groups of consumers). This test usually involves exposing the focus group to the advertising message, then having a trained facilitator from a market research firm who can engage the participants in a discussion about the impact of the message. The data for frequency is found in the aforementioned media kits and similar materials from media companies. The data almost always includes statistics on the media’s audience (demographics, lifestyle/psychographics, etc.).  Jeffrey Pilcher, Say It Again: Messages Are More Effective When Repeated, The Financial Brand, September 23, 2014. Retrieved May 19, 2017 from https://thefinancialbrand.com/42323/advertisingmarketing-messages-effective-frequency/; 2. Gian Fulgoni, The Varying Impact of Ad Frequency in the Digital Environment, ComScore, March 31, 2010. Retrieved May 19, 2017 from https://www.comscore.com/ita/Insights/Blog/The-VaryingImpact-of-Ad-Frequency-in-the-Digital-Environment i

Chapter 51 Gross Rating Points Measurement Need When marketers advertiser their company’s product, particularly on television in the United States, they want to know the size of the audience or the equivalent advertising weight for the chosen marketing vehicle.

Solutioni Gross rating points (GRPs) are an aggregate measure of the total amount or volume of advertising exposures a media campaign will generate via specified media vehicles (often television or radio, although newspapers use it as well) during a specific time period. In broadcast advertising, each GRP is equal to an advertising audience size of 1% of the total potential audience for a given media vehicle. In mathematical terms, it is the product of reach (the number or percentage of people in the target audience reached by a single exposure) multiplied by the frequency (the number of times the target audience is exposed to the same ad, commercial, or program). GRP is represented by the following formula: GRP = Reach × Frequency As a brief illustration, if your company chose to run a television advertisement at the World Cup Finals and 60% of the world’s population was viewing, then the reach would be 60. Let’s further assume that the same ad is run on other programs, creating a total combined reach of 75%. If the ad is run three times (frequency), then the total GRP is 225: GRP = 75 × 3 = 225

Impact GRP is a cumulative measure of individual rating points used to measure the exposure of specific marketing campaigns or programs. As a gross measure, it includes audience duplication, which refers to the number of people or households exposed to a particular ad multiple times. Duplication is important to note because GRPs can, and

  Chapter 51: Gross Rating Points often do, exceed 100% of the target population. This duplication can mislead marketers to believing that GRPs are a clear measure of impact when, perhaps more precisely, they measure exposures. A truer measure of impact would be any change (ideally, an increase) in sales resulting from the exposures. If a marketer knows that the target audience needs to be exposed to the marketing campaign five times before they decide to purchase, and he/she wishes to reach 50% of the market with this campaign, then the marketer would need a media schedule that would give at least 250 GRPs (reach =50%, frequency = 5 times; 50 × 5 = 250). It is very important for marketers to review each marketing vehicle to determine its specific GRP so that the total marketing campaign can be effectively maximized to achieve overall campaign goals. GRP is used in both marketing planning and performance review. In measuring the effectiveness of their marketing campaigns, marketers would be wise to take the added step of comparing the media kit data to the actual GRP performance for the medium used, to determine any variance, either better or worse, from the marketing plan. The actual performance data is based on audited “post-buy” information, usually collected by a third party market research firm to measure each of the media companies in the specific market or vehicle chosen. Using reach, frequency and GRP together, let’s assume there are ten households in a specific market. In this market there are also two television channels—channels A and B. Your company has decided to run a television advertisement on both channels. Six of the ten households watch channel A and two of the ten households watch channel B. During the course of the working week (Monday–Friday), the ad runs on the following schedule: – Monday = 3 × – Tuesday = 2 × – Wednesday = 3 × – Thursday = 1 × – Friday = 2 x Reach, GRP and frequency are as follows: – Reach = 80% o each house represents 10% of the selected market and eight households watch either of these channels (8 × 10% = 80%) – GRP = 140 o each house is 10% of the market, therefore each time the ad runs it represents a rating of 10  Monday = 30 rating  Tuesday = 20 rating  Wednesday = 30 rating  Thursday = 20 rating  Friday = 40 rating

Impact  

–

TOTAL: 140 GRPs Frequency = 1.75 (140 GRPs ÷ 8 households = 1.75)

Once marketers know their marketing objectives, along with their budget constraints, they can determine the media vehicles that are most appropriate. Reach, frequency, and GRP are useful measures that help a marketer evaluate the effectiveness of their final media decisions. Before evaluating the appropriateness of a particular media choice, a marketer needs to be clear on the kind of product they have, the marketing objectives required, and the target audience they wish to reach. For example, newer products usually require greater emphasis on building awareness, which may dictate a higher frequency of exposure than needed by more mature products. Therefore, the marketer’s objectives will be different in the early stages of a product’s lifecycle versus later stages. In fact, the product lifecycle is an important influence on the marketing choices made and, consequently, the specific media needed. The following example illustrates the point (see Figure 51.1):

Figure 51.1: Product Lifecycle

Figure 51.1 is a variation on the classic “S” curve (the name is derived from the shape of the curve) that illustrates the product lifecycle. While an overall marketing campaign for a product will likely have a long-term objective (such as to achieve 50% market share) and theme (for example, to be recognized as the most reliable), a product evolves overtime from being unknown to, ideally, being well-known. Each of the

  Chapter 51: Gross Rating Points stages shown above will have different marketing objectives and, consequently, different media will be needed. GRPs will vary at each stage as well, reflecting the evolving marketing campaign. Media choices will also be influenced by the kind of product, such as whether it is a simple product like soap, or a complex product like enterprise software. Complex products may require a higher frequency than simpler ones because they take longer to explain and to facilitate understanding. Furthermore, the specific media will vary as well. The marketing of complex products is likely to be more effective in information-intensive media, such as print ads in vertical trade media (versus using billboards, for example, since they tend to be better for simpler products and messages). Different geographic markets also affect media choices. The developing markets in Southeast Asia may not be familiar with a particular company’s products, even if that company is well-known elsewhere. This may influence marketers to increase the frequency so as to ensure the target audience is sufficiently exposed to the message. Cultural differences will also affect a marketer’s choice of media vehicle, frequency, and reach. The quality of the exposure is another important consideration when interpreting GRPs. A marketer needs to be aware that the target audience may “see” an ad, but may not be listening to the description or reading the content. Therefore, subtle messages may be missed by the target audience. This is an issue if a marketer discovers that a campaign with high GRPs, that looked strong on paper, actually yields a low return in terms of sales generated or negligible market share increases. Marketers will then need to review the relevance of the campaign content, the creative execution, and even their understanding of the target audience to determine why a campaign may not achieve targeted results. As with reach, the data to determine GRP is found in the media kits of the selected advertising vehicles. Radio, television, print, and online media sources provide data describing their target customers in demographic and, increasingly, psychographic terms. These customer profiles help advertisers decide if the target audience of the proposed media vehicle is suitable for their marketing needs. The media companies use the data to defend their pricing strategies, charging different prices depending on the size and location in the publication or the time of day and length for broadcast vehicles.

 R. J. Best, Market-Based Management: Strategies for Growing Customer Value and Profitability (Upper Saddle River, NJ: Pearson Education, 2005), 308; Nielsen.com, Nielsen At Adtech—Gibs on Gross Rating Points, Targeting And Data Fusion, November 5, 2009. Retrieved May 28, 2017 from http://www.nielsen.com/us/en/insights/news/2009/nielsen-at-adtech-gibs-on-gross-ratingpoints-targeting-and-data-fusion.html ; MarketingProfs.com, What Is a GRP and How Is it Calculated? Retrieved May 9, 2017 from https://www.marketingprofs.com/Faqs/showfaq.asp?ID=134&CatID=1 i

Chapter 52 Cost Per Gross Rating Point Measurement Need Marketers need to measure the cost per gross rating point, or cost per point (CPP).

Solutioni The formula for CPP is:

CPP = Where

TCat GRPTt

CPP = cost per gross rating point TCat = total cost of selected advertising in time period t GRPTt = total gross rating points during time period t CPP tells advertisers how much it will cost to reach one rating point (1% of the market). In Chapter 42, we illustrated GRPs using a hypothetical World Cup example. In that example, a company’s advertising choice yielded a GRP of 225. If the cost for television ads during the World Cup was $100,000, then the CPP is $444:

$100,000 225 = $444

CCP =

Impact Advertisers plan their broadcast media buying based on target audience statistics of the proposed media vehicle and also gross rating points (GRPs—see Chapter 51). Their final media choice will be affected by the budgeted dollars available for that media. CPP helps marketers compare media options to determine those that yield the best CPP. Cost alone will not determine the decision, as marketers also must consider target audience profiles of the various media choices, overall pricing differences that may allow better placement (such as a better time slot) and higher frequency (see chapter 41) on certain media options (perhaps because that particular media is rated lower than the others). U.S. readers will note the regular ratings battles among the major networks (ABC, CBS, NBC, CNN, MSNBC, and Fox). CPP is a good measure of

  Chapter 52: Cost Per Gross Rating Point advertising efficiency, assuming common media are being compared (comparing TV stations, for example). CPP serves a dual measurement purpose: evaluative—comparing two or more media choices; and planning—helping advertisers plan the ideal media mix based on available budget, media audience profile, and time slot placement.

 i Formula derived from J. Imber and B. Toffler, Dictionary of Marketing Terms (Barron’s Educational Services, Inc., 2000), 143 >; MBASkool, Cost per Rating Point. Retrieved May 29, 2017 from http://www.mbaskool.com/business-concepts/marketing-and-strategy-terms/12347-cost-per-rating-point.html; MuseumTV, Cost-Per-Thousand (CPM) and Cost-Per-Point (CPP). Retrieved May 10, 2017 from http://www.museum.tv/eotv/cost-per-thou.htm

Chapter 53 Response Rate Measurement Need Marketers want to measure the total number of advertisements (or mailers, or offers) they send and compare it to the number of customers who responded by clicking through or, best of all, actually purchasing. One of the marketing areas where more accurate measurement is feasible is direct marketing campaigns (such as direct mail or online permission marketing). Marketers want as high a correlation as possible between total advertisements and the total number of customers who responded to the advertisements.

Solutioni The response rate refers to the percentage of people who respond to an offer relative to the number of people who received the offer. The following formula captures the key variables: Rr =

Where

Pr Pe

Rr = response rate Pr = number of people who respond to your ad Pe = number of people exposed to your ad If a company targets 10,000 people in its direct marketing campaign and receives 200 responses, then its response rate is:

200 10,000 = 2%

Rr =

Impact Companies face increasing pressure to improve efficiency and reduce costs. Senior management expects marketing management to provide relevant, accurate information on the investment return from each marketing communications campaign

  Chapter 53: Response Rate conducted. However, this is impractical and ill advised since the purpose of many marketing activities is to shape perceptions through large scale advertising and marketing communications campaigns. Nevertheless, many of marketing’s activities, including direct marketing, can be measured. Measurements can be made with a higher degree of precision if ad campaigns are properly coded and the ensuing responses are correlated back to the originating campaign. The response rate is a basic measure that can indicate the percentage of people who find the offer attractive. If they respond, this can lead to purchase, but it is not a guarantee. Turning direct marketing responses into actual purchasers is described by the conversion rate in Chapter 54. A response may also be a request for additional information. This depends on the wording in the offer. If it is clear to recipients that they will somehow benefit by responding (such as a price discount on a favorite product, or a free gift with purchase), then the chance of converting them to actual buyers increases. However, if the offer is somewhat vague, such as describing a “hot new feature” but no other benefit or clear relevance to the target customer, then a lower purchase rate is likely. Direct marketing has proven over the years to be most successful when it is offering a tangible benefit that can be easily obtained, in contrast to developing general awareness that tends to be accomplished more effectively by broadcast advertising. Direct marketing also works well for short-term promotions aimed at increasing immediate demand and revenues. Classic marketing theory suggests that if you can convince customers to buy your product, then you have a better chance of making them loyal customers. Of course, that is dependent on your commitment to quality, service, and products that are relevant. That is not as easy as it sounds. Marketers need to be aware that response rates vary depending on the direct marketing vehicle used. Direct marketing is an effective tool when marketers and management establish clear objectives about the purpose of the campaign, design an offer that is relevant to the target audience, and set a time limit in which the offer will remain valid. Direct marketing is generally ineffective for general awareness building, primarily due to the higher per person cost versus broadcast campaigns that can reach more people many times. Therefore, marketers should resist creating awareness-building direct marketing programs to the general population, since they tend to yield a low response. A proven inhouse list of target customers is an ideal audience, since they are already familiar with the company and its products. A third-party list can be quite good, if the marketer understands their target audience clearly and if the third-party vendor has a reputation for providing high-quality names. However, a good customer list is only one step toward an improved response rate. Marketers must combine this with a relevant message and the best media to reach the target customer most effectively. The target audience names come from the marketer’s database, a third-party database, or a combination of the two. The numbers in the formula are derived from the marketer’s own statistics based on their specific direct-marketing objectives and activities. If the marketer’s goal was to generate 400 favorable responses from the

Impact  

10,000people reached in the initial target audience, then the 2% response in the above example is low. If the goal is a higher response rate, then marketers should use a reputable list comprised of either current or previous customers, or a list of customers who appear to fit the target audience profile.  i Arthur Middleton Hughes, What Is Your Customer Response Rate?, Database Marketing Institute, August 3, 2017. Retrieved August 3, 2017 from http://www.dbmarketing.com/articles/Art108.htm ; Dave Chaffey, Marketing Campaign Response Rates, Smart Insights, October 11, 2012. Retrieved May 7, 2017 from http://www.smartinsights.com/managing-digital-marketing/planningbudgeting/marketing-campaign-response-rates/; Lynda Partner, 62% Response Rate on Email Campaigns!!, MarketingProfs, March 1, 2001. Retrieved May 7, 2017 from http://www.marketingprofs.com/2/62percent.asp

Chapter 54 Conversion Rate Measurement Need To measure how many of the customers who responded to an ad or promotional offer convert to purchasing customers.

Solutioni The conversion rate is the percentage of prospective customers or visitors (to a website) who both respond and buy a company’s products and services. Cr =

Where

Pb Pr

Cr = conversion rate Pb = number of people who both respond and buy Pr = number of people who respond to your ad Measure 53 described the response rate and cautioned that customers who respond to a direct marketing campaign are not necessarily buyers yet. Continuing with Metric 53’s example, if 75 of the 200 responses actually buy the product, then the conversion rate is 37.5%: 75 200 = 37.5%

Cr =

Impact Without question, companies should strive for a higher conversion rate because it is an indication that their offering was attractive enough to attract a response and a purchase. Achieving a high conversion rate depends on many variables, including the relevance and appeal of the offer to the target customer, how easily accessible the offer is, the visual design, appropriate price, and how it compares to competing offers. With this list of qualifiers, it does appear to be a daunting task to develop a

  Chapter 54: Conversion Rate successful campaign. But that is the beauty of marketing—it is part art and part science. Marketers must be able to balance the quantitative performance demands with the qualitative aspects of sound judgment. Additionally, marketers must market their plans and ideas inside their own organizations if they want to achieve internal support and, consequently, deliver on the promises their programs make to the marketplace. Similar to the response rate’s limitations, the conversion rate is highest when the marketer is exceedingly clear in his objectives, target audience identification, and message design. An appropriately chosen direct marketing media is also important. To achieve high conversion and response rates, marketers must exercise surgical precision in their marketing efforts and resist the temptation to develop a one size fits all campaign. By using direct marketing for its intended purposes—to either build a relationship with loyal customers or general short-term increases in sales through promotional offers—the resulting rates will likely satisfy the marketing campaign objectives. The data for the number of people who actually buy will be captured in the company’s chart of accounts on a regular basis (daily if online, or weekly/monthly for other retailers). More specifically, it will be contained in the customer accounts summary (or its equivalent), in the sales department, customer service, or a similar ordertaking department. A sophisticated marketing operation will also keep track of customers who bought products as a result of any direct marketing campaign by putting a reference code in the campaign message asking consumers to mention the code to receive the special offer. Similar types of reference tags can be used to track response to specific campaigns.

 i Justin Driskill, What Is a Conversion Rate? The Online Advertising Guide, June 7, 2017. Retrieved June 22, 2017 from http://theonlineadvertisingguide.com/glossary/conversion-rate/

Chapter 55 Advertising-To-Sales Ratio Measurement Need Determining the return on the various programs marketing implements.

Solution The advertising-to-sales ratioi describes the effect of advertising on a company’s total sales. The formula is: ASR =

Where

Ea St

ASR = advertising-to-sales ratio Ea = total advertising expenditures St = total sales during time t To illustrate: Nikeii spent US$3.2 billion in advertising in 2016, with total global sales of $32.4 billion, so its advertising-to-sales ratio was:

$3,200,000,000 $32,400,000,000 = 9.9%

Impact Measuring how effective the advertising campaigns are at creating sales is a vital piece of information that marketers supply to support their marketing efforts. Advertising is used to build a company or product image, attract customers and, ultimately, generate, or certainly influence, an increase in sales. The amount spent on advertising will vary depending on the type of product, who the target audience is, the type of media used (online, print, broadcast), and the design and content of the message. Typically, a lower advertising-to-sales ratio is better than a higher one, since that implies the advertising was effective in convincing the target audience. As additional advertising-to-sales research shows, there are differences among industries, due to

  Chapter 55: Advertising-To-Sales Ratio the unique competitive characteristics of each industry. The auto industry, particularly in the United States, spends 1% to 2% of sales on advertising. While that is obviously a low percentage, it is often in conjunction with aggressive promotional programs at the dealer level. This can include reduced financing, discounted pricing, and gift giveaways or special upgrades for same day purchases, each serving as an inducement to purchase. Business products, such as enterprise hardware, are not advertised as much as consumer products. Marketers focus more on relationship development, value-added services such as additional hours of engineering support, and even user-group seminars to promote their products. Interestingly, Starbucks, the global coffee brand, is rarely, if ever, advertised. Instead, their stores serve as their primary marketing vehicle. Yet few would argue that they have been quite successful despite the absence of conventional advertising approaches. Total advertising expenditure and total sales will both be measured in the income statement. Sometimes income statements capture marketing expenses in one or two general categories. If so, then simply review the marketing department budget for the detail on total ad dollars spent. Updated industry ad-to-sales ratio data can be found in financial institution reports such as Dun & Bradstreet and ad industry reports from Ad Age.  i Advertising Age, Advertising to Sales Ratios by Industry, July 11, 2017. Retrieved July 14, 2017 from http://adage.com/article/datacenter/advertising-sales-ratios-industry/106575/ ii Sebastian Buck, Nike Spends Billions on Marketing, But Millennials Still Like Toms More, June 23, 2016. Fast Company Magazine. Retrieved May 14, 2017 from https://www.fastcompany.com/3061133/nike-spends-billions-on-marketing-but-millennials-stilllike-toms-more; News.nike.com, Nike, Inc. Reports Fiscal 2016 Fourth Quarter and Full Year Results, June 28, 2016. Retrieved May 14, 2016 from http://news.nike.com/news/nike-inc-reports-fiscal2016-fourth-quarter-and-full-year-results

Chapter 56 Promotion Profit Measurement Need Measuring the profit resulting from marketing’s promotional campaigns.

Solutioni The formula for promotion profit is: PP = {Uid × (Mr – D)} + {Ui × Mr} – {Ubd × D} – Cp + ( ± CE) Where PP = promotion profit Uid = incremental units sold on deal Mr = margin r D = discount Ui = undiscounted incremental units sold Ubd = base units sold on deal Cp = promo costs ± CE = positive versus negative carryover effects The first group of variables, {Uid × (Mr – D)}, measures the additional profit made from incremental sales due to the promotional discount. The second group, {Ui × Mr}, measures the incremental sales of units at the regular price. The third group, {Ubd × D}, measures baseline sales sold at the discounted price. The fourth variable, Cp, measures the cost of the promotion, and the final group, (± CE), measures the net value of any positive carryover effects over negative carryover effects. Carryover effects are the feelings consumers have from taking advantage of the deal, (fortunate versus skeptical, for example).

  Chapter 56 : Promotion Profit

Figure 55.1: The Effect of a Promotion Source: Grande, H., J. J. Inman, and P. Raghubir. “The Three Faces of Consumer Promotions.” California Management Review 46, no. 4 (Summer 2004): 32.

Figure 55.1 illustrates an increase of 100,000 units sold during the promotion period (assume one week). A total of 100,000 units were sold in each of the nonpromotion weeks. While the promotion increased units sold, the next step is determining if the promotion was profitable. The authors state that the face value of the promotion was $.50, versus the regular $.80 margin. Per the chart, incremental unit sales at the discounted price totaled 70,000 units, creating a $21,000 profit (70,000 units × $.30. Sales from baseline units sold on discount resulted in a $30,000 reduction below normal dollar volume since 60,000 units were sold at the promotion’s face value of $.50 (a loss since the baseline level of dollar sales without the discount would have been $.50 per unit higher). So, the promotion did not make an economic profit since the 70,000 units of incremental sales resulted in a $21,000 profit, yet the 60,000 units of baseline sales were at a $30,000 loss. Looking at the top bar of the chart during time period t, incremental unit sales at regular prices totaled 30,000, creating a $24,000 profit for those units (30,000 × $.80 {the full margin}). The end result is a $15,000 profit before promotion costs and any positive/negative carryover effects:

Impact  

PP = {70,000 × ($.80 – $.50)} + {30,000 × $.80} – {60,000 × $.50} – Cp + ( ± CE) PP = {70,000 × $.30} + $24,000 – $30,000 – Cp + ( ± CE) PP = $21,000 + $24,000 – $30,000 – Cp + ( ± CE) PP = $45,000 – $30,000 – Cp + ( ± CE) PP = $15,000 – Cp + ( ± CE)

Impact Marketing promotions are designed to increase sales over the duration of the promotion, with the hope that some of the customers acquired from the promotion become loyal over the long term. Since promotions convey special offers, such as limited time discounts, sales volume will increase, but margins on each product sold will decrease. According to an article from the California Management Review entitled “The Three Faces of Consumer Promotions,”ii the authors persuasively argue that promotions work in three ways: 1. Economic value: the value resulting from the discount; 2. Information content: the message implied by the discount. This can be positive or negative to the consumer. Perhaps a discount is seen as an offer to try a new product. Alternatively, the consumer may see the discount as a ruse to sell older or lower quality products; and 3. Affective appeal: feeling aroused by the discount. An interesting aspect to this analysis of promotions is the differences between incremental and baseline sales at both the discounted and regular prices. Promotions should generate additional sales volume, but the greater challenge is doing so profitably. The analysis indicates there is a baseline (or steady state) level of sales that occurs every week, irrespective of promotions. When a promotion runs, baseline sales are then divided into regular price sales and discount price sales, resulting in a loss over what would have occurred during a normal, nonpromotional cycle. Incremental sales can determine whether the promotion effects resulted in a profit or loss since they, too, are comprised of regular and discounted sales. Marketers must account for these different sales groups when planning promotions. If their planning indicates a positive outcome, as shown here, then the promotion can go forward. Actual results will inevitably differ from plan, so the marketer should review the actual promotion results with the same analytical rigor applied in the planning stages. Marketers will gain insight into the economic effects of promotions, while also gleaning some of the psychological impact, since the promotion alters buying patterns from baseline performance. The challenge is for marketers to gather information on sales performance trends, knowledge of their target customers, and their potential response to the promotion, and reasonable judgment about the after-effects of any

  Chapter 56 : Promotion Profit promotion. This analysis is a blend of art and science that is the core of marketing decision making. Data for promotion profit will usually be sourced in the sales tracking and financial summary reports (typically quarterly and annually).

 i H. Grande, J. J. Inman, and P. Raghubir, “The Three Faces of Consumer Promotions,” California Management Review 46, no. 4 (Summer 2004): 30–34. ii Priya Raghubir, J. Jeffrey Inman, and Hans Grande, “The Three Faces of Consumer Promotions,” California Management Review (Summer 2004): 23–42. Retrieved May 4, 2017 from http://cmr.berkeley.edu/search/articleDetail.aspx?article=5346

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Part 8: Direct Marketing Metrics Direct marketing describes the marketer’s efforts to directly reach the customer through direct marketing communications (direct mail, e-mail, social media, and similar “personalized” or one-on-one means). The direct marketing effort requires marketers to have a target list of customers that will each receive a marketing message tailored to their needs and interests. Tailoring these messages means that marketers either have well developed customer profiles, with information about the customer’s likelihood of accepting the marketer’s offer, or they have lists of customers whose general profile fits the marketer’s needs. Direct marketing messages are usually in the form of an appeal, promotion, or limited time offer, each designed to ask the customer to take action. The direct marketing metrics in this section help marketers assess the impact of their direct marketing efforts: 57. Direct marketing revenue goals 58. Direct marketing profit goals 59. Direct marketing gross profit 60. Direct marketing net profit 61. Direct marketing return on investment

DOI 10.1515/9781501507304-008

Chapter 57 Direct Marketing Revenue Goals Measurement Need Ascertain how many direct marketing communications must be sent to achieve the revenue goal for a direct marketing campaign.

Solutioni Direct mail revenue goals measure the effectiveness of the marketer’s direct marketing advertising by setting a revenue target, then determining the number of direct marketing pieces that need to be sent to achieve that target.

DM = Where

Rt Sa × Rr × Cr

DM = number of direct-marketing pieces Rt = revenue target Sa = average sale Rr = response rate Cr = conversion rate Let’s assume an online retailer sells auto supplies seeking revenue of $400,000 and its marketing team wants to know how many direct-marketing communications to send to achieve the revenue target. The marketers know from experience that out of 200 customers who buy from their site each day, 150 buy products. This yields a conversion rate of 75% (for more on this, see Chapter 54 about the conversion rate). Those who buy, spend an average of $300. The marketing team has done its homework on the industry and knows that the average response rate is 2% for direct-marketing campaigns promoting auto supplies: DM =

$400,000 $300 × .02 × .75

= 88,889 communications If this marketing team is creative, they might be able to create a message that is so compelling it increases the response rate to 5%. This improvement would decrease the number of marketing pieces needed to send to 35,555 pieces:

  Chapter 57: Direct Marketing Revenue Goals

DM =

$400,000 $300 × .05 × .75

= 35,555 pieces

Impact The benefit of direct marketing revenue goals is that they help marketers set specific revenue and resulting cost targets for a given campaign. In the case of the example used above, another benefit is that the retailer gains 1,333 new customers (88,889 × .02 × .75) who might develop long-term loyalty. While this particular campaign may produce the $400,000 revenue increase, the marketer is seeking to convert those buyers into loyal customers over the long term, and the marketer also has the potential to acquaint those who do not initially respond into future customers. Since they are now aware of the company and its products, they add to the retailer’s customer foundation and create, in effect, an ongoing customer revenue stream. These benefits are partly due to the effectiveness of direct mail as a marketing tool that generates a specific response from target customers based on crafting a relevant offer. Marketers can set a revenue target and can expect to generate measurable results tied specifically to the campaign. This degree of measurement precision is harder to achieve with general awareness marketing, like television or radio broadcast ads, because they are designed to develop an image rather than inspire a call to action for customers. Direct marketing revenue goals are a useful measure for specific campaigns, but ongoing success with this format requires marketers to have unique offers each time they are relevant to the target customer’s needs and are consistent with their company’s strategic objectives. Since direct marketing is often used for promotional offers, it is challenging for companies to regularly offer limited time period discounts without the risk of training their customers to always wait until the next price promotion. Furthermore, frequent promotions may erode brand value at both the product and corporate level if done too frequently. Direct marketing is also used to develop a one-to-one dialog with loyal customers, enabling marketers to tailor their messages accordingly. While customer loyalty is certainly an important goal for most companies and marketers, actually developing it requires more than setting revenue targets for specific loyalty-building campaigns. The message to loyal customers must resonate with them, suggesting to them that the company truly understands their needs and, perhaps even more important, that their continued loyalty is appreciated. As with many other marketing metrics, the measurement is the easy part. The development of the right strategy and campaign that yields the desired results is quite challenging, however. Marketers may be tempted to adjust the metrics in the formula to fit their revenue goals, irrespective of industry or competitor response and conversion rate averages.

Impact  

The challenge is remaining realistic about the expected performance of a campaign, since its success depends on many factors: the right target audience, a well-conceived campaign and message, imaginative creative design, a product that the customer wants, and, the right offer. These various criteria are critical components of the marketer’s overall plan. Yet even if these are each executed flawlessly, there is still the chance that the target audience will not respond as expected, since it is quite difficult to predict actual behavior. Therefore, marketers are encouraged to review past campaigns and those of competitors to determine the strengths and weaknesses of each marketing program. These statistics are found in specific reports within the marketer’s company. For example, revenue targets are usually established at the corporate level then translated into more specific targets for each product line or retail outlet. Average sales statistics will be based on company averages and, while possibly found in end of year financial statements, are more likely to be contained in the product line or per store profit and loss reports as a footnote measure. Chapters 53 and 54 provide guidance on the response rate and conversion rate statistics, respectively.  Philippe Graner, Data Drive: Planning for Profitability, Target Marketing, March 1, 2011. Retrieved May 3, 2017 from http://www.targetmarketingmag.com/article/determine-your-marketingcampaign-s-profit-generating-response-rate-breakeven-analysis-417197/all/; T. Egelhoff, “Direct Marketing: Why it Works and How to Use It,” Smalltownmarketing.com Retrieved May 16, 2017 from http://www.smalltownmarketing.com/formula.html i

Chapter 58 Direct Marketing Profit Goals Measurement Need When setting a direct marketing campaign profit goal, the marketing team must estimate the number of direct marketing communications to achieve the goal.

Solutioni The formula for direct marketing profit goals uses target profitability levels to determine the number of direct marketing communications. The formula is nearly identical to that for direct marketing revenue goals, except that the denominator includes the target profit percentage, as follows:

DM = Where

Rt Sa × P × Rr × Cr

DMPG = direct marketing profit goals Rt = revenue target Sa = average sale P = profit goal in percentage terms Rr = response rate Cr = close ratio Continuing with the example of our marketer selling automobile supplies from Chapter 57, let’s assume that her target profit margin is 30%. This factor is added to the formula as follows: DM =

$400,000 $300 × .30 × .02 × .75

= 296,296 direct marketing pieces The impact of this on the cost of the marketing campaign is significant. If, as we discussed in Chapter 57, the marketer was to create an offer that would yield a 5% response, then it reduces the size of the required marketing to 118,519 pieces to achieve the same profit target.

  Chapter 58: Direct Marketing Profit Goals

DM =

$400,000 $300 × .30 × .05 × .75

= 118,519 direct marketing pieces

Impact The benefits and risks are similar to those with direct marketing revenue goals. Whether or not a particular profit goal is feasible for a given business will be partly determined by a profitability analysis for its industry and a keen knowledge of the competitor dynamics. While a marketing campaign may generate revenue, the challenge is whether it is profitable. Marketers determine spending allocations based on overall company and marketing budgets. For a new product launch, a marketer may decide that revenue generation is more important than profitability, driven by the goal to develop awareness and share quickly. This may even be acceptable for several concurrent marketing programs within the context of an overall marketing plan, since a profitable performance for the entire company is generally more important than success with any specific product line. However, marketers must think carefully how to transition from revenue growth to profit growth as products mature and customers change. The direct marketing campaign should include profit targets as a result. The data for determining direct marketing profit goals will be based on performance tracking as captured by company sales and financial reports.  Philippe Graner, Data Drive: Planning for Profitability, Target Marketing, March 1, 2011. Retrieved May 3, 2017 from http://www.targetmarketingmag.com/article/determine-your-marketingcampaign-s-profit-generating-response-rate-breakeven-analysis-417197/all/; T. Egelhoff, “Direct Marketing: Why it Works and How to Use it,” Smalltownmarketing.com Retrieved May 16, 2017 from http://www.smalltownmarketing.com/formula.html i

Chapter 59 Direct Marketing Gross Profit Measurement Need To determine if a campaign of a certain size will produce a gross profit based on a specific number of marketing communications to be sent and response rates for their business.

Solutioni This calculation tells you whether your direct marketing campaign produces a positive gross profit: Pg = DM × P × Sa × Rr × Cr Where Pg = gross profit DM = number of direct marketing pieces P = profit goal in percentage terms Sa = average sale Rr = response rate Cr = conversion rate Using the example of the auto supplier, let’s plug in the numbers from Chapters 57 and 58: Pg = 88,889 × .30 × $300 × .02 × .75 = $120,000

Impact The marketing team’s gross profit looks healthy suggesting that they should go forward with the campaign. However, it would be smart for the team to check the net profit to ensure that this is the right move. This will be discussed in Chapter 60, Direct Marketing Net Profit. Positive gross profits are an important first step in determining the success of a direct marketing campaign. As with Chapters 57 and 58, data for direct marketing gross profit will come from a combination of internal reports from sales and finance.

  Chapter 59: Direct Marketing Gross Profit  Philippe Graner, Data Drive: Planning for Profitability, Target Marketing, March 1, 2011. Retrieved May 3, 2017 from http://www.targetmarketingmag.com/article/determine-your-marketingcampaign-s-profit-generating-response-rate-breakeven-analysis-417197/all/; T. Egelhoff, “Direct Marketing: Why it Works and How to Use it,” Smalltownmarketing.com Retrieved May 16, 2017 from http://www.smalltownmarketing.com/formula.html i

Chapter 60 Direct Marketing Net Profit Measurement Need Continuing our direct marketing measurement, the marketer needs to determine net profitability from the direct marketing campaign.

Solutioni Net profit is gross profit minus operating expenses. Calculating this helps determine if the direct marketing campaign produces a positive net profit. This is virtually identical to the formula for direct marketing gross profit, with one new component—operating expenses (cost of direct marketing campaign, in this case): Pg = DM × P × Sa × Rr × Cr – Cdm Where Pg = gross profit DM = number of direct marketing pieces P = profit goal in percentage terms Sa = average sale Rr = response rate Cr = conversion rate Cdm = cost of the direct marketing campaign Using the same numbers as above, let’s now include the cost of the direct marketing campaign. In this case, the auto supply marketing team outsourced the design and printing work, which cost them $8,000: Pg = 88,889 × .30 × $30 × .02 × .75 – $8,000 = $4,000

Impact The auto supply marketing team now knows that their campaign indicates they will produce a net profit. The point to this particular sequence is to demonstrate the various levels of analysis needed to determine the efficacy of a direct marketing campaign. Numerous factors are within the direct control of any company: goals, size of

  Chapter 60: Direct Marketing Net Profit marketing list, content of the offer, and industry metrics. The harder area to control is consumer behavior. There is no guarantee that, despite analytical rigor and an elegant business plan, customers will respond as hoped. But knowing this can help marketers develop a certain creativity and patience in their marketing efforts. Doing so will enable marketers to learn which activities work best as well as those that did not achieve objectives.  Philippe Graner, Data Drive: Planning for Profitability, Target Marketing, March 1, 2011. Retrieved May 3, 2017 from http://www.targetmarketingmag.com/article/determine-your-marketingcampaign-s-profit-generating-response-rate-breakeven-analysis-417197/all/; T. Egelhoff, “Direct Marketing: Why it Works and How to Use it,” Smalltownmarketing.com Retrieved May 16, 2017 from http://www.smalltownmarketing.com/formula.html i

Chapter 61 Direct Marketing Return On Investment Measurement Need As with many proposed expenditures, a company’s leaders want to know the return on investment (ROI) for a given project.

Solutioni Direct marketing ROI is the return on your direct marketing investment. ROI =

Where

(( DM × Rr × Cr × Sa ) − C ) C

DM = total number of direct marketing pieces sent Rr = response rate Cr = conversion rate of people who actually made a purchase Sa = average sales per purchase C = total cost of direct marketing campaign Let’s assume our auto supplier from Chapters 57–60 has decided to market premium luxury floor mats by sending direct marketing communications to 250,000 target customers at a total cost of $200,000. The marketer’s research indicates that specialty direct marketing campaigns such as this tend to get a very high response rate of 25%. Of the 250,000 people targeted, the marketer anticipates that 62,500 will respond. The auto supplier expects 10% of the respondents, 6,250 people, to convert to sales. Furthermore, based on previous direct marketing experience with similar floor mats, the average amount spent per customer is $200. The calculation is as follows:

ROI =

((250,000 × .25 × .10 × $100) − $200,000) $200,000

= 213% This campaign’s ROI is 213%, certainly a positive result.

  Chapter 61: Direct Marketing Return On Investment

Impact Direct marketing’s potential as a one-to-one marketing tool can be powerful, but years of “interruption” marketing have jaded consumers, resulting in marketing communications being ignored by the target audience before being read. Marketers know that response rates can make or break a marketing campaign, and to justify the risk to senior management, marketers need to measure the investment return. As with any ROI calculation, direct marketing ROI will provide marketers with an indication of the success of a particular investment. In this instance, we examined expected marketing, response, and conversion. The final test would be to revisit this ROI after the event and compare the projected and actual performance results. But from these preliminary forecasts, this campaign appears to be an attractive marketing opportunity. There are online ROI calculators that marketers can use specifically to assess direct marketing performance, including: – The American Marketing Association: https://www.ama.org/resources/MarketingToolkit/LeadGenerationAndAutomationEssentials/Pages/Marketing-Automation-ROI-Calculator.aspx – Brandwise: http://www.getbrandwise.com/dm_roi.html Marketingprofs.com: https://www.marketingprofs.com/Faqs/showfaq.asp?ID=137&CatID=10 Marketers do not have the luxury of telling their bosses to approve spending requests for marketing programs unless the program can demonstrate a reasonable ROI. Direct marketing ROI is a good tool to use to review the potential return of a future campaign. If there is previous history, then postcampaign actual numbers are useful as well. As with the marketing metrics concerned with direct marketing, the data for understanding ROI depends on the direct marketing list being used (in-house, third party, random), and the number of responses will usually depend on how many pieces are marketed and the offer described in the direct marketing piece. Also, the response and conversion rates depend on the promotional offer and, to a lesser extent, industry trends. In each case, these rates will vary, so marketers should know the benchmark metrics for their industry, and their company’s objectives, in advance. This knowledge will make it is easier to measure success once the campaign is under way.  MarketingProfs.com, Real-World Education for Modern Marketers, Retrieved May 2, 2017 from http://www.marketingprofs.com/Faqs/showfaq.asp?ID=137&CatID=10 i

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Part 9: Digital/Social Metrics Marketers are marketing through digital and social media, sending text messages to subscribers of services around the world. Since the mid-2000s, the growth of digital and social media, particularly companies like LinkedIn, Facebook, Twitter, and Google have gained sizable global audiences. Facebook alone has over 2 billion users, a staggering figure considering the company was founded in 2004. These new digital tools have created additional, powerful marketing opportunities for companies, effectively accelerating the shift in power from companies to individuals. The task for marketers is to effectively measure the results of their online/digital/social marketing efforts. The metrics in this section are: 62. Gross page impressions 63. Word of mouth 64. Total clicks 65. Click through rate 66. Cost per click 67. Cost per action 68. Pay per lead 69. Activity ratio for social media 70. Deductive social media return on investment 71. Resolution time 72. Social media profitability 73. Bounce rate 74. Return on advertising spend

DOI 10.1515/9781501507304-009

Chapter 62 Gross Page Impressions (Or Gross Page Requests) Measurement Need To measure website usage and frequency.

Solutioni Gross page impressions (GPI), or gross page requests, measures a website’s total traffic volume. It is the number of times any person has accessed a website, irrespective of repeat visits or unique visitors.

Impact GPI is useful information for starting an analysis of marketing vehicle usage as it will suggest to marketers whether their website is generating much interest from the market overall. However, it does not reveal any specifics about the users or their web surfing choices (web surfing describes a user’s online search across the Internet as they move from page to page and website to website). If marketers want more in-depth information, a third party market research firm, such as an audience measurement company, could assist. For example, marketers may want to determine the advertising potential for their website based on the traffic visiting it; using that data to sell the attractiveness to potential advertisers. GPI is a helpful measure to show potential advertisers the number of people visiting the website. Of course, many other variables will be important to advertisers, but GPI is a good starting point. Website traffic data can be collected from web server logs, which are software programs that automatically record each and every website visited.  MBASkool, Gross Impressions. Retrieved June 15, 2017 from http://www.mbaskool.com/business-concepts/marketing-and-strategy-terms/10689-grossimpressions.html 2; Laura Lake, Gross Impressions, TheBalance.com, June 11, 2017. Retrieved May 14, 2017 from https://www.thebalance.com/gross-impressions-explained-4043412; AdSpeed, Gross Impressions and Unique Impressions. Retrieved June 11, 2017 from https://www.adspeed.com/Knowledges/10/Ad-Metrics/Gross-Impression-Unique-Impression.html

i

Chapter 63 Word of Mouth Measurement Need To understand whether word of mouth (WOM) generated from social media activities is impacting business efforts.

Solutioni WOM = # of direct clicks + # of clicks from recommendations # of direct clicks Where

# of direct clicks is defined as any click that first connects to the site # of clicks from recommendations is defined as clicks from other links, such as other websites, ads, banners, social media recommendations, etc.

Example: Company X had 1,000,000 direct clicks and 1,380,000 indirect clicks in January. They wanted to determine the impact of WOM:

1,000,000 + 1,380,000 1,000,000 = 4.8 Each direct click influenced 4.8 additional clicks. In analog terms, this suggests one person told an average of 4.8 additional people about the product/service they purchased.

Impact WOM helps marketers evaluate the size of the audience that visits a website directly and indirectly. Digital usage footprint data is comprised of both direct and indirect clicks, the sum of which are then divided by direct clicks. This is akin to conventional

  Chapter 63: Word of Mouth WOM in which a consumer tells several other people about the product/service experience they had. It helps marketers assess the age-old business adage that the greatest testament to a company’s offerings is whether a customer would recommend it to another person. The company gains the sale directly from the customer, and also the potential to capture the other people the consumer contacted. The converse is true as well—individual negative consumer experiences can quickly escalate to a wider audience that sees the offering as negative, even without personal experience.

 i Mark Jeffrey, Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know (John Wiley & Sons, 2010), 181.

Chapter 64 Total Clicks Measurement Need The marketer’s use of social media has multiple objectives. A key goal is to determine whether the time and money invested in supporting the company’s social media efforts results in the members of its social media audience clicking onto their website.

Solutioni Total Clicks = WOM × Direct Clicks Where

WOM = word of mouth (based on Chapter 63 Direct clicks = only those clicks that are directly to the site; no referral clicks

Example: Continuing with the example from Chapter 63, the WOM of 4.8 is multiplied by the 1,000,000 direct clicks: WOM = 4.8 × 1,000,000 = 4,800,000

Impact Total clicks provide insight about the potential multiplier gained from WOM. The data is from the WOM metric multiplied by the direct clicks. Customers develop a sense of what doing business with a company is like during the process of buying the firm’s offerings. Marketers know that making the customer’s experience positive can encourage the customer to voluntarily share their positive experience with others. Total clicks helps marketers understand the impact that a single customer has on developing additional customer relationships.  i Mark Jeffrey, Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know (John Wiley & Sons, 2010), 185.

Chapter 65 Click Through Rate Measurement Need To determine if the online advertising is inspiring people to click through to the website.

Solutioni Click through rate (CTR) = Where

# of clicks # of impressions

# of clicks is defined as the total number of clicks to the site # of impressions describes the number of instances an online ad is shown

Example: Our online marketer has 480,000 total clicks. Her online ad has been delivered 1,000,000 times. The calculation is as follows: 4,800,000 = .032 150,000,000

The CTR is 3.2. For every 100 ad impressions, there were 3.2 click-throughs.

Impact The CTR measures how many customers click through on a link after viewing it. Digital usage footprint data is comprised of both direct and indirect clicks, the sum of which are then divided by direct clicks, which translates into a multiplier that indicates. CTR helps the marketer assess the frequency with which an online ad results in a visitor clicking through to the marketer’s offering. However, click-throughs do not necessarily mean the prospective customer will purchase, but it is a generally positive sign that the ad generated interest. CTR has decreased over the years, with average CTRs below 1%. While CTR is an important lead-in to a website, a more meaningful metric is conversion rate (Chapter 54), since it indicates the percentage of visitors that end up purchasing.

  Chapter 65: Click Through Rate  i Brad Geddes, “What Is a Good Click Through Rate?,” Certified Knowledge. Retrieved July 7, 2011 from http://certifiedknowledge.org/blog/what-is-a-good-click-through-rate/; Kristina Volovich, What’s a Good Click Through Rate? New Benchmark Data for Google AdWords, Hubspot, April 21, 2016. Retrieved June 3, 2017 from https://blog.hubspot.com/agency/google-adwords-benchmarkdata

Chapter 66 Cost Per Click Measurement Need To understand the cost per click (CPC) of the marketing programs designed to generate word of mouth (WOM).

Solutioni Two approaches to determine CPC will be discussed. Approach 1: Cost Per Click CPC is the price paid for an internet advertisement on a per click-through basis. Websites that offer online advertising have simple pricing structures. For example, consider a campaign where payment is based on the number of times a banner is clicked. Clicks are sold for $.10 per click. Hence, if there are a thousand clicks per week on the banner, the total amount payable to the website for that week would be $100. Approach 2: Cost Per Clickwom

Cost Per ClickWOM = Where

CPC WOM

CPC = cost per click WOM = word of mouth (based on Chapter 63) How: To determine CPC, the marketer divides the total cost of the online marketing campaign by the number of direct clicks. The result is then divided by the WOM calculation. Example: Let’s assume the campaign cost $50,000 and generated 100,000 direct clicks. Simply plug in the numbers as follows:

CPC =

$50,000 100,000

= .50

  Chapter 66: Cost Per Click From Chapter 63, we know that WOM = 4.8. Completing the calculation yields the following result:

.50 = .104 4.8 Therefore, the Cost Per Clickwom equals $0.104 or 10.4¢ When compared to the CPC of $0.50 or 50¢, the Cost Per Clickwom is cheaper on a per click basis, suggesting that the WOM campaign was cost effective.

Impact An important aspect of social media marketing is getting community members to share positive WOM that ultimately leads to clicks. This effort involves both financial and time investment. Each advertising media has different pricing and payment conventions. Print and broadcast advertising, for example, cost advertisers less as they buy more print ads or airtime. Payment is usually upfront, meaning that the advertisement will not be placed until the advertiser has paid the media vehicle in full for the use of that space. Web advertising is most often in the form of banners, interstitials and links (referenced in Chapter 53, Click-Through Rates). Marketers know how to measure the effectiveness of these ads using click-through rates, so now they must determine how to measure the cost of these ads. Generally speaking, advertisers must weigh costs with each media vehicle chosen. Online advertising is a simple approach, although the costs are not always obvious, since predicting the actual number of user click-throughs is difficult. Advertisers have faced the unfortunate side effect of competitors who repeatedly click the online ad, just to increase the cost. Since per click pricing is relatively cheaper, a competitor has to be devoted and persistent to drive up the costs. Fortunately, most online websites have software tools that can determine if click-throughs are following a repetitious pattern, so that advertisers don’t pay for these types of clicks. Marketers should ensure the website they have chosen has user statistics that provide guidance on the audience type. This helps marketers determine if the site reaches the desired audience. CPCwom estimates the CPC with WOM, showing marketers how much less per click it costs using WOM incentives than marketing designed to motive direct clicks from target customers, providing a clearer sense of the CPC for all clicks, direct and WOM. This helps determine if a WOM campaign is maximizing its potential. If the result of the calculation is less than 1, then the campaign is considered successful.

Impact 

3

 Mark Jeffrey, Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know (John Wiley & Sons 2010), 185; Word Stream, Cost Per Click (CPC): Learn What Cost Per Click Means for PPC. Retrieved May 2, 2017 from http://www.wordstream.com/cost-per-click; Chris Leone, What Is a Good Cost-Per-Click (CPC)? Webstrategies, May 24, 2016. Retrieved May 3, 2017 from https://www.webstrategiesinc.com/blog/what-is-a-good-cost-per-click-cpc i

Chapter 67 Cost Per Action Measurement Need To find out the cost of converting a prospect to a customer.

Solutioni Cost per action (CPA) is calculated by:

CPA = Where

C Cv

CPA = cost per action C = cost Cv = conversions If a marketing team invests $50,000 in a search engine optimization campaign and attracts 1,000 new customers as a result, then the CPA is $50: Vs =

$50,000 $1,000

= $50 As another example, let’s assume a company pays $.10 to a website for every completed transaction (and not per click) coming from a banner ad. If 1,000 people visit the website daily, 100 click on the banner and ten buy a product, then the cost of advertising on the website would be $1 per day ($.10 × 10 sales). CPA is paid once the target customer has completed the action desired, whether that is purchase and/or filling out a customer profile. In other words, CPA is based solely on specific results, such as sales or registrations that are converted from user clicks. The website owner takes most of the advertising risk since their commissions depend on good conversion rates that translate into sales.

  Chapter 67: Cost Per Action

Impact CPA campaigns are often lower cost since the actual costs are incurred only after the customer has completed the action. Data for CPA is found in the company sales reports and detailed financial statements and related advertising accounts. Cost per click (Chapter 66) charges per user click whether or not a paying transaction ultimately occurs. Senior management may find cost per click’s lack of a guaranteed transaction too imprecise to justify their advertising expenditure. For website owners, the decision to charge for completed transactions versus per clicks is a higher risk strategy, but it will also build confidence with customers because a CPA payment system suggests you are willing to support your website audience claims, since you receive no payment until a transaction is completed. For advertisers, a CPA approach will cost more per click since you are paying for a revenue-generating result. But your marketing and senior management will likely be happier since the cost is directly related to a positive financial result.

 i Matthew Goulart, 5 Critical Marketing Metrics to Follow, Entrepreneur, July 28, 2016. Retrieved May 3, 2017 from https://www.entrepreneur.com/article/278758; Jason Spooner, Why Cost Per Acquisition Is the Only Metric that Really Matters, Social Media Explorer, March 28, 2014. Retrieved May 30, 2017 from http://socialmediaexplorer.com/content-sections/tools-and-tips/why-cost-peracquisition-is-the-only-metric-that-really-matters/; Facebook, What Does Cost Per Action Mean? Retrieved May 30, 2017 from https://www.facebook.com/business/help/237396169733125

Chapter 68 Pay Per Lead Measurement Need Marketers obtaining customer leads online need a payment method for each lead acquired.

Solutioni Pay per lead simply describes an online payment method in which payment is based on actual, qualifying leads generated by a website or an advertisement on a website. Assume, for example, that your company attracts 10,000 visitors per day to its website, 1,000 of which click on a banner ad promoting the advertiser’s website and, of those, 100 register on the destination website. Then your company, as the publisher of the website on which the banner ad was placed, will be paid for the 100 leads that were generated.

Impact An advantage of website advertising is the measurement precision that allows marketers to know the details of their customers’ website behavior (their page selection, length of time on each page, links clicked, repeat visits, etc.). Qualified leads are any marketer’s desire, as long as the overall revenue generated from qualified leads that turn into sales is not exceeded by the cost. A sizable and growing challenge with online advertising is getting website visitors to pay attention to ads since, over the past several years, online advertising effectiveness has declined (although it can still be very cost effective compared to traditional advertising forms). As with any marketing communication, the key to success is identifying the right need, the right audience, the right message, and the right website. Even then, success is not guaranteed. For the website publisher, pay per lead is similar to cost per action, since customers of your site will have greater confidence if you charge them only for actual qualifying leads, based on actual registrations. These registrations are important to the advertiser since customers who register are giving their approval to be contacted in the future, qualifying them as viable prospects. Pay per lead can be unreliable due to the potential for fraud. Website publishers may generate false leads on the destination website through the use of programs called robots. Activity-based filtration (ABF) is a tool marketers can use that analyzes

  Chapter 68: Pay Per Lead website log files to identify activity suspected to be robot-generated. ABF should be conducted periodically to check questionable activity.  The Digital Marketing Reference, Pay Per Lead Definition. Retrieved May 4, 2017 from https://www.marketingterms.com/dictionary/pay_per_lead/; Emily Wubsauer, Why 2017 Is the Year of Pay Per Lead (PPL), Videodesign, January 24, 2017. Retrieved May 3, 2017 from https://www.vieodesign.com/blog/why-2017-is-the-year-of-pay-per-lead-ppl i

Chapter 69 Activity Ratio for Social Media Measurement Need Marketers need to measure the percentage of their customer base that is active at any one time.

Solutioni The Activity Ratio (AR) for social media is also known as “audience engagement” and/or “active advocates.” With a slight modification of terms, AR can also be used as a way to measure conversion. Active members All members Where Active members are defined as those who are AR =

regularly using and engaging with the marketer’s social media. All members are those people the marketer has attracted over time, including those who are inactive. Example: Our marketer has 100,000 active members out of 1,000,000 total members.

AR =

100,000 = .10 1,000,000

= .10 × 100 = 10% Therefore, 10% are active members.

Impact When customers purchase, the transaction suggests the customer was interested enough to buy the product at least once. Over time, the number of customers generally increases as the business grows, but not all customers remain active. This same logic applies to customer activity on a company’s social media sites, wherein marketers need to understand how many of their social media community members are active. Customer activity is usually a good indicator of the customers’ interest

  Chapter 69: Activity Ratio for Social Media level. This knowledge will help marketers find ways to ensure their social media remains relevant. AR helps marketers understand the level of activity from the members of their social media networks. The number of active members, as deduced from regular audits of the marketer’s social media applications, is divided by the total number of members the marketer has gained over time. The results are company-specific, due to the diverse marketing campaigns implemented by each company. Marketers must use reliable data to convince senior management that their social media efforts are creating an active online community that generates positive results for their company.

 Adapted from: Jeremiah Owyang, “Social Marketing Analytics Research Findings,” Web Strategy website, June 10, 2010. Retrieved September 3, 2011 from http://www.webstrategist.com/blog/2010/06/10/slides-and-recording-social-marketing-analytics-researchfindings/ Altimeter Group, 2010; http://socialtimes.com/social-media-metrics_b2950 i

Chapter 70 Deductive Social Media Return on Investment Measurement Need To assess if the social media efforts are yielding a positive return.

Solutioni The methodology is a sequence of succeeding measures, as illustrated by the example below. Marketing creates a social media campaign to emphasize a new promotion for its company’s product. The projected per unit profit is $35, and the cost of the social media campaign is $1,500. Twitter is used to send out ten tweets designed to inspire the target audience to visit the company’s website. Step 1: Determine the unduplicated audience reach of the ten tweets. In this example, we will assume 250,000 people are the target. Step 2: Estimate the percentage of the target audience that will actually see the tweet. In this instance, marketing knows from previous experience that 12% of the target audience will actually see the tweet: 250,000 × .12 = 30,000. Step 3: Estimate the percentage of those who saw the tweet that will find it compelling. Our marketer estimates this to be 10%: 30,000 × .10 = 3,000. Step 4: Estimate the percentage of those who find it compelling that will visit the site. In this example, marketing estimates 5% will visit the site: 3,000 × .20 = 600. Step 5: Estimate the percentage of those who visit the site that purchase. Marketing knows that the conversion rate is 15%: 600 × .20 = 120. We can now calculate the return on investment (ROI) for this social media campaign as follows: $35 profit × 120 purchasers = $4,200 – $1,500 = $2,700

$2,700 = 1.8 $1,500 1.8 × 100 = 180% ROI

  Chapter 70: Deductive Social Media Return on Investment

Impact Deductive Social Media ROI is useful in planning social media campaigns. Marketers will use data from previous campaigns to estimate the potential returns for a new social media effort. As this example illustrates, the ROI is based on the quality of the estimates made. 180% is certainly a positive ROI, but marketers must ensure their estimates are based on reasonable assumptions, which most likely result from past experiences and/or industry data. Data will be found from social media advertising kits, as well as marketing’s own research about customers and sales performance reports.

 i Don Bartholomew, “Social Media Measurement 2011: Five Things to Forget and Five Things to Learn,” MetricsMan. Retrieved September 23, 2011 from http://metricsman.wordpress.com/2010/12/30/social-media-measurement-2011-five-things-toforget-and-five-things-to-learn/

Chapter 71 Resolution Time Measurement Need Customers of social media are investing in faster response times due to the immediate, real time nature of social media dialogs and, therefore, need to evaluate how quickly customer inquiries are resolved.

Solutioni RT =

Total Inquiry Response Time Total # Service Inquiries

Where Total Inquiry Response Time is defined as the sum total of all response times the company had in a given time period. Total # Service Inquiries refers to all inquiries received in the same time period. Example: In one thirty-day period, our marketer’s company spent 6,000 minutes (or 100 hours) responding to customer inquiries. There were a total of 500 customer inquiries:

6,000 = 12 500 Therefore, each inquiry took an average of 12 minutes per response.

Impact Customers expect quick and efficient service that effectively solves their problem and measures how quickly organizations respond to inquiries made via social media channels. Unlike traditional customer service, social media users expect nearly instantaneous resolution from humans, not automated responses. Each firm has to determine a resolution time that is consistent with industry practice and, preferably, demonstrably better if it wants to distinguish itself from competitors.

  Chapter 71: Resolution Time Customer inquiries are usually tracked via customer software, recorded customer service conversations, and sales tracking systems that capture customer profiles.  Jeremiah Owyang, “Social Marketing Analytics Research Findings.” Web Strategy website, June 10, 2010. Retrieved September 3, 2011 from http://www.web-strategist.com/blog/2010/06/10/slidesand-recording-social-marketing-analytics-research-findings/ Altimeter Group, 2010. i

Chapter 72 Social Media Profitability Measurement Need Marketers need to evaluate whether their company’s social media efforts, such as blogging and tweeting, are producing profitable results.

Solutioni (R – Cg)*(F*Cr*Or*Pr) – h*T = Profit Where R = Revenue per sale Cg = Cost of goods per sale F = Number of followers/friends Cr = Click rate (% of followers that click on the marketer’s social media links and then go to their company’s site) Or = Opt-in rate (% of followers that opted to receive e-mail) Pr = Purchase rate (% of followers that opted also purchased) h = Hourly rate charged for marketer’s social media efforts T = Amount of time marketer spends on social media Example: The following assumptions are made: – R = $500 – Cg = $80 – F = 3,500 – Cr = 30% – Or = 5% – Pr = 30% – h = $65 – T = 60 hours In addition, the measurement period covers 30 days. The result is:

  Chapter 72: Social Media Profitability ($500 – $80)*(3,500*.30*.05*.30) – $65*60 = $2,715. Therefore, this social media campaign produced a $2,715 profit.

Impact The variables in this calculation are the key areas requiring a marketer’s attention since an improvement in each of the % rates improves the profitability. Marketers can then focus their efforts on how to improve the click, opt-in, and purchase rates individually by improving the design of each of those parts of their social media efforts. Data is found in financial, supplier, sales, and marketing media reports.

 Tyler Garns, “Social Media Money Formula,” Small Business Trends. Retrieved July 17, 2011 from http://smallbiztrends.com/2010/05/the-social-media-money-formula.html i

Chapter 73 Bounce Rate Measurement Need To determine the percentage of visitors that leave the website after visiting only one page.

Solutioni Bounce rate helps determine how effective the first page is at keeping visitor interest in continuing to search through the site. The formula for bounce rate is:

Rb = Where

Tv × 100 Te

Rb = bounce rate Tv = # of visitors that leave after viewing one page Te = total visitors to the page Websites live and die by their visitor traffic. If a website has 100 visitors that leave after viewing one page, or the first page they see, out of 150 total visitors to that page, then the bounce rate is:

100 × 100 120 = 83 + %

Sni =

A bounce rate of 83% is considered high and it suggests that the website has room for improvement to encourage visitors to spend more time looking thought the site, which will happen only if they believe the content within is useful.

Impact Bounce rate effectiveness is relative. If a website has a clear call to action that is desirable on one page, then there is no need for visitors to click past that first page.

  Chapter 73: Bounce Rate However, a content-laden website, such as an extensive product catalog, or a robust business information publishing site, is only as effective as the design of each page and the content within to capture the visitor’s imagination.ii Data for bounce rate is captured by web analytics tools that most Internet service providers have, as well as Google Analytics.iii  i Paul W. Farris, Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein, Marketing Metrics: The Definitive Guide to Measuring Marketing Performance (Upper Saddle River, NJ: Pearson Education, 2010). DeMers, Jayson. 10 Online Marketing Metrics You Need to be Measuring. August 15, 2014. Forbes. Retrieved May 27, 2017 from https://www.forbes.com/sites/jaysondemers/2014/08/15/10online-marketing-metrics-you-need-to-be-measuring/#3d3525fc76c1 ii Sam Kusinitz, How to Decrease Your Website’s Bounce Rate (Infographic), Hubspot.com. Retrieved May 12, 2017 from https://blog.hubspot.com/marketing/decrease-website-bounce-rateinfographic iii Google Analytics, Bounce Rate. Retrieved May 12, 2017 from https://support.google.com/analytics/answer/1009409?hl=en

Chapter 74 Return On Advertising Spend Measurement Need To measure how much profit is made from advertising.

Solutioni Return on advertising spend (ROAS) is calculated as follows:

ROAS = Where

A C

ROAS = return on advertising spend A = advertising revenue C = cost of advertising An ever-growing percentage of global advertising investments are in digital and social media. To attract customers through an online/digital campaign for their food delivery service, a Singapore company spent $12,000 on a Facebook promotional campaign that produced $18,000 in additional revenue, resulting in a $.50 ROAS: ROAS =

$18,000 − $12,000 $12,000

= $.50

Impact Return on advertising sales helps marketers decide if an advertising campaign is worth the investment. A positive ROAS would indicate success for the campaign. For those who are curious, ROAS differs from ROI. ROAS measures revenue generated over costs for the specific marketing campaign, whereas ROI measures profitability, which is typically the final financial outcome that most businesses care about. Both are useful and complement each other by providing deeper insight into the relative success of individual marketing campaigns and overall marketing investments.  Matthew Goulart, 5 Critical Marketing Metrics to Follow, Entrepreneur, July 28, 2016. Retrieved May 3, 2017 from https://www.entrepreneur.com/article/278758; BigCommerce, What Is ROAS?

i

  Chapter 74: Return On Advertising Spend  Calculating Return on Ad Spend. Retrieved June 18, 2017 from https://www.bigcommerce.com/ecommerce-answers/what-is-roas-calculating-return-on-adspend/; Laura Lake, What Is Return on Ad Spend (ROAS) and How Is it Calculated? The Balance, June 21, 2017. Retrieved June 24, 2017 from https://www.thebalance.com/roas-and-how-is-it-calculated2295469



Part 10: Place/Distribution Metrics “Place” refers to the marketer’s tools for determining how and where customers will purchase products, including channels, retail merchandise assortments and inventory, and distribution location. Place strategies have grown more sophisticated in today’s digital age, when customer demands have increased. The global market place has grown crowded, with competing brands and customer access to information (and products) via digital technology and the ubiquitous information on the internet. Place decisions are also expensive because of real estate costs, store design expenses, inventory fulfillment and warehousing requirements, supplier location and relationships, IT infrastructure needs, and competitors developing and improving their own retail operations as well. Place issues are further complicated by the fragmentation of markets and segments. Sophisticated retailers like Amazon, Alibaba, Apple Stores, Carrefour, Crate and Barrel, IKEA, Pottery Barn, and Costco, for example, have discovered that customers at all levels shop in their stores and online, depending on their needs. IKEA offers affordable furnishings to budget customers, yet IKEA appeals to upscale customers as well, due in part to the innovative designs, unique store layouts, and vast selection. Whether the place strategy focuses on a discount store or an exclusive, upscale environment, customers expect the merchandise to be high quality (even in discount stores), the service to be helpful, the merchandise thoughtfully displayed, and the shopping environment to be friendly. In short, creating experiences for customers that go beyond the purchase of a product and include the development of an emotional attachment have become the new normal in today’s retail world.

DOI 10.1515/9781501507304-010

  Part 10: Place/Distribution Metrics The place/distribution measures described in this book help store management assess performance results of their operations. They are: 75. Cost per sales dollar 76. Transactions per customer 77. Transactions per hour 78. Average transaction size 79. Average items per transaction 80. Hourly customer traffic 81. Returns to net sales 82. Inventory turnover 83. Percent inventory carrying costs 84. Gross margin return on inventory investment 85. Sales per square foot 86. Sales/profits per employee 87. Retail close ratio 88. Retail margin percentage 89. Percent utilization of discounts 90. Shrinkage to net sales

Chapter 75 Cost Per Sales Dollar Measurement Need To measure the cost per sales dollar of each credit sale.

Solutioni Cost per sales dollar is measured as follows:

CSD = Where

Coi Sci

CSD = cost per sales dollar Coi = total departmental operating costs in period i Sci = total credit sales in period i To illustrate, let’s assume that a food supplier receives an order from a grocery customer for five cases of canned peaches. The supplier sends the five cases to the retailer, along with a bill with net thirty terms (meaning that the retailer must pay the bill within thirty days or an interest penalty will be charged in addition to the principal amount owed). If the retailer does not pay, then the supplier incurs collection costs from the effort to retrieve payment, ranging from a simple letter (the cost of the labor, letterhead, and postage) to the retention of a collection agency at a substantially higher cost. In a oneyear period, the departmental operating costs incurred to collect credit sales can be significant. Total departmental operating costs are the sum of annual fixed and annual variable costs. In our example, the supplier’s costs are as follows: Annual Fixed Cost = $80,000 Annual Variable Cost = $70,000 Therefore, total departmental operating cost are $150,000. If the annual revenue expected by the food supplier is $200,000, then we can calculate the cost per sales dollar:

Csd =

$150,000 $200,000

= $.75 It costs our food supplier $.75 per dollar of credit sales generated.

  Chapter 75: Cost Per Sales Dollar

Impact Credit sales occur both online and at the retail level. Since credit purchases are cashless, mechanisms exist to verify that the buyer has the funds (known as a credit limit) and that the seller can accept the electronic funds transfer once the transaction is approved. The benefit to sellers is that credit transactions are credited directly into their bank accounts once the buyer is approved. However, this costs the seller processing fees since the credit issuers charge sellers for the convenience and security of electronic transactions. Another form of credit sales is the individual account established between sellers and buyers whereby sellers provide buyers a specific credit limit that allows the buyers to acquire products now and pay for them in the future, based on a regular billing cycle (usually monthly). Credit sales can turn into bad debt if a buyer does not pay their bills, costing the sellers a collection fee, which raises the cost per sale. Marketers want to minimize the costs per sales dollar for a simple reason: profits improve as the costs decline. A high cost per sales dollar may not necessarily be cause for alarm, however. Industry practices may impose a higher cost structure, so your company should compare its costs to those of the competition to determine if the result is within reason for the industry. However, marketers would be well-served by understanding the sources of the higher costs before concluding that it is acceptable to be at cost parity with the competition. Perhaps the industry is in decline and arcane practices need to be phased out. The sources of the costs are more than the processing and collection fees. Marketers must step back and review the entire customer selection process. High costs may indicate changing segment and customer needs. High costs may also suggest that a more effective customer audit process is needed to determine whether the highest quality customers pay on time versus those who are regularly late. Even marketing’s communication efforts may need revamping since high costs may signal that customers are not clear about payment terms. Higher costs could also result from mislabeled or inaccurate billing, perhaps resulting from hastily prepared invoices or unclear writing from the salesperson. Finally, high costs may also indicate unevenly enforced policies, allowing customers to infer that the supplier is relaxed about payment terms. Each of these scenarios suggests potential problems, even if the industry norm indicates otherwise.

 i Rob Olsen, Performance Measures for Credit, Collections and Receivable, CRFonline. Retrieved May 10, 2017 from http://www.crfonline.org/orc/ca/ca-7.html; Victor Cook, Cost Per Dollar of Sales— Gerstner’s Rule, Customers and Capital, May 11, 2007. Retrieved May 29, 2017 from http://www.customersandcapital.com/book/cost_per_dollar_of_sales/

Chapter 76 Transactions Per Customer Measurement Need To determine how many in-store potential customers convert to actual buying customers.

Solutioni Transactions per customer (TPC) measures the percentage of potential customers that actually buy. The formula is: TPC = Ttranst × 100 Ttrafft

Where TPC = transactions per customer Ttranst = total number of transactions in time period t (usually one day) Ttrafft = total customer traffic in time period t For example, if you run a retail outlet and a particular day has customer traffic of 1,000 people, and the total transactions for that day is 100, then the TPC is 10%:

TPC =

100 × 100 1,000

= 10%

Impact TPC is a measure of a retailer’s success in converting potential customers into actual buyers. Alternative terms are the “percentage yield rate” and/or the “walk to buy ratio,” but each measures the same thing. Generally, the higher the percentage, the more effective the retailer is at converting those who are merely browsing into paying customers. If the figure is low, then the retailer may need to review its marketing activities, including:

  Chapter 76: Transactions Per Customer – – – –

Promotions (the discounts are not attractive enough or the wrong products are being promoted) Point of purchase materials (stocking may be low, the display may be poorly placed, or the design may be unappealing) Merchandising (the look of the products on stores shelves and their location in the store may not appeal to customers or reflect how they walk through the store) General marketing activities (awareness-building brand development activities may not be consistently executed, print ads for specific products may be confusing or poorly executed, and the store location may be inconvenient).

The biggest challenge is measuring customer traffic since it is difficult to actually measure each individual potential customer unless a specific person(s) is devoted to counting customers for a given period of time, or a third party research firm is retained to conduct a customer count survey. There are automated tools that can count customer traffic as well, although these do not account for double counting (customers who visit more than once in the time period measured). Finally, transactions are recorded on the digital payment systems (or similar electronic hardware and software) so these totals are more easily gathered than the customer traffic totals.  Wayne Patten, The Growth Equation—Increasing the Number of Transactions Per Customer, LinkedIn, March 18, 2016. Retrieved June 3, 2017 from https://www.linkedin.com/pulse/growthequation-increasing-number-transactions-per-customer-patten i

Chapter 77 Transactions Per Hour Measurement Need Retailers need to know the transaction pattern to determine the best possible combination of these activities.

Solutioni Transactions per hour (TPH), or any chosen period of time, calculates the number of transactions that occur during that time, and is represented by:

TPH = Where

Ttranst Tht

TPH = transactions per hour Ttranst = total transactions in time period t Tht = total hours in time period t Let’s assume a store sells books and the owners wish to measure TPH. The store is open from 8 a.m. to 9 p.m. every day. Ownership decides to review an entire week’s activity to determine TPH. During the week being reviewed, 1,600 transactions occur. We can now calculate TPH:

1,600 91 = 17.6

TPH =

17.6 transactions occurred in the average hour during the week being measured.

Impact Retailers juggle multiple responsibilities, including setting employee work schedules, buying the product mix, setting retail prices, product placement and merchandising, and scheduling hours of operation. TPH provides retailers with the flow of business, helping them understand peak times when customer demand is highest. For example, retailers can review transactions in each actual hour to determine which times of day are busiest. This information will enable the retailer to schedule the right

  Chapter 77: Transactions Per Hour number of employees during the busiest times. Equally important, this information will help a retailer determine the best times to run promotions as well, since they would want promotions to be seen by the largest possible number of customers, so as to maximize sales.  Matt Phillips, Starbucks Is Now Selling 46% More Things Per Hour Than it Was Five Years Ago. Quartz, November 22, 2013. Retrieved June 2, 2017 from https://qz.com/149995/starbucks-is-nowselling-46-more-things-an-hour-than-it-was-five-years-ago/ i

Chapter 78 Average Transaction Size Measurement Need Retail management wants to measure the average value of each transaction.

Solutioni This measures the average financial value, in dollars (or whichever currency being used), of each transaction/sale:

Ta = Where

St Ti

Ta = average transaction size St = total dollar value of sales in time t Tt = total number of transactions in time t Let’s assume a retail store generates $1 million in sales annually, and the total number of transactions is 50,000. Then the average transaction size is $20 per transaction:

Ta =

$1,000,000 50,000

= $20

Impact Average transaction size is an important metric because it can help retailers measure their success in making increasingly larger sales from each customer. An important concept to understand in the preceding sentence is “increasingly larger sales.” Ideally, the average transaction size should always be increasing since it strongly suggests that the retailer is having not just continued, but increasing success in selling products to its customers. Retail managers and marketers want to know how much the average customer spends per transaction so that they can develop strategies and programs to cost effectively improve the sales amount. Often, this is a matter of persuading customers who are already committed to buying, to buy more. Ideally, retailers want to see the average transaction size increase year after year because this measures their productivity, their

  Chapter 78: Average Transaction Size success at selling products, and their ability to regularly attract customers. Furthermore, the transaction size can be an indicator of the types of items that sell well versus those that do not. It may suggest the profile of their average customer, even by time of day. By understanding this, retailers can also develop a plan that improves their merchandise mix and, over the long term, more effective in-store product arrangements, point-of-purchase displays, and the general attractiveness of the store layout. Marketers and retail store managers can find the average transaction size a useful indicator of shopping patterns at different times of the day. Savvy retailers will use this information to vary the in-store promotions throughout the day, creatively combining promotions for short durations, knowing that customers buy particular combinations of products and, with proper incentive, may be inspired to add to their purchase if the item is relevant to their profile. Technological innovations and pricing algorithms have led to even more sophisticated ways for studious retailers to maximize the average transaction value. These sophisticated software advancements gather detailed, minute-by-minute data of purchase patterns per individual buyer, allowing for greater understanding of the choices customers make throughout the day. Marketers must be careful to consider the meaning of the average transaction value before reaching conclusions. For example, purchase patterns for cold medicine may increase sharply for a brief period of time when a promotion for that product is run. However, the medicine may have been purchased due to the imminent need by the customer for the product, irrespective of the price promotion. In this instance, the marketer will have effectively decreased the product’s margin when the sale would have occurred anyway. Therefore, marketers must exercise sound judgment in determining the reasons behind changes in average transaction value. The temptation is to infer behavior when the reality is that behavior is very hard to glean from transaction statistics. Depending on the retailer and the sophistication of their IT systems or the discipline of store management, this data is captured every day. Well-run retailers do their end-of-day totals to review the day’s performance and to close the books so that the next day can be measured anew. Point-of-purchase systems will usually measure each transaction individually, by item and selling price. Even manual systems record each sale so, either way, the information should be captured at the store level.  Splitit, What Is Average Transaction Value (ATV), and Why Is it Important? N.D. Retrieved May 14, 2017 from https://www.splitit.com/2015/06/what-is-average-transaction-value-atv-and-why-is-itimportant/; Wayne Patten, Average Transaction Value, PJT Accountants, January 17, 2013. Retrieved May 24, 2017 from http://blog.pjtaccountants.com.au/average-transaction-value-and-number-oftransactions i

Chapter 79 Avergage Items Per Transaction Measurement Need Retailers need to know the typical transaction profile, including the number and types of items purchased, the average transactions value, and even the time of day. Knowing the average number of items per transaction reveals to the retailer part of the customer’s preferences, even if the customer’s expanded profile is unknown (age, income, behavior).

Solutioni Average items per transaction is a simple formula, represented by:

Savg = Where

S T

Savg = average number of items sold per transaction S = total number of items sold T = total number of transactions Let’s assume a traditional convenience store in the United States, which is about 2,500 square feet in size and offers 500 SKUs (stock keeping units), sells 200 items and averages fifty transactions per day. We calculate the average number of items per transaction as follows:

200 50 =4

Savg =

The same formula would apply to online retailers as well.

Impact In absolute terms, the metric merely measures the average quantity of items purchased. But this data can also provide insight into the basic purchase patterns of their average customer. Depending on the number of items purchased and any increases

  Chapter 79: Avergage Items Per Transaction over time, this metric may suggest to a traditional retailer’s management that customers find their merchandise mix and store layout attractive, thereby inspiring additional purchases. Of course, the opposite is true as well. It is also conceivable that some customers prefer to buy items related to a specific category (known as item affinity, which refers to the similarity or “complementarity” between items). A clever retailer will want to understand the mix of items in each transaction to see if there are interesting patterns or trends to be exploited. But because the metric only measures average items per transaction at the time of sale, the traditional retailer cannot determine which aisles the customers merely visited without purchasing representative products, how long the customer was in the store, or where the customer went afterward. They can only speculate. However, if a marketer ran a price promotion campaign for a limited period of time and sales increased during that time, it would be reasonable to infer that the promotion affected the sales increase. The advantage online retailers have is due partly to the unique software tools (usually called web analytics or, simply, analytics software) available to measure Internet activity. Online marketers will find that analytics programs offer more precision in understanding the activities a customer undertook before and after purchase, which can be useful in developing future promotions, marketing programs, and merchandise selections. There are software tools for online marketers that “learn” from prior visits from customers. These tools, known as affinity engines or personalization servers, are designed to provide online customers with suggestions of other products the customer might find interesting based on the items they are reviewing while on the Internet. Amazon.com, among many online retailers, illustrates this. Whenever a customer visits Amazon, their selections are remembered and, when they visit again, Amazon greets them with a simple reminder of what they purchased (or even merely browsed) before, recommending similar or related items the customer ought to consider. There is a great deal of programming complexity (called business rules) involved in this seemingly simple activity, but it is a capability that is growing in sophistication and can result in a positive online shopping experience. Marketers, of course, gain important advantages with web analytics, personalization, and affinity engines since it improves the potential for increasing the number of items per transaction. Marketers may be tempted to overinterpret behavior based on information resulting from this metric. Marketers should be wary of speculating about the reasons behind the actual items per transaction since many factors can affect a consumer’s purchase decision. Certainly, price promotions can induce additional purchases of a product beyond a normal selling volume. But it is conceivable that spontaneous decision making may also be a factor. The key takeaway is that pinpointing the reasons behind the purchase decision are hard to glean without a direct and immediate survey of a large sample of customers. The knowledge gained from such a survey can be useful, but it can be expensive and time consuming as well.

Impact  

Most traditional retailers capture daily sales totals at the end of each business day. These are increasingly tracked via computerized systems, known as point-ofpurchase systems. Assuming the retailer has an automated point-of-purchase system, the transaction data are captured with every customer sale, typically from electronic barcode scanning. The data usually include item description, quantity, price, and any promotional discounts. Each transaction also logs the time of day, which is useful in identifying shopping patterns. Online retailers have software programs that automatically track each transaction, plus provide data on customer clicking patterns. Analytics programs have been developed that can measure not just the actual item-specific sales activity, but the cross-selling factors that may have influenced the customer’s final decision. For example, before a customer buys a product online, other web pages may have been viewed that influenced the customer’s final decision. After the transaction is completed, the analytics programs can provide data on which web pages the customer visited next.  Klipfolio, Units Per Transaction, N.D. Retrieved June 2, 2017 from https://www.klipfolio.com/resources/kpi-examples/supply-chain/units-per-transaction i

Chapter 80 Hourly Customer Traffic Measurement Need Retailers seek to measure total customer traffic during a specific period of time.

Solutioni HCT = Where

Ttrafft Tht

HCT = hourly customer traffic Ttrafft = total customer traffic in time period t Tht = total hours in time period t If a retailer has 1,000 customers during a ten-hour day, then the hourly customer traffic (HCT) is 100:

1,000 100 = 100

HCT =

Impact Similar to Chapter 76 (Transactions Per Hour), retailers use HCT information to determine employee scheduling, store hours, and even price promotions. The busiest hours warrant the highest staffing levels and may be an opportune time to run a promotion to maximize sales. HCT is different from transactions per hour in one key respect: HCT measures all customer traffic, not just paying customers. Retailers will need more staff during higher customer traffic periods to answer customer questions and handle point-of-sales cash transactions. Peak customer traffic times are a great opportunity for retailers to focus on improved service since many of those who are merely browsing may return in the future to purchase if their initial service experience was positive. Data for HCT is tracked through in-store transactions on the payment system software.

  Chapter 80: Hourly Customer Traffic  Opentracker.com, Hourly Trends, N.D. Retrieved May 4, 2017 from https://www.opentracker.net/docs/reports/traffic-trends-behavior/hourly-trends; Google Analytics Help, View Hourly, Daily, Weekly, or Monthly Data, N.D. Retrieved May 4, 2017 from https://support.google.com/analytics/answer/1010054?hl=en i

Chapter 81 Returns to Net Sales Measurement Need To measure returns from customer sales, which indicates rates of customer satisfaction/dissatisfaction.

Solutioni Returns to net sales (RTN) measures the value of products that are returned relative to net sales:

RTS = Where

Trat × 100 Snt

RTS = returns to net sales Trat = total $ returns and allowances in time period t Snt = net $ sales in time period t To illustrate, a retailer has total returns and allowances of $30,000 in a one-month period. During the same period, net sales are $1,000,000. RTS equals 3%: = RTS

$30,000 × 100 $1,000,000

= 3%

Impact A higher figure suggests that the retailer may have problems related to the quality of the products and/or a below average service experience. Retailers want the lowest possible RTS figure, since returned products or allowances cost them money as well as harm their reputation.  i Mike Kappel, How to Find Net Sales—Formula and Examples, Patriot Software, October. 15, 2015. Retrieved May 17, 2017 from https://www.patriotsoftware.com/accounting/training/blog/net-salesexplained/

Chapter 82 Inventory Turnover Measurement Need To understand how quickly inventory is being sold (as it is one indicator of the popularity of the product).

Solutioni Turnover measures how quickly total inventory is sold and refilled during a given period of time. It is calculated as follows:

Turnover = Where

S Ia

S = sales Ia = average inventory Note: Average inventory is usually calculated as the sum of each month’s beginning-of-month inventory figures (12 in all) plus the last end-of-month inventory amount, divided by 13.

Suppose a retailer has twenty outlets and its sales last year were $80 million. The average inventory each month was $8 million. The turnover, then, equals ten, as follows: Turnover =

$80,000,000 $8,000,000

= 10

Impact In consumer products and retail companies, the marketing effort often includes planning product inventory levels based on forecasts from field sales teams, buyers, and internal projections derived from past experience and current conditions. Unless a company is facing rapidly escalating supply prices, then the business leaders will want to sell off their inventory quickly (a high turnover) to keep their storage, tracking, personnel, and warehouse costs down. High inventory levels do occur when

  Chapter 82: Inventory Turnover prices are rising quickly because companies want to stock up on the supplies before the prices rise further. Turnover is a key measure of retail productivity. In effect, turnover is measuring the velocity of inventory change and, since inventory represents money (invested) sitting in a warehouse, the sooner it is sold, the sooner the investment earns returns. Therefore, a high inventory turnover is generally a good sign. For example, retailers selling perishable goods such as food will have higher inventory turnover than those with nonperishable goods, since spoilage is a real risk. However, durable goods are also important to turn over quickly since they generate revenues that can be put to use in newer inventory and for other productive purposes. A low turnover rate may imply several problems, including poor sales (perhaps from insufficient marketing), underperforming or outdated products, or consumers who have grown weary of the product or category. Poor sales, of course, leads to increasing inventories, which can put pressure on the retailer since the investment in inventory is not producing any return (see Chapter 84 on Gross Margin Return on Inventory Invested for more insight on this). Conversely, a high turnover rate may suggest strong sales performance due to uniquely relevant products that satisfy growing consumer needs. Interestingly, a high inventory turnover may also signal ineffective buying from suppliers, leading a retailer to not having enough inventory to replenish depleted stocks (a concept known as the fill rate). Newer products tend to attract attention and increase purchase frequency, slowing as consumer familiarity and competition grows. Also, expanding retail chains will witness increasing inventories, which will distort the inventory turnover patterns until the new stores gain a consistent operating performance. Clearly, there are many factors that influence inventory turnover. It is the responsibility of marketers to attract as many consumers as possible, then convert them to buyers so that retail inventories are kept to a manageable level consistent with the particular industry in which their company competes. As referenced periodically in this book, this is accomplished through the marketing mix of product (the right product for the consumer), place (accessibility of products for consumers), promotion (communication that appeals to the consumer), and price (the equivalent of the consumer’s cost, which is influenced by perceptions of quality and uniqueness, among many factors). Marketers must pay attention to each of these marketing “levers” to see which ones stimulate consumer purchases most effectively, and maximize profitable sales as a result. Data for inventory turnover is based on actual production and finished goods reports that are found in sales, finance, and marketing.  i Ryan C. Fuhrmann, How Do I Calculate the Inventory Turnover Ratio? Investopedia, November 7, 2016. Retrieved May 30, 2017 from http://www.investopedia.com/ask/answers/070914/how-do-icalculate-inventory-turnover-ratio.asp; Accounting Tools, Inventory Turnover Formula, May 16, 2017. Retrieved May 30, 2017 from https://www.accountingtools.com/articles/2017/5/16/inventoryturnover-formula

Chapter 83 Percent Inventory Carrying Costs Measurement Need To determine the percentage of net sales attributed to the carrying costs of managing the unsold inventory.

Solutioni Percent inventory carrying costs (PICC) is calculated with the following formula: PICC =

Where

Icc × 100 Snt

PICC = percent inventory carrying costs Icct = inventory carrying costs in time period t Snt = net $ sales in time period t If your company is a computer retailer with net sales of $1,000,000 during the month, and your inventory carrying costs were $300,000, then your PICC is 30%: = PICC

$300,000 × 100 $1,000,000

= 30% Certainly, the lower the PICC, the better your financial bottom line, since carrying costs eat into margins and reduce profitability.

Impact Retailers regularly adjust inventory levels to service depleted store stocks and not overly burden their storage and warehouse facilities with unsold inventory. Inventory residing in storage incurs carrying costs, which are the costs associated with leasing storage space, insuring the unsold inventory, moving inventory to new locations, shrinkage, and the labor used to periodically count each item. Retailers face a daily cost challenge due to labor, shrinkage, facilities maintenance, insurance, rent, and product returns. Keeping inventory levels as low as possible while still being able to effectively replenish in-store stocks is a constant management task. Consequently,

  Chapter 83: Percent Inventory Carrying Costs the best retailers pay close attention to product and purchase patterns, facilitating a more efficient and effective inventory management system that, ultimately, will help reduce costs and improve profitability. Data for inventory turnover is based on actual production and finished goods reports that are found in sales, finance, and marketing.

 James Wilkinson, Inventory Cost, The Strategic CFO, July 24, 2013. Retrieved June 6, 2017 from https://strategiccfo.com/inventory-cost/; Dan Kiefer, The Million Dollar Question—The True Cost of Carrying Inventory, N.D. Retrieved May 22, 2017 from http://k3s.com/wpcontent/uploads/2012/05/True-cost-of-carrying-inventory.pdf; Accounting Coach, How Do You Calculate the Cost of Carrying Inventory? N.D. Retrieved May 23, 2017 from https://www.accountingcoach.com/blog/calculate-inventory-carrying-cost i

Chapter 84 Gross Margin Return on Inventory Investment Measurement Need To measure the products with the highest return on inventory investment.

Solutioni Gross margin return on inventory investment (GMROII) measures how successfully a retailer has invested its money used for inventory. More simply, it is a measure of an item’s gross profitability. It is calculated using this formula:

GMROII = Where

M Cai

GMROII = gross margin return on inventory investment M = gross margin dollars Cai = average inventory costs in dollars Let’s assume that a sporting goods retail chain is earning gross margins of $3 million. Average inventory at cost is $1 million. Therefore, the GMROII is $3: GMROII =

$3,000,000 $1,000,000

= $3 This means that the retailer is making a very healthy 300% gross margin on their originally $1 million inventory investment.

Impact A key source of profits is the investment in inventory. Retail managers want to invest in those products that yield the highest potential return on the amount invested. Retail marketers are interested in this as well since the characteristics of the products in inventory have a direct influence on price, merchandising and, ultimately, marketability. If a retailer’s merchandise is more favorably received by customers and can earn a higher profit as well, then their decisions will also favor the products offering

  Chapter 84: Gross Margin Return on Inventory Investment the highest investment return potential. GMROII is a measure of the productivity of a company’s inventory investment. It helps describe the relationship between key retail performance measures: total sales, the gross profit margin earned on sales, and the number of dollars invested in inventory. In this example, $1 of investment earned $3 in return. Another way to explain this is that GMROII tells managers how much they have earned back on their original inventory investment during one year. GMROII is also a useful measure because it applies to any merchandise within the retailer’s business. Furthermore, it is a viable management tool for employee performance, especially those responsible for selling. Goals for gross margin, sales targets, and team rewards for high-performing departments can all be tied to GMROII, serving as an incentive for employees to focus on the factors that improve this metric. Marketers are advised to take note as well, since the promotional activities they create to attract buyers will have a direct impact on GMROII. Each retailer’s unique mix of business activities affects how marketers develop programs (promotions, pricing, message, point of purchase) to attract customers while also maximizing GMROII. Marketers are keen to satisfy customers and want to know that their customers are receiving what they expect when they expect it—not just that an order left their warehouse on time. However, GMROII poses some challenges for retailers. For example, retail businesses also measure operational efficiency based on the fill rate, which effectively measures the amount of stock available to fill a particular order. If a customer order requires 100 items and the retailer’s available stock allows it to ship ninety-five items, then the fill rate is 95%. Management efficiency would suggest that filling close to 100% of the order is important, both for customer satisfaction and for reputation development for the retailer. A high GMROII may indicate a low fill rate, meaning that the retailer has low inventory (perhaps related to high inventory turnover, which could indicate that the dollars invested in inventory are turned into profitable sales) and cannot fill the full order. Increasing the fill rate would compel the retailer to invest more money in advance to increase inventory (and hopefully improve future fill rates, which would satisfy customers) before turning that investment into profitable sales. Yet the return on the inventory investment would be low until sales occur to reduce the inventory. What is the right fill rate and GMROII? Each retailer must make that decision based on their business needs, operating model, and customer expectations of service, among many considerations. Furthermore, while GMROII may be high, it could be at the expense of shipping the wrong product, the wrong quantities (as referenced above), or using the wrong transportation logistics (which might affect delivery date and final customer price). A low GMROII may result from a different set of factors. Discounts and dating (special terms offered to customers if a purchase is paid for within a certain time limit) can reduce the GMROII, as can rebates offered at the time of the sale. A retailer may have the optimal mix of inventory and fill rate, which would suggest operational efficiency and good customer satisfaction, but a low GMROII due to marketing program

Impact  

discounts that drove demand higher. In this instance, the marketer’s programs increased demand, but it affected margins. Marketers and retail management must recognize the impact of their various programs on costs, gross margins, inventory, and customer satisfaction to determine the appropriate mix that yields the proper investment return. Data for GMROII is found in financial and accounting statements that track the cost of goods sold before interest, taxes, depreciation, and amortization.  i Shari Waters, Calculate Your Gross Margin Return on Inventory Investment, The Balance.Com, May 2, 2017. Retrieved May 29, 2017 from https://www.thebalance.com/calculate-gmroi-2890416; PWC’s Retail Benchmarking Survey, November 2013. http://www.retailcouncil.org/sites/default/files/documents/pwc-benchmarking-study-201311-en.pdf; George Matyjewicz, Inventory Turns, N.D. Business Know-How. Retrieved May 30, 2017 from https://www.businessknowhow.com/manage/inventory.htm

Chapter 85 Sales Per Square Foot Measurement Need Retail space is an expensive solution, whether owned or leased, so retailers need to maximize the sales per square foot (SPSF) of the main customer selling space.

Solutioni SPSF measures how productive a retailer is with the use of retail space for merchandising products that generate revenue. It is important to note that the selling area refers to the actual selling space, as opposed to window displays (to which consumers have no access), dressing rooms (where no merchandise is displayed for sale), and similar nonselling floor space. Also, vacant space costs money (much like an empty airline seat costs money), so the productive use of existing space is critical to successful sales:

SPSF = Where

S Sa

SPSF = sales per square foot S = total sales Sa = selling area in square feet Suppose that a retailer specializing in Chinese herbal medicine has total sales of $2 million and a total selling area across all stores of 10,000 square feet. The SPSF is $200, calculated as follows: SPSF =

$2,000,000 10,000

= $200

Impact Retail space is a form of marketing, and marketers pay close attention to the use of each store’s selling space so that it is appealing to customers. Therefore, a retailer’s selling space is a key productive asset since its business model depends on its effectiveness at utilizing this space to generate profitable sales. Store layout, merchandise

  Chapter 85: Sales Per Square Foot mix, and general ambience all influence consumer purchase decisions at the store level, and each of these are important to marketers who want to create a positive shopping experience for consumers and develop the proper image for the company. SPSF varies, so marketers must review these variations to determine the factors influencing sales. Furthermore, any advertising and promotions run by marketers to increase customer traffic and sales will have a direct and measurable impact on SPSF. Large retail chains will use SPSF to assess performance across all stores, looking for those that either underperform or overperform against the chain average. In an effort to maximize buying power from suppliers and develop consistent expectations from the market, large chains often focus on designing selling space with identical layouts and merchandise mixes. However, this assumes that customer expectations and needs are the same everywhere, which is rarely true. Retailers ignore these differences at their own peril. Marketers will want to compare SPSF for the same period in prior years to understand how their programs affect buying patterns. Promotions, such as yearly “sales” (discounts), can drive temporary revenue increases and even higher monetary margins on an absolute basis, although they will likely be lower on a percentage basis. Correspondingly, months with low or no marketing promotions may result in lower overall financial performance. The challenge is determining the proper use of aggressive marketing programs since, done too frequently, they can train consumers to wait for promotions before shopping, harming the business pattern during nonpromotion periods. Marketers will also want to understand how their performance compares to that of their competitors’ and/or the industry in which they compete. Most retailers generate daily sales reports that are consolidated into weekly and monthly financial summaries. Information on each store’s square footage should be available in the detailed notes of the company’s tangible assets. Marketers merely need to match each store’s revenues with its square footage to ensure the correct SPSF total is calculated at the store level. This is usually aggregated to the company level to arrive at an overall average SPSF figure.  Vitaly Pyrih, Profit Navigation, ORMS Today, December 1997. Retrieved May 30, 2017 from Chance Miller, Apple Again Found to be the World’s Top Retailer in Sales Per Square Foot, 9to5Mac, July 29, 2017. Retrieved May 30, 2017 from https://9to5mac.com/2017/07/29/apple-top-retailer-persquare-foot/ i

Chapter 86 Sales/Profits Per Employee Measurement Need Evaluating the financial contribution (sales!) generated by each employee is an important productivity measure.

Solutioni This is a measure of financial performance on an individual employee basis:

SPPE = Where

S or P E

SPPE = sales/profits per employee S = total sales P = total profits E = total number of full-time employees Let’s assume a marketer’s product line has $60 million in sales and $6 million in profits and that there are 600 full-time employees. The sales per employee is therefore $100,000, calculated as follows:

$60,000,000 600 = $100,000

SPPE =

Its profits per employee are:

$6,000,000 600 = $10,000

SPPE =

Impact Productivity is important in every business. Retailers have high fixed costs in property, plant, and equipment, plus additional investments in inventory and marketing.

  Chapter 86: Sales/Profits Per Employee Retail stores with slow or no business must still pay employees to keep the business running during operating hours. Sales/profits per employee (SPPE) is an important measure of productivity. It helps a retailer gauge, in effect, the amount generated (either revenues or profits) per employee. A lower figure is an indication that either the company is overstaffed or underproductive with its employees and, therefore, ways must be found to improve. Retail management should include operations staff when measuring productivity since their wages are effectively paid by the sales revenues generated, with the caveat that including operations staff can distort the performance of employees on the selling floor. A company’s sales are likely to be somewhat cyclical during the course of the year, with certain times of the year stronger (from a revenue standpoint) than others. This will affect the SPPE figure differently at each change in the business cycle. Retailers may find that their SPPE numbers are quite strong during holiday periods (relative to the full-time employees), which can distort the overall productivity picture for a company. SPPE may also be misleading if industry averages are used as performance benchmarks since competitors, while offering similar products, may have very different business models and cost structures. Therefore, marketers and company managers need to consider SPPE in the context of their capabilities and asset utilization first, before comparing it to the competition. However, if a company’s SPPE is dramatically different from industry norms, then marketing should investigate the reasons behind the differences. It may turn out that you have long-term challenges to correct to remain competitive. The sales and profit data come from the company’s financial statements; specifically, from the income statement. The employee information is most likely in the human resource files. This example refers only to full-time employees.  Ready Ratios, Revenue Per Employee, N.D. Retrieved May 28, 2017 from https://www.readyratios.com/reference/profitability/revenue_per_employee.html; Nicholas Carlson, Revenue Per Employee Charts Are a Fascinating Way to Judge the Health of Tech Companies, Business Insider, April 9. 2015. Retrieved May 28, 2017 from http://www.businessinsider.com/revenue-per-employee-charts-are-a-fascinating-way-to-judgethe-health-of-tech-companies-2015–4 i

Chapter 87 Retail Close Ratio Measurement Need To determine how many prospective customers become paying customers (not just window shoppers).

Solutioni The close ratio measures how many customers convert from shoppers to actual buyers. It is calculated as follows:

Cr = Where

Bt Tr

Cr = close ratio Bt = buyers in time t Tt = total traffic in time t In this example, a retailer has 300 total buyers on any given day. If this retailer has total traffic of 1,500 shoppers, then the close ratio is 10%, computed as follows: =

300 1,500

= .20 or 20%

Impact Understanding the close ratio can assist retailers in developing strategies designed to increase the conversion from shoppers to buyers, which will likely lead to increased sales. A useful marketing tool below is derived from the Ansoff Matrixii outlining available options (see Figure 87.1):

  Chapter 87: Retail Close Ratio

Figure 87.1: Ansoff Matrix Expressing Customer and Product Marketing Options

Each quadrant describes a different customer and product approach. Of course, this framework can be expanded by marketers to outline corresponding marketing programs, including pricing, promotion, and placement. The purpose is to determine a strategy or combination of strategies to inspire higher conversion from shoppers to buyers and, thus, increase sales. Most retailers do not have the time or resources to count shoppers who visit their store on any given day, although there are tools available to assist. Electronic triggers mounted at store entrances can record each shopper that crosses their path, enabling store managers to review the visitor totals when they close the daily books. A more expensive, and arguably less precise, option is to pay someone to count the number of shoppers who enter the store over a period of a few days to develop an average shopper total for those days. Errors are reduced with electronic triggers or even doormat counters that record a shopper every time someone steps on the mat. However, these, too, can be imperfect since shopping carts may be mistakenly counted as shoppers. Furthermore, the electronic method does not distinguish between unique visitors, repeat visitors, and buyers; information which is of interest to marketers since they want to understand buyer profiles as deeply as possible to develop marketing programs that maximize purchases. The data for buyers (transactions) is captured in the end-of-day totals and/or in the point-of-purchase software. The harder figure to determine is the total number of shoppers, but this can be done either with electronic counters mounted near the entrance to the store, or people can be hired to survey the total number of shoppers who visit each day over a period of several days to determine an average.  i Richard Young, Sales Pipeline: Five KPIs Every Business Must Consider, Sales Pop, December 4, 2013. Retrieved May 23, 2017 from https://salespop.pipelinersales.com/sales-management/sales-

Impact 

3

 pipeline-five-kpis-every-business-must-consider/; SMS Storetraffic.com, Driving Your Closing Ratio…Drive Your Sales. Retrieved May 23, 2017 from https://storetraffic.com/drive-your-closingratio-drive-your-sales/ ii The Ansoff Matrix first appeared in the Harvard Business Review in 1957 in an article by H. I. Ansoff entitled “Strategies for Diversification.” Ansoff discussed it further in his book Corporate Strategy (New York: McGraw-Hill, 1965).

Chapter 88 Retail Margin Percentage Measurement Need To determine the retail margin percentage (RMP) given the complexities of retail since retailing is a high cost business yielding low margins.

Solutioni The RMP is the profit margin that retailers realize after purchasing from the wholesaler and then selling to the consumer. It is a measure of how much money the retailer makes. The following formula summarizes the calculation: RMP =

( Sp − Pp) Sp

Where RMP = retail margin percentage Sp = selling price to consumers Pp = purchase price from wholesalers Suppose a retailer is selling a consumer product at a retail price of $5 and the price they paid from the wholesaler was $2.50. The RMP is 50%. RMP =

($5 − $2.50) $5

= 50%

Impact High capital investment in equipment, plus facilities costs, whether leased or owned, put pressure on the retailer to generate profitable sales. Additional costs include labor and inventory. Each of these costs reduces the retailer’s profits, and RMP objectives have an important impact on product and category profitability, positioning, and even image. It reflects the retailer’s strategy in attracting the target audience and it is also influenced by the manufacturer’s own recommendations. The RMP will have an impact on the merchandise mix between store brands and national or global brands. Store brands may allow a retailer to increase its margins, even accounting for the in-house production and manufacturing costs, over nonstore,

  Chapter 88: Retail Margin Percentage national brands, thereby improving the RMP. A store brand reduces costs for the retailer since the retailer is not paying the premium prices for the better-known brands. Part of the higher pricing for better-known brands is to offset the higher advertising costs, although the higher prices also reflect the fact that the better-known brands are trusted, allowing the manufacturers to charge higher prices. Retailers set prices based on several factors including their own per-store expenses, store positioning, product type, and customer type. Manufacturers influence retail price expectations by providing guidelines to their retail accounts, depending on their own positioning and margin objectives. The final retail price is also affected by slotting fees (payments a manufacturer pays to a retailer to place the products on store shelves), co-op marketing (a shared advertising or promotional arrangement between manufacturers and retailers to encourage product sales), promotional allowances (additional discounts offered to retailers for performing promotional activities in support of the manufacturer’s products), and other similar marketing programs. For manufacturers and retailers, these fees are usually set at the corporate level and are often negotiated. Retailers will have their own set of pricing and profit guidelines for each product they sell, often down to the individual store level (since goals may vary slightly from market to market, even if the store is part of a chain). In some cases, the corporate strategy may include a tacit understanding that each store manager has limited freedom to adjust corporate requirements based on the prevailing market situation in a given area. The wholesale selling price is usually found on shipping or customer invoices, purchase orders, and/or accounting reports. The retail selling price to consumers is influenced by several factors including manufacturers, marketing programs and, of course, consumer response. Ultimately, the retailer will have this information contained in their end of day sales summaries at the store level, by item.

 James Wilkinson, Margin Percentage Calculation, The Strategic CFO, July 24, 2013. Retrieved June 1, 2017 from https://strategiccfo.com/margin-percentage-calculation/; Matthew Hudson, What Is Gross Profit Margin in Retail? The Balance, April 3, 2017. Retrieved May 9, 2017 from https://www.thebalance.com/what-is-profit-margin-in-retail-2890209

i

Chapter 89 Percent Utilization of Discounts Measurement Need To understand the impact on margin when discounts are used.

Solutioni Percent utilization of discounts (PUD) measures the total value of discounts taken compared to the total purchases from the supplier:

PUD = Where

Vd × 100 Pt

PUD = percent utilization of discounts Vd = $ value of discounts taken Pt = total $ purchases A retailer’s buyer or buying team (in the case of large, multidepartment retailers such as warehouse stores and department stores) purchases their merchandise from a network of suppliers. The suppliers induce product sales often through the use of buyer discounts, used primarily to increase the placement of new products and/or for volume purchases. If a supplier offers 20% discounts for purchases over $100,000, then a retailer who buys $200,000 of merchandise will pay $160,000: = PUD

$40,000 × 100 $200,000

= 20%

Impact When retailers buy products from suppliers, the supplier offers discounts for certain volume purchase levels or as an incentive for the retailer to purchase specific products the supplier is particularly keen on selling. At the end of each business reporting cycle, retailers review the financial results of the time period being measured. This includes measuring the discounts actually taken from suppliers when purchasing their merchandise, to determine if the various discount opportunities offered were

  Chapter 89: Percent Utilization of Discounts utilized. Each discount represents the potential for the retailer to improve their margin, hence the importance of understanding the metric. PUD is a simple, yet highly useful measure enabling retailers to see what percentage of their total purchases received a discount. Retailers want to maximize the use of supplier discounts since it can lead to improved retail margins. When the level of supplier discount utilization is low, the retailer can review purchases with their buyers to see where and what discounts were missed. The information would also demonstrate to the buyer the bottom line impact of missed supplier discount opportunities.

 Leemore Dafny, Christopher Ody, and Matt Schmitt, When Discounts Raise Costs: The Effect of Copay Coupons on Generic Utilization, UCLA Anderson School of Management, October 4, 2016. Retrieved June 1, 2017 from http://www.hbs.edu/faculty/Publication%20Files/DafnyOdySchmitt_CopayCoupons_32601e45849b-4280-9992-2c3e03bc8cc4.pdf; Jerry A. Hausman, Individual Discount Rates and the Purchase and Utilization of Energy Using Durables, The Rand Corporation, Spring 1979. Retrieved May 30, 2017 from https://economics.mit.edu/files/6866 i

Chapter 90 Shrinkage to Net Sales Measurement Need Retail management needs to determine the percentage of inventory lost to shrinkage. Shrinkage is a retail term used to describe the difference between inventory purchased and officially received at the time of delivery, and the actual value of that same inventory in the stores, warehouses, or other locations in the retailer’s distribution channel. Shrinkage results from customer or employee theft, misplaced or careless inventory storage, or administrative errors.

Solutioni = SNS Where

AI − BI × 100 Snt

SNS = shrinkage to net sales AI = actual inventory in $ (measured at retailer’s cost) BI = book inventory in $ (measured at retailer’s cost) Snt = net $ sales in time period t Retailers regularly confront unaccounted inventory shrinkage. Let’s assume a local hardware store that sells tools does a weekly inventory and its most recent results reveal that the actual inventory for its most recent week-ending inventory was valued at $55,000. The managers compare that number to the book inventory (determined by calculating inventory purchases minus sales for the same week), which indicates a value of $62,000. Total net sales for that week were $71,000 (measured at full retail price). The calculation is as follows: = SNS

$55,000 − $62,000 × 100 $71,000

= –9.9% Therefore, this retailer has shrinkage to net sales (SNS) of 9.9%. With low net margins common in retail businesses, a nearly 10% shrinkage has a substantial impact on the bottom line.

  Chapter 90: Shrinkage to Net Sales

Impact SNS helps retailers understand the direct financial impact of shrinkage, although it does not suggest a cause. Retail management should review its security procedures and inventory tracking systems, compare purchase orders to products shipped, and review the signatures that approved inventory for shipping. Management should also review any records that contain daily inventory levels and identify the times of day when products were shipped to determine any patterns that may exist. Perhaps the same employee is on the job each time actual versus book inventory levels differ, and is improperly recording shipments, in which case more training is needed. It is conceivable that when the inventory was first received it was counted incorrectly. Of course, the worst-case scenario is theft and pilferage. The most important action management should take is to reduce shrinkage through a diligent review of every touch point the inventory crossed from its arrival to its shipment (or when it went missing).  Chris Bradford, How to Determine Inventory Shrinkage Percent, AZ Central, N.D. Retrieved May 9, 2017 from http://yourbusiness.azcentral.com/determine-inventory-shrinkage-percent-7837.html; Jac Brittain, How to Calculate Shrinkage in Retail, LPM Insider, May 11, 2017. Retrieved May 14, 2017 from http://losspreventionmedia.com/insider/inventory-shrinkage/how-to-calculate-shrinkage-inretail/ i



Part 11: Sales Metrics The measures in this section help sales managers set the size of their sales force, establish quotas, evaluate salesperson performance, calculate variances to plan, and determine compensation. Sales forces conducting person-to-person selling remains one of the most effective ways to market products. The costs are higher due to the limited number of customers a salesperson can reach, versus the broad-based reach of integrated marketing communications. But, business is still conducted primarily based on relationships between companies and with customers, so sales people play a critical role. Sales people uncover the needs of buyers, whether retail buyers, wholesalers, B2B buying teams, or individual consumers in retail stores. The best sales people excel due to a unique combination of business intelligence, entrepreneurial spirit, strong people skills, and an intense desire to win. Companies have a significant investment in their sales forces and they want to see them succeed by producing a regular stream of sales from new and existing customers. Sales management must plan their sales activities each year based on corporate goals, market conditions, and the performance expectations of each sales person. The challenges are sizable since markets, customers, and competitors constantly change. The challenges are compounded by the relentless pressure to produce results. Sales management has to establish the right expectations via quotas and targets, monitor the activities of each salesperson, keep the sales team focused on growing the business, motivate the team to keep working hard, and minimize interference from nonsales people in the organization. The measures in this section provide needed quantitative insight. Selling success is a relationship-driven process, however. No matter how elegant or sophisticated the

DOI 10.1515/9781501507304-011

  Part 11: Sales Metrics quantitative analysis, closing the sale depends on interpersonal relationships, in which trust is crucial. The Five Ambassadors framework (see Figure P11.1) describes the behaviors of top performing business people, particularly those in sales. It should be given careful consideration by sales and marketing management in the development of their plans since, ultimately, talented people are needed to ensure successful implementation. Brand Ambassador Representative of company’s image and culture; conveyed via verbal and visual imagery Imagination Ambassador

Experience Ambassador

Combines relevant

Creates experiences and

company resources

results born from wisdom,

imaginatively to benefit

trial and error, and self-

customers, market

confidence 5 AMBASSADORS Value Producing Behaviors Knowledge Ambassador Deep knowledge of customer, market and business overall; translates knowledge into creative, effective solutions

Relationship Ambassador

Views relationships from lifetime potential, not one-time; nurtures client relationships whether immediate need or not

Figure P11.1: Figure P11.1 The Five Ambassadors Framework

The Five Ambassadors framework describes the behaviors of top performers. It has evolved over five years. Initially based on interviews with U.S. CEOs and top sales performers, it has been further developed since, through discussions with CEOs of companies in Asia and Europe, feedback about top sales performers in multiple industries, and student research of over 200 companies around the world since 2001. Each of the Five Ambassadors is a specific behavior exhibited by the top performers at different times of their job. Typically, these behaviors were most prominent when the individual was either selling a product, service, or idea. The top performer effortlessly shifted from one Ambassador role to the next, depending on the specific

Part 11: Sales Metrics  

business conditions they faced at that time. The Five Ambassadors’ behaviors were also exhibited when the top performers were seeking assistance (funding, budget increase, project help) from another party. These behaviors are rarely conscious. The top performer did not think to him or herself, “Now I must act like a resource ambassador.” Rather, the Five Ambassadors were a fluid set of behaviors that ultimately convinced the other party of the merits of the top performer’s argument. Each of the Five Ambassadors encompasses multiple behaviors within, but the behaviors were similar enough to be grouped into the broader Ambassador designations. Separately, each of the Five Ambassadors is an admirable set of behavior characteristics. Collectively, they are a powerful combination of skills that contributes to the overall success of the enterprise. Finally, the Five Ambassadors are not sequential behaviors. They are often simultaneous.

Brand Ambassador This describes an individual’s efforts to present their company, product, or department to another person or group (customer, vendor, or another internal department), using visual or verbal imagery. Visual imagery is self-explanatory: top performers are adept at using relevant visual examples to complement their presentation, making it memorable and connecting the audience to the initiative being presented. Verbal imagery deals with the words used to paint verbal pictures.

Imagination Ambassador Imagination Ambassador describes how the top performer’s combines company resources in imaginative, often unique ways, to benefit customers and the market. This is not merely a surface level awareness of the company’s products, but an in-depth understanding of its organization: the most influential people, how different departments contribute, and which resources would be most appealing and relevant to the buying or receiving party. It is often exhibited as an explicit description of which departments or functions were part of the solution being sold. For example, in the enterprise software industry, a product sale is far more than just the software. It includes engineering support, customer service, warranties, consulting, and more. Once the sale is made, the customer requires that the product works and functions as specified and, if not, wants to know what remedies are available. Top performers understand this and, in the presales effort, they work hard to combine the various resources to create a solution that the customer explicitly realizes solves their need. The bottom line is that the Imagination Ambassador behaviors connect a company to the cus-

  Part 11: Sales Metrics tomer beyond the core product purchase by extending the product definition to include the areas that support it. As a result, the customer develops confidence that the company will support the products it sells.

Knowledge Ambassador The Knowledge Ambassador describes the knowledge that the top performer has and uses to describe for the buyer market conditions, trends in the economic environment, and similar information. The top performer then presents this information throughout the sales or persuasion process to help the customer understand outside conditions and influences that could affect their business (explaining the “need” to buy the product). This information is gleaned from a wide range of sources (the Internet, magazines, newspapers) and becomes a crucial aspect of the top performer’s efforts to win the customer. Top performers frequently update their market knowledge so they can be an advocate for both the customer and their own company while demonstrating why the customer needs their products to be successful in the challenging environment described. The Knowledge Ambassador behaviors help the customer become smarter about their own business and understand why the seller’s products are an integral piece of their success.

Relationship Ambassador The Relationship Ambassador behaviors describe how sellers relate to buyers. A salesperson must have a deep understanding of his or her buyers. Not just the company overall, but the buyers individually, including who they are, what they like, and hate [usually it’s love and hate, like and dislike. Are you putting in hate on purpose, or would “dislike” be better?], what their interests are, why they have bought before, and what they have bought before. The Relationship Ambassador behaviors continue even when a sale has been completed, as the seller shifts to a more informal relationship, but never stops contact. The seller wants to be the first person the buyer thinks of when it comes time to purchase again.

Experience Ambassador The Experience Ambassador behaviors relate to the wisdom that comes from trial and error and the application of that wisdom every day. Overall, the Five Ambassadors are a seamless pattern of behaviors exhibited by top performers. Rather than approaching each business relationship with a methodical, rigid plan outlining their behavior, the top performers combine spontaneity with thoughtful planning to achieve their objectives.

Part 11: Sales Metrics  

Sales managers understand the dual needs of quantitative and qualitative measures. The challenge is determining what measures are most important so that a salesperson’s performance can be improved. The metrics discussed in this section are: 91. Net sales contribution 92. Absolute index 93. Relative index 94. Percent of sales 95. Independent sales representative analysis 96. Turnover rate 97. Recruiting 98. Breakdown approach 99. Workload approach 100.Sales performance quotas 101. Average sales per call 102. Close process and close ratio 103. Cost per call 104. Break-even sales volume 105. Sales productivity 106.Four factor model 107. Sales variance analysis 108.Sales volume variance 109. Sales enablement 110. Net promoter score®

Chapter 91 Net Sales Contribution Measurement Need To determine how much a particular entity represents of the total sales of all entities.

Solutioni Net sales contribution calculates the financial sales contribution of a specific segment or sales territory to total sales for all segments or territories, expressed as a percentage. Note that territories can be defined geographically and/or in terms of customer or product type. The formula for net sales contribution is: = Sni

Si × 100 ∑ Si

Where Sni = net sales contribution for segment or territory i Si = sales from segment or territory i ∑St = total sales from all segments or territories To illustrate, assume a company has total sales of $100 million, with sales from territory A of $25 million. The net sales contribution is 25%:

= Sni

$25,000,000 × 100 $100,000,000

Impact Net sales contribution measures each segment’s or territory’s contribution to total sales. It is a useful starting point for further analysis when marketers wish to clarify the underlying factors of each segment’s contribution, particularly as measured against the marketing plan for the time period under review. Knowing the performance of each segment helps marketers be more effective in their future marketing and product efforts, and net sales contribution is a valuable metric in this process.

  Chapter 91: Net Sales Contribution Sales data on each segment or territory is maintained by sales management. Segmentation is an important tool to help marketers identify groups of customers with similar characteristics, for which they then develop marketing programs that appeal to each segment while also maintaining consistency with their company’s goals. Most finance departments may also keep this level of detailed data, depending on the reporting criteria and requirements they use.  Harold Averkamp, What Is Contribution Margin? Accounting Coach, N.D. Retrieved May 14, 2017 from https://www.accountingcoach.com/blog/what-is-contribution-margin; Tat Chee Tsui. Interstate Comparison—Use of Contribution Margin in Determination of Price Fixing, Pace International Law Review, April 2011; Steven Bragg, Contribution Margin Ratio, Accounting Tools, July 19, 2017. Retrieved May 14, 2017 from https://www.accountingtools.com/articles/2017/5/16/contribution-margin-ratio i

Chapter 92 Absolute Index Measurement Need When marketers need to determine overall performance and annual bonus awards.

Solutioni AI = Where

Rat Rbt

AI = absolute index Rat = the sum of total actual revenues during time period t Rbt = budgeted revenues during time period t Revenue estimates are a key target set by sales management, derived from the company’s overall performance objectives for the year. During the annual performance review, sales management compares actual revenue results to estimates. For example, let’s assume a company has five sales offices in Japan, and each sales office is allocated an equal share of the estimated revenue target. If the total revenue target is $100 million, then each office would be responsible for generating $20 million in revenues. At the end of the year, actual revenues total $120 million. The Absolute (AI) Index is calculated as follows:

AI =

$120 million $100 million

= 1.2 The answer provides sales management with performance results that may determine the level of bonuses awarded. Results larger than 1 indicate that the sales territory overperformed and exceeded its target, whereas anything less than 1 means the territory underperformed.

  Chapter 92: Absolute Index

Impact The AI measures absolute (or actual) revenues for every sales unit (region, territory, office, team, individual) and compares the result to budget revenues to arrive at a performance factor. Bonus awards differ for every company, but one approach is to pay a bonus equivalent to one month’s salary if sales representatives achieve 100% of their sales target (an AI of 1.0). We assume that each sales rep earns a base salary of $48,000 annually. Therefore, monthly pay equals $4,000. Assume further that the individual territories had the performance results in Table 92.1. Table 92.1: Performance Results and the Absolute Index Territory

Estimated revenues

Actual revenues

Absolute Index

A

$,,

$,,

.

B

$,,

$,,

C

$,,

$,,

.

D

$,,

$,,

.

E

$,,

$,,

.

.

The bonus awarded per sales representative would be as follows: Territory A: $4,000 × 1.3 = $5,200 Territory B: $4,000 × .85 = $3,400 Territory C: $4,000 × 1.2 = $4,800 Territory D: $4,000 × 1.4 = $5,600 Territory E: $4,000 × 1.25 = $5,000 Sales management must make a decision whether Territory B even deserves a bonus since it did not achieve its target. The decision rests on many factors: – Were there uncontrollable factors that affected Territory B’s results, such as a sudden economic change in that region or a surprising new competitor with a newer, more affordable product? – Did individual sales representatives within the territory achieve and/or exceed their individual performance and, if so, should they be rewarded? – Was the revenue target too aggressive for the territory?

Impact  

Sales management must also consider the psychological impact of their decision. For example, if Territory B is not awarded a bonus, will the sales team be demoralized, or is that even a consideration? Conversely, if a bonus is awarded, then the other territories may be resentful since it signals that management awards bonuses even for underperformance, which may lead other territories to not work as hard in the future knowing that they will still receive a bonus. Each of these questions and challenges must be weighed in the context of each company’s unique competitive situation and in relation to their own company culture as there is no best way to address this issue. The data for budgeted revenues is found in the annual sales plan, which will have goals for each performance area (revenues, profits, units sold, number of accounts, etc.). End of year actual revenue figures will be part of the company’s annual report. Each territory’s results are unlikely to be in the annual report, but will be contained in territory-by-territory summaries provided by sales management to the finance or accounting people.  June Cotte and Aland Yang, “Worldwide Equipment (China) Ltd: A Sales Performance Dilemma”; Richard Ivey School of Business, University of Western Ontario, case # 902A28.

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Chapter 93 Relative Index Measurement Need To understand the relative performance of each sales territory.

Solutioni Relative Index (RI) is a relative ranking methodology, not a formula, and is determined by comparing sales territories in a country or a region to each other based on a common performance measure, usually revenues (although it can be profits or units, depending on the company and industry situation). The chapter on the Absolute Index (AI) showed the sales performance of five territories for one company (see Table 93.1). Table 93.1: Same as Table 92.1 on Absolute Index Territory

Estimated revenues

Actual revenues

Absolute Index

A

$,,

$,,

.

B

$,,

$,,

.

C

$,,

$,,

.

D

$,,

$,,

.

E

$,,

$,,

.

Sales management then ranks the final performances from best to worst to determine the RI (see Table 93.2). Table 93.2: Table 93.1 sorted by Relative Index Territory

Estimated revenues

Actual revenues

Relative Index

Rank

D

$,,

$,,

.



A

$,,

$,,

.



E

$,,

$,,

.



C

$,,

$,,

.



B

$,,

$,,

.



  Chapter 93: Relative Index If sales management wishes to reward overall team bonuses, then RI is a helpful guide. The actual bonus amount depends on each company’s real situation, but for illustration we will assume that the five territories must meet their target before a bonus is paid. Furthermore, since there are five territories, we will assume that the RIbased team bonus generously awards 5 times the base bonus to the top team, 4 times to the second ranked team, 3 times to the third ranked team, 2 times to the fourth ranked team, and 1 time to the fifth ranked team. Clearly, this structure has its fiduciary limits since a company with fifty sales territories would pay enormous sums to the top teams, so a more sophisticated model would be used, but the evaluation process would remain the same. The bonus awarded per sales representative would be as follows: Territory D: $4,000 × 1.4 = $5,600 × 5 = $28,000 Territory A: $4,000 × 1.3 = $5,200 × 5 = $20,800 Territory E: $4,000 × 1.25 = $5,000 × 3 = $15,000 Territory C: $4,000 × 1.2 = $4,800 × 2 = $9,600 Territory B: $4,000 × .85 = $3,400 × 0 = $0

Impact The RI helps marketers measure the relative revenue results for each sales territory in relation to each other. It is figured once the AI is calculated. The RI is effective with almost any sales criteria since it is merely a ranking methodology, with the stipulation that the figures used to determine the relative rankings must be consistent (i.e., use only revenues, units, or profits, etc.). The AI, from which RI is derived, illustrated the impact of each territory’s AI on the bonus awarded, and we showed that Territory B’s sales representatives each received a bonus of $3,400. However, most companies are unlikely to pay bonuses when targets are not met, unless the circumstances are extraordinary.

 June Cotte and Alan Yang, “Worldwide Equipment (China) Ltd: A Sales Performance Dilemma”; Richard Ivey School of Business, University of Western Ontario, case # 902A28, pp. 9–10.

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Chapter 94 Percent of Sales Measurement Need To determine the optimal sales force size as a percentage of total sales.

Solutioni The percent of sales measurement is calculated using the following steps: 1. Forecast planned revenues 2. Determine percent of sales based on industry standards, the firm’s own historical performance, or a combination of both 3. Budget for management and field sales roles Let’s assume that a Sydney-based food manufacturer of classic Fish and Chips had sales of $50 million last year and anticipates 20% growth next year, to $60 million in sales. It sells to retail chains and individual sidewalk vendors, and the industry average for the cost of the sales force as a percentage of total sales is 3.6%. The company’s sales budget is divided into management (20%), field sales (75%), and support staff (5%). Based on this, we can now determine the sales force size by first calculating: 1. Sales force budget 2. Sales force percent 3. Sales force dollars

Sales force budget SFB = PR × FSR Where SFB = sales force budget PR = projected revenues FSR = field sales ratio (based on industry average) SFB = $60,000,000 × 0.036 = $2,160,000

  Chapter 94:Percent of Sales Sales force percent SFP = FS + SS Where SFP = sales force percent FS = field sales percent of budget dollars SS = support staff percent of budget dollars SFP = 0.75 + 0.05 = 0.80

Sales force dollars SFD = SFB × SFP Where SFD = sales force dollars SFB = sales force budget SFP = sales force percent SFD = $2,160,000 × 0.80 = $1,728,000 If the average salesperson in this company (or industry) costs $75,000 (including salary, bonus, commission, and benefits, also known as “fully loaded” costs), then we can calculate the number of sales people the company can afford as follows: SFS =

Where

SFD SFC

SFS = sales force size SFD = sales force dollars SFC = sales force costs

SFS =

$1,728,000 $75,000

= 23 If they had twenty people last year, then three additional people can be hired for a total sales force size of twenty-three.

Impact  

Impact Sales management may find this tool useful for planning purposes and to justify an expansion in their team. However, management should also consider whether the gain in sales can be accomplished by altering compensation incentives of the existing team, realigning territories, or shifting responsibilities among the existing team members. Hiring new people adds a sizable potential cost to the sales budget and, if the forecast numbers are not met, then the sales organization’s performance will be worse than before since new people were added but no new sales. The pressure will then be on sales management to quickly either increase sales, thereby putting additional stress on the field sales force, or terminate some of their sales reps, potentially hurting morale. The use of industry standards is rarely a practical benchmark, attractive though it may be for planning purposes. Industry standards use averages, but often companies within an industry have significantly different operating standards, sizes, and financial requirements, distorting the averages. The chart on the following page provides data on the average sales force size across industries. If a company is noticeably different than its industry average, then management would be wise to analyze the possible reasons for the variation, keeping its own context firmly in mind.  i Adapted from W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 114–115.

Chapter 95 Independent Sales Representative Analysis Measurement Need A critical need is determining whether to have a dedicated sales force, and the associated higher fixed costs, or an independent sales force, usually from a third-party firm contracted to the company. The question is how to compare these two approaches.

Solutioni The analysis begins with setting the cost of a company sales force and an independent sales force equal to each other: Cost of company sales force = Cost of independent sales force Sales management would need to solve for the breakeven level of sales, below which the independent sales force would be more attractive and above which the dedicated sales force is the more sensible approach. To do this, cost comparisons need to be made. Let’s assume the company has a total sales cost of $3 million and companyemployed sales people are paid $75,000 plus a 4% commission on each sale. The average independent salesperson is paid a 7% commission, plus an allowance for administrative costs of $25,000. In the formula below, x represents the breakeven level of sales: .04x + $3,000,000 = .07x + $25,000 $2,975,000 = .03x $99,166,667 = x Therefore, breakeven sales is $99,166,667, below which the company should use the independent sales force and above which the company should use a dedicated force (see Figure 95.1).

TOTAL SELLING COSTS

  Chapter 95: Independent Sales Representative Analysis

n de en p e In d

Sales Dedicated

rce Fo s ale tS

Dedicated Sales Force is cheaper

Force

Independent Sales Force is cheaper

Breakeven ($99 million+) SALES VOLUME Figure 95.1: Dedicated Versus Independent Sales Force Cost Analysis Source: Adapted from Cron, W. L., T. E. DeCarlo, and D. J. Palrymple. 2004. Sales Management. John Wiley & Sons, Inc., pp. 253–254.

Impact Cost is not the only consideration for sales management in weighing the pros and cons of a dedicated sales force versus an independent sales force. A dedicated sales force is expensive since the company is paying salary and full benefits, even as sales cycles inevitably increase and decrease. But a dedicated sales force is also going to be more loyal and devoted to the company’s products, whereas an independent sales force is representing products from multiple companies and may emphasize those products easiest to sell. However, a proven independent sales force provides a significant boost to the company by generating sales at a lower cost. Furthermore, similar to the reward options available to in-house sales forces, company management can create incentives to facilitate better cooperation and performance from the independent sales team. There is no clear-cut resolution, nor should this analysis be used to arrive at one. Sales management needs to consider the situation in which their company operates and factor in long-term strategic goals. Costs will influence the decision, but other harder to control factors, like dedication and loyalty, may dictate which option may be more successful in the long run.  Adapted from W. L. Cron, T. E. DeCarlo, and D. J. Palrymple. Sales Management (John Wiley & Sons, Inc., 2004), 253–254.

i

Chapter 96 Turnover Rate Measurement Need To measure sales force turnover.

Solutioni The turnover rate calculates the number of salesperson departures relative to the total sales force size, multiplied by 100 (to convert it to a percentage):

TR= Where

D × 100 F

TR = turnover rate D = number of departures annually F = total sales force size (annual average) If a company has 1,000 sales people worldwide and seventy-five depart, then the turnover rate is 7.5%:

= TR

75 × 100 1,000

= 7.5%

Impact Turnover is inevitable as organizations change. Departures of salespeople can be expensive since management invests time and money into recruiting, training, and retaining salespeople. When salespeople leave, especially top performers, they take knowledge (about the company, its products, and its strategy, as well as insight into their own territories about customers and market dynamics) to another firm. The turnover rate should be reviewed to determine if the results are “acceptable.” Industry and competitor comparisons may be part of a company’s sales review. A low turnover percentage may sound great from the Human Resources and expense perspectives, but it may also signal that the company is overly generous with its compensation, loose with its performance standards, or that sales management has a hard time identifying and replacing underperforming people.

  Chapter 96: Turnover Rate Turnover is comprised of several components: – Death – Involuntary departure (i.e., termination) – Voluntary departure (i.e., recruitment by another company) – Retirement – Internal transfer Death, of course, is a form of involuntary departure. As the least controllable factor, it should not be a key management concern. Termination results from poor performance, poor sales rep/company fit, illegal or unethical salesperson behavior, or job loss due to company-wide cutbacks. Sales management can minimize turnover from termination if their recruiting and candidate selection criteria are clear, the interview process involves managers and colleagues from several departments, and a thorough background check is conducted. Voluntary departure may be within management’s control if they are familiar with their salespeople and can identify sources of dissatisfaction before they grow into problems. Sales management may decide to respond by improving financial compensation, promoting staff, changing responsibilities, or offering other nonfinancial benefits (more days of paid vacation, for example). Any of these decisions will be weighted against the potential future value expected from the sales reps most likely to depart. Retirement is less likely to be a significant challenge for savvy sales management since they will have anticipated replacing those retiring for months or even years, allowing time for recruiting of new salespeople and for succession planning. However, early retirement may occasionally surprise sales management, perhaps due to personal reasons from the sales rep. Turnover’s impact can cost a company in other ways. A report by Better Jobs Better Care, a U.S.-based program funded by the Atlantic Philanthropies and the Robert Wood Johnson Foundation, outlined additional costs related to turnover: Direct costs include: – Cost of separation from the company – Cost of vacancy – Cost of replacement – Cost of training and orientation – Cost of increased injured workers Indirect costs include: – Lost productivity until replacement is trained – Cost due to reduced service quality – Lost clients to other agencies due to deterioration in agency image, etc. – Cost due to deterioration in organizational culture and employee morale adversely impacting reputation, service quality and further increasing turnover

Impact  

Costs at service delivery level include: – Consumer/Clients: o Reduction in quality of care and quality of life o Care hours not provided – Workers: o Increased worker injuries o Increased physical and emotional stress o Deterioration in working conditions leading to increased likelihood of quitting Third-party payer costs include: – Under-funding of care services due to financial drain of turnover – Increased downstream medical costs for Medicaid and Medicare – Illnesses and injuries attributable to reduced service quality – Higher levels of institutionalization of clients due to insufficient community based staffing and quality of care. Given the expense related to turnover, sales managers should conduct diligent and thorough evaluations of the causes of their organization’s turnover to determine areas for improvement.  Tutor2u, Labour Turnover, N.D. Retrieved May 27, 2017 from https://www.tutor2u.net/business/reference/labour-turnover; SHRM, How to Determine Turnover Rate, August 11, 2015. Retrieved May 27, 2017 from https://www.shrm.org/resourcesandtools/tools-and-samples/how-to-guides/pages/determineturnoverrate.aspx i

Chapter 97 Recruiting Measurement Need Determining the number of applicants required to ultimately fill the vacant positions is needed.

Solutioni The following formula can be used to determine the scope of the recruiting effort:

R= Where

H S× A

R = recruiting H = new hires required S = percentage of recruits selected A = percentage who accept An illustration will help: – – –

Company X needs 25 new salespeople Past experience indicates 20% of those who apply will be offered positions HR statistics suggest that 75% of those offered a new position will accept:

R=

25 (.20) × (.75)

= 167 Based on these statistics, a minimum of 167 people would need to apply if the company wants to fill the twenty-five positions.

Impact With salespeople filling a vital role (growing revenues, profits, and customers), identifying and recruiting the best talent is one of sales management’s most important

  Chapter 97: Recruiting tasks. Sales management may lead its own recruiting effort or, more likely, they will work with the HR department to coordinate the recruiting efforts. Recruiting is an important activity and sales management must carefully plan the time and people resources required to do an effective job. In this basic example, 167 applicants may be a large number of applicants to review if your organization is small or medium sized. On the other hand, if you are IBM, then the number of people available from HR and field sales is large enough that the responsibilities can be distributed with lower disruption from regular work activities. No matter how large the organization, recruiting requires a keen sense of the following: – The company’s culture – The personalities that would fit your company’s culture – The skills of recruits sought – A clear process for the recruit that is explained upfront – A thoughtful description of the job – A set of interview questions designed to identify the best possible candidates for your company – The professional will to stick to your overall recruiting standards and not settle on talent less qualified than you need

 i Adapted from W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 324.

Chapter 98 Breakdown Approach Measurement Need They must determine how many salespeople are needed to service existing customers and also attract new customers.

Solutioni To determine sales force size using the breakdown approach, sales professionals must know their previous sales history, projections of their own new sales for the upcoming year, and market forecasts.1 It is calculated using this formula2:

SFS = Where

FS SPP

SFS = sales force size FS = forecasted sales SPP = average sales per person To determine sales force size, sales management must first develop total forecast sales for the year. To illustrate,3 let’s assume that a beverage company specializing in herbal soft drinks has sales of $100 million. Due to the nature of the company’s contracts with its distributors, all existing business will be renewed for the coming year. Furthermore, the company has confirmed a new distributer contract for $5 million. Research indicates the overall market in herbal beverages will grow 15% this year. To summarize: Sales previous year

= $100,000,000

New distributor contracts current year

= $5,000,000

Total sales forecast current year

= $105,000,000

Projected market growth

= 15%

The company’s current year’s projected sales is the sum of last year’s sales plus this year’s expected new contracts plus projected market growth: FS = FSp + MG (in dollars) Where

  Chapter 98: Breakdown Approach FS = current year’s forecasted sales FSp = current year preliminary sales forecast MG = market growth in dollars Therefore, FSp = $105,000,000 + $15,750,000 = $120,750,000 At this stage, the company must determine whether its existing sales force is the right size or if it needs to adjust it (increase or decrease) based on the total forecast sales. Last year, this herbal beverage company had 100 salespeople. The average sales person generated sales of $1 million ($100,000,000 ÷ 100). To maintain $1 million of sales per person, this company must have 121 salespeople, a 21% increase in sales force size: Average sales per person

= $1,000,000

Sales force size

= $120,750,000 $1,000,000 = 121 salespeople needed

Impact As a company’s business grows, successfully servicing existing and new customers is both a responsibility and ongoing challenge for the field sales force. Every company is different, and tailors their sales planning based on corporate sales objectives (volume or profit-oriented, customer loyalty, or new customer acquisition) and market conditions (customer needs, competitor tactics, economic, and demographic trends). Sales managers design their tactical go-to-market plans around maximizing the potential financial returns from their targeted customer base. Given these factors, companies need to determine sales force size, and the breakdown approach is useful when the primary information available to a company’s decision makers, aside from its own baseline sales, is market growth (economic and/or demographic). The breakdown approach is useful for determining sales force size, but do not depend only on last year’s average sales per person as a benchmark for future sales needs. As business grows, companies seek to improve both efficiency and effectiveness, which includes establishing growth targets for existing salespeople. The example in this chapter simplifies a common sales management challenge: how to inspire the sales force to achieve these new growth targets yet not demotivate them by being overly aggressive. The breakdown approach might lure sales management into the comfortable world of maintaining existing sales standards ($1 million of sales per person in this case). While the field sales force may find the new goals a relief, since they

Impact  

only have to maintain the same level of sales as last year (it is the number of new representatives hired that drives growth in this case), it offers little long-term challenge, and the risk of complacency grows over time. Conversely, if the same 100 salespeople are asked to achieve the new $120.75 million target, then the 21% sales increase required may be too formidable, leading to reduced motivation. Sales management must look at the factors contributing to the projected sales increase. Sales data for the previous year’s sales is found in the annual report. Expected market growth can be obtained from economic forecasts for the given company’s specific industry. And projected customer growth can be learned from market research data including customer survey information. Each of these will affect the sales management’s decision on the right balance between sales force size requirements and projected sales growth.  Va-Interactive, Conduct a Sales Forecast, N.D. Retrieved June 5, 2017 from http://www.vainteractive.com/inbusiness/editorial/sales/ibt/sales_fo.html; J. Evetts, Seven Pillars of Sales Success (Sterling Publishing Co., 1990); D. H. Bangs, Jr., The Start Up Guide (Upstart Publishing Co., 1989); R. L. Leza and J. Placencia, Develop Your Business Plan (The Oasis Press, 1988); D. H. Bangs, Jr., The Market Planning Guide (Upstart Publishing Co., 1998); I. Burstiner, The Small Business Handbook (Simon & Schuster Inc., 1997); P. Resnik, The Small Business Bible (John Wiley & Sons, Inc., 1988). i

Chapter 99 Workload Approach Measurement Need To determine the right size for the sales force based on the amount of work expected.

Solutioni The workload approach organizes customers into common groups, usually based on account size. Management then determines how many salespeople are required to call on the various customer groups.1 There are three workload approaches that will be discussed here.

Approach 1ii The workload approach calculates sales force size as follows:

SFS =

SE SEaps

Where SFS = sales force size SE = total selling effort needed (total calls to be made) SEaps = average selling effort per salesperson (average total calls made per salesperson) Network marketing companies offer a useful illustration of this workload approach. Networked marketing companies generate sales through large networks of independent sales representatives. Each sales representative generates their income from a combination of product sales and the sales from other representatives they have recruited into their organization (this recruited organization is also known as the downstream sales team). Let’s assume that a hypothetical sales representative named Barbara has identified 3,000 new customers in her territory who she wants to reach in the next thirty days to achieve her sales objectives. She must now determine the number of salespeople required. First, Barbara would outline the facts as she knows them:

  Chapter 99: Workload Approach Total number of customers = 3,000 Duration (in days)

= 30

Next, she needs to determine the denominator (average selling effort per prospective salesperson) by dividing the number of customers to be reached by the number of days required:

Total selling effort needed Number of days required 3000 30 = 100 calls

=

Finally, Barbara can now determine the number of salespeople she needs by dividing the total selling effort needed by the average calls made per salesperson:

Total selling effort needed Average calls made per salesperson 3,000 100 = 30 salespersons =

From a practical point of view, it is likely that not all of Barbara’s new hires will stay the entire thirty days (perhaps due to the type of work, challenges with customers, or finding another job). She should factor in a turnover rate to ensure she can get the equivalent of thirty salespersons’ work for thirty days. Each industry turnover rate differs, but Barbara determines that 20% is normal for network marketing. Therefore, her calculation is refined: = 30 × .20 = 6 (added to the original forecast of 30 people) = 36 total salespeople required

Approach 2iii A slight variation on the first approach is outlined in the sequential steps below: 1. Identify the total number of calls needed or customers to be reached (3,000, in Barbara’s case)

Solution  

2. Determine time needed per call (roughly 1.6 hours per call in this case, derived from 100 calls per sales person divided by 20 days in a working month, assuming an 8 hour day) 3. Determine total working time (a × b) (4,800 hours in this case) 4. Determine actual selling time available per salesperson (160 hours based on 8 hours per day × 20 days) 5. Determine number of salespeople (c ÷ d) (4,800 ÷ 160 = 30) Once again, Barbara would want to consider a turnover rate.

Approach 3iv An alternative workload method is known as reach-frequency, and it is represented by the following:

FTE =

reach × frequency capacity

Where FTE = full time employees reach = how many customers need to be reached frequency = customer visits during the sales period Let’s assume that Barbara and her team have identified 10,000 potential customers in four different segments (see Table 99.1): Table 99.1: Reach and Frequency Example Customers

Reach

Frequency

Calls

Segment 

,



,

Segment 

,



,

Segment 

,



,

Segment 

,



,

Total

,

,

The average sales representative has a total sales capacity of 100 calls (20 selling days × 5 calls per day). Sales representative capacity

 calls

  Chapter 99: Workload Approach Using the formula, we can determine the needed sales force:

15,500 100 = 155 sales reps needed

FTE =

Clearly, Barbara’s sales force needs have changed, but so too have the assumptions. The first two approaches assumed one call per potential customer, but not all customers will buy on the first contact. In fact, most will not. The reach-frequency method provides more guidance when the assumed number of customer visits before a sale is made is larger than one. Of course, the numbers from the previous two approaches can certainly be used to illustrate Approach 3: Customers

Reach

Frequency

Calls

Segment  total

,



,

3,500 100 = 30 sales reps needed

FTE =

Impact Sales plans usually include a projection of the total work required to achieve a goal. The challenge lies in the cost of reaching the goal: salespeople are expensive. The leaders of a business want to keep costs low to maximize profits while also maintaining good relations with customers. It can be a vexing challenge. The workload approach is useful, particularly with less complex, higher-volume products such as consumer goods, since established practices and expectations exist between product manufacturers, sales reps, and customers (whether consumers, in the case of network marketing businesses; or channel accounts, in the case of traditional consumer products distribution). The reason is that metrics exist from years of industry practice and management can approximate the number of customers they need to reach to achieve a certain level of dollar sales. The workload approach becomes more challenging with more complex products (e.g., industrial machinery and software technologies) since achieving the sales objective depends on qualitative factors such as the depth of the relationship with the customers and the amount of customization required to complete a sale. These variables that are hard to pin down numerically but are nevertheless important in this type of sale. Also, the workload approach focuses only on the costs (or investment) made, and not the return. More complex management issues such as pricing, marketing communications and promotion programs, market share

Impact  

goals, and training expenses are ignored. Sales management must also consider these factors when determining sales force sizing.  i Jean-Patrick Tsang, Sales Force Sizing Strategy, Bayser Consulting, January 2002. Retrieved May 24, 2017 from http://www.bayser.com/SalesForceStrategy.htm; Sales Force Management, Workload Method-Sales Force, December 18, 2007. Retrieved May 24, 2017 from http://salesforcemanagement.blogspot.co.za/2007/12/workload-method-sales-force.html; SMstudy, Effective Methods of Determining Sales Force Size, March 17, 2016. Retrieved May 25, 2017 from https://www.smstudy.com/article/effective-methods-of-determining-sales-force-size ii Determination of Sales Force Size. N.d. Retreived May 25, 2017 from http://vle.du.ac.in/mod/book/print.php?id=10235&chapterid=17010 ; SMstudy. Effective Methods of Determining Sales Force Size. March 17, 2016. Retrieved May 25, 2017 from http://www.smstudy.com/article/effective-methods-of-determining-sales-force-size ; iii Determination of Sales Force Size. N.d. Retreived May 25, 2017 from http://vle.du.ac.in/mod/book/print.php?id=10235&chapterid=17010 iv Jean-Patrick Tsang, Sales Force Sizing Strategy, Bayser Consulting, January 2002. Retrieved May 24, 2017 from http://www.bayser.com/SalesForceStrategy.htm;; Mike Periu. How to Calculate the Size of Your Sales Force. Open Forum. June 13, 2011. Retrieved May 25, 2017 from https://www.americanexpress.com/us/small-business/openforum/articles/how-to-calculate-thesize-of-your-sales-force/ ; Determination of Sales Force Size. N.d. Retreived May 25, 2017 from http://vle.du.ac.in/mod/book/print.php?id=10235&chapterid=17010

Chapter 100 Sales Performance Quotas Measurement Need To understand how to structure sales quotas.

Solutioni The following methods are useful guidelines for establishing sales volume quotas: 1. Last year's total company or territory sales numbers by product or customer 2. Last year’s salesperson's sales numbers by product or customer 3. Sales costs times a multiplier ( x 3, for example) 4. Corporate general administrative costs plus a gross margin 5. Revenue goals committed to industry analysts or shareholders 6. Total of the sales team's goals (by territory, product or customer) divided by the number of salespeople 7. Estimated income potential provided to the salesperson if he/she achieves 100% of their quota 8. Analyst’s projected annual growth rate for this industry for this year (for example, if the analyst forecasts industry growth of 20%, then quotas are up 20%) 9. Vice President of Sales' experiences at other companies 10. A percentage of the top salesperson’s performance in their territory To illustrate the first method listed on the previous page, let’s look at the sales revenues by quarter for Procter & Gamble in 2016 and 2017:2 Period ending

//

Revenues ,,,

//

//

//

,,,

,,,

,,,

If Procter & Gamble were to use volume quotas to guide its salespeople, then these quarterly revenue figures would be further divided by region and/or product group and/or customer type. The sales representatives would receive a quota for the new planning year based on these figures from 2016/2017, plus percentage increases described by the company’s growth plan. This example uses dollars as the standard measure.

  Chapter 100: Sales Performance Quotas

Impact The sales management plan flows directly from the corporate strategic plan and key marketing objectives. For example, the corporate strategic plan may set product innovation as the primary objective. Marketing would develop its customer development plans based on the corporate objective. In this case, marketing would target early adopter customers who find innovative products appealing. Sales would then identify specific customers who are the closest fit to the corporate and marketing profiles. When the targets are achieved, sales representatives receive compensation above and beyond their base salary. Planning assumptions are important when developing sales volume quotas. Reflecting on the Procter & Gamble example, if the company does set future quotas based on last year’s sales plus percentage increases based on the company growth plan, then it assumes the salesperson has maximized the potential of his/her market the previous year. In Table 100.1, the salesperson exceeded their one-year target of $1.2 million by $150,000, achieving 113% of their quota. Table 100.1: Shows the Percent of Quota Achieved Quota

One year target

Actual

Quota % achieved

Sales volume ($)

$,,

$,,

%

However, the salesperson may be an underperformer in a territory with significant potential. Therefore, using last year’s performance plus expected growth may still not realize the full potential of the territory. Sales management must work directly with the sales representative to develop quotas based on the territory’s true potential. Sales quotas are most effective when salespeople are directly involved with sales management in their own goal development. Setting goals with management allows the salesperson to provide and receive direct feedback on their past performances, and provide their insights to sales management about the unique characteristics of their territory. Individual sales quotas are less effective in team selling situations since cooperation may be hindered by each salesperson’s individual performance goals. Team volume quotas are feasible, but require a clear agreement among the sales team members that success is based on their combined effort, irrespective of imbalances in individual contribution. However, contribution imbalances are likely in team situations since each person has a different point of view on how best to achieve an objective, and therefore team volume quotas may be short-lived since one or more members of the team may feel they were undercompensated for their contribution. Sales

Impact  

volume quotas are less effective with large-scale industrial sales such as heavy equipment or complex enterprise software because the sales cycles are unpredictable and quite long. Products with extreme pricing variation are harder to measure using sales volume quotas since market conditions may make early planning assumptions invalid at the time of the actual sale. Finally, sales volume quotas reward activities related to selling. Nonselling activities such as planning, proposal development, and customer support programs are usually ignored.

Addendum 1: The Unit Volume Quota The performance expectations of sales representatives selling high cost products such as computer hardware, complex enterprise software, or products with significant pricing variation are measured more effectively with a unit volume quota. For example, if a sales person sells fifty units of a product priced at $10,000 per unit, then $500,000 is the total sales figure. But if the price increases 20% to $12,000 per unit (perhaps due to the increase in price of materials or similar sources of supply price changes), then only forty-two units are sold at the same dollar volume. Quota

One year target

Actual

Quota % achieved

Unit volume





%

If the objective of the salesperson is to sell fifty units, then his/her challenge is to achieve that target irrespective of price. A unit volume quota shifts the emphasis to features and benefits that solve the customer’s problem so that price becomes secondary. It also forces a change in the salesperson’s behavior. Addendum 4 at the end of this chapter discusses activity quotas, which establish performance goals for activities related to improved performance in revenues, profits, market share, product volume, territory development or customer acquisition, and retention.

Addendum 2: The Point-Quota System Point-quota systems set targets based on accumulating a certain number of points and not dollars or units. Point quotas reward sales representatives for selling certain combinations of products, dollar volumes, or units. For example, sales management may award five points for new products, three points for upgrades, and two points for legacy products to encourage new product placement. Management may also award points for certain levels of dollar or unit sales achieved. Or, management might convert new product, dollar, and unit sales into points.

  Chapter 100: Sales Performance Quotas Point systems are useful when management wants to change the behavior of sales representatives that are meeting their quotas through the sale of one or two key products that are easier to sell, downplaying other products as a result. Senior management would assign more points to products that need greater placement in the market. Alternatively, if profitability needs to be improved, then points can be assigned to those products with higher relative profitability. To illustrate, we can look at a variation of the tables used earlier and assume that Procter & Gamble’s management wishes to improve sales of products A and B because they are more profitable than products C and D, which are less profitable but easier to sell. Furthermore, P&G management decides to award 1 bonus point for any sales over quota. Tables 100.2 and 100.3 show the respective performances of two different sales reps. Table 100.2: Sales Rep 1 Quota

One year point target

Actual

Quota % achieved

Bonus points

Product A





%



Product B





%



Product C





%



Product D





%



.%



Quota % achieved

Bonus points

Table 100.3: Sales Rep 2 Quota

One year point target

Actual

Product A





%



Product B





%



Product C





%



Product D





%



.%



In the point system, senior management will reward the first sales rep more favorably than the second sales rep, even though the second sales rep achieved 157.5% of quota versus the first sales rep’s 119.5%. The first sales rep earned her bonus by beating her quota with the harder-to-sell products that are also more profitable. Point-quota systems have the advantage of forcing sales team attention to focus on products management seeks to sell, but the disadvantage of growing complexity as a company’s product offering expands into multiple lines and product pricing levels.

Impact  

Addendum 3: The Profit Quota Whereas the point-quota system helps focus sales’ attention on management’s product mix priorities, the profit quota pushes sales representatives to achieve predetermined profits for each product’s sales volume. Profits are defined on either a gross margin or contribution margin basis. Gross margin is the difference between net sales (gross sales less returns, discounts, and allowances) and the cost of goods sold (expenses associated with producing the product, including labor, raw material, overhead). Contribution margin is defined as the sales price minus the variable costs. The profit quota approach works best when sales representatives have some influence over final pricing. P&G’s actual 2016/2017 gross margin was just under 50%, so the profit quota would set a gross margin target of approximately 50% for each product. In our earlier table, products A and B have higher profits; therefore, management might set a gross margin target of 60%. Products C and D might have a gross margin target of 48%. The goal is to meet or exceed each gross margin target. If this is done, then a bonus is paid.

Addendum 4: The Activity Quota A firm’s senior management sets performance targets that include specific financial, market, and product objectives. These objectives are then translated into specific targets for their respective areas of responsibility. Each salesperson is rewarded based on achieving the specific targets set for them. Senior management needs a tool that motivates salespeople to pursue the right activities so that the goals are reached. Activity quotas are a good tool for motivating salespeople to plan the specific activities that will lead to improved performance in their territory. Sales management must establish activity quotas that set proper expectations for their sales team. Activity quotas include: – Total number of calls to new and existing customers per period of time – Total number of letters sent to prospective customers – New account calls – Product displays – Account meetings with loyal customers – Additional product and support services presentations to customers – Internal account update meetings – Coordinating product installations – Account coordination meetings with strategic partners – New proposals

  Chapter 100: Sales Performance Quotas Activity quotas are intended to guide specific behaviors that will ensure the performance targets are met. Sales management must define the most important activities their sales representatives perform, from which specific activity targets are set. If the right behaviors and activities are identified and measured, then salespeople should have a clear picture of senior management’s expectations and an equally clear sense of those activities that do not conform to senior management’s expectations and, therefore, should be avoided. In Table 100.1, the rep achieved 113% of their quota based on sales volume quota setting. Table 100.4 illustrates how activity quotas can provide a clearer picture of the sales representative’s performance. Table 100.4: Table Including Activity Quotas Quota

One year target

Actual

Quota % achieved

Sales volume

$,,

$,,

%

Product demonstrations 



%

Average calls per week



%



%

Average

%



New accounts per month 

Sales management would review this performance with the rep to improve the weaker activity areas. Since the sales volume quota was exceeded while the other activity areas underperformed, sales management would want to establish more aggressive sales volume targets as well. Activity quota achievement is determined from the sales call reports of each sales representative, which places responsibility on the salesperson to accurately record the results of customer meetings. Sales management may occasionally audit the data from these reports by calling the customers directly to verify the information. However, audits can send a demotivating signal that conveys a lack of trust between sales management and the sales representatives.

Impact Sales management establishes quotas that serve as revenue targets for each sales representative. The quotas apply to one or more growth objectives: geographic territories, product sales, and/or number of customers, and are measured in dollars or units. Sales volume quotas are a common toolset for companies of all sizes because they guide salespeople on where to apply their effort, motivate them to perform, and serve as benchmark standards for performance evaluation.

Impact  

Each quota system in this chapter provides management with a method for achieving a particular result. However, setting quotas is complex since most businesses do not face uniform markets with consistent customer demands and clearly delineated competitor offerings. Therefore, companies may employ multiple quota methods even for the same product simply due to differences across territories. Each sales rep’s territory is likely to differ on multiple dimensions: – maturity of the local market; – popularity and reputation of your products versus those of the competition; – number of qualified customers; – economic characteristics of each market; – sales potential of each territory; and – financial targets for each territory. Finally, even with sound quota systems, sales representative performance also depends on softer abilities like motivation, confidence, and desire. Setting quotas for these intangibles is not possible, but their influence in successful selling is well-researched and should be carefully factored into each rep’s individual performance plan by sales management.  Bob Marsh, Do You Manage Sales Quotas or Sales Performance? Leveleleven, March 4, 2015. Retrieved May 23, 2017 from https://leveleleven.com/2015/03/do-you-manage-sales-quotas-orsales-performance/; Steve W. Martin, The Twelve Sales Metrics that Matter Most, Harvard Business Review, December 9, 2013. Retrieved May 23, 2017 from https://hbr.org/2013/12/new-insight-intokey-sales-metrics; Bryan Philips, Setting Quotas & Targets for the High Performance Sales Teams, Performance Center, September 21, 2016. Retrieved May 23, 2017 from https://www.performancecentre.com/quotas-for-high-performance-sales/ 2 Income Statement, Procter and Gamble, Yahoo! Finance. Retrieved May 23, 2017 from https://finance.yahoo.com/quote/PG/financials?p=PG i

Chapter 101 Average Sales Per Call Measurement Need To measure how much each sales person generates in dollars per call.

Solutioni Average sales per call measures the value in dollar sales arising from each sales call. The formula is:

SPC = avg Where

Tsalest × 100 Tcallst

SPCavg = average sales per call Tsalest = total sales in time period t Tcallst = total calls in time period t A small, upscale hotel company has a sales team that consists of two salespeople per property for each of the five properties belonging to the company. Each salesperson is responsible for group business (“group” is defined as ten or more rooms). Most of the salespeople conduct their own customer research and cold calling. The average number of sales calls (cold calls included) in a five-day work week is seventy-five, and the average total group sales per sales rep per week is $20,000. Therefore, the average sales per call is $267:

$20,000 × 100 75 = $267

= SPCavg

Each call generates $267 in revenue.

Impact A quick review of these numbers will suggest that not every sales call results in revenue being generated. Instead, only a few of each week’s seventy-five calls lead to group books, usually four to five. Assuming five bookings is the average number of

  Chapter 101: Average Sales Per Call bookings per week, then the average sales-per-booking is $4,000, a more reasonable result given the price of rooms, length of stay, and size of groups. Average sales per call helps sales management understand each salesperson’s performance both individually and compared to other sales people. Over time and repeated measuring, performance patterns will emerge that will guide future sales management decisions on customer account management, territory structure, pricing latitude, and target segments. Knowing the average sales per call will also help sales management understand the strengths and weaknesses of each salesperson with respect to the kinds of customers being contacted, thereby aligning account assignments more effectively in the future. Data for average sales per call is in the sales and business development reports that track prospects and customers.

 i David Carnes, How to Calculate Sales Productivity, Chron, N.D. Retrieved May 22, 2017 from http://smallbusiness.chron.com/calculate-sales-productivity-11118.html; Turaj Seyrafiaan, Effectiveness Indicators—Revenue/Call, Sales/Call, The Taylor Reach Group Inc., 2011. Retrieved May 22, 2017 from https://thetaylorreachgroup.com/effectiveness-indicators-revenuecall-salescall/

Chapter 102 Close Process and Close Ratio Measurement Need To evaluate each salesperson’s performance.

Solution Two tools are useful in measuring the sales close: 1. The close process 2. The close ratio

The Close Process Historically, there are several known variations on the typical sales cycle process, including AICP (awareness, interest, conviction, purchase) and AICTR (awareness, interest, conviction, trial, repeat). As sales have grown in sophistication, so too has the close process and, consequently, the steps involved in the time to close. This is represented in Figure 102.1.i

Figure 102.1: Interest in the Events in the Sales Process Over Time

  Chapter 102: Close Process and Close Ratio Figure 102.1 graphically portrays common steps in the sales process, from initial targeting to close. Each step is labeled across the top and the accompanying percentage indicates the likelihood of the sale being concluded at that stage. Within each step are many of the probable activities that occur in that stage. The percentages and activities listed are purely for illustration and each sales management team and rep will have a better understanding of each stage’s needs for their own situation. The bell curve illustrates the intensity of effort, which reaches its peak in the presentation and proposal stages, where a great deal of effort has gone into preparing these critical phases. Assuming the customer remains interested, the sales effort shifts toward concluding the sale (and minimizing any last minute obstacles). The chart is not meant to imply that the salesperson loses interest as the sale approaches the close phase. Instead, it merely reflects the changing intensity of effort and not a diminishing of interest.

The Close Ratio At any given time, a salesperson will have multiple simultaneous customers, each at different stages of the close process. As the salesperson and customers move through the stages, each increases their commitment to the effort and reduces the chances of canceling before the close. To get to this stage, salespeople either directly cold call customers themselves, or cold calls are conducted on their behalf by a telemarketing team. Either of these identifies and separates those customers worthy of pursuing from those no longer of interest. As the salesperson and their customers enter this cycle, not all customers will complete it. Therefore, the salesperson and sales management are interested in the percentage of customers that close once they enter the close process cycle. This is expressed as follows:

CR =r

Cat × 100 Cpt

Where CRt = close ratio in time period t Cat = actual sales closed in time period t Cpt = potential sales to close in time period t Let’s assume that a salesperson for a medical devices company has twelve potential customers per month over the course of a year. On average, seven customers per month complete the process to close. This sales person’s close ratio is 58%:

CR =r

84 × 100 144 = 58%

Impact  

Impact In pursuing sales, the salesperson is interested in closing (concluding) sales as quickly as possible and with maximum financial benefit to all stakeholders. The close process is important to understand as it helps the salesperson plan their progress toward the close and, psychologically, it helps them see the progress, providing a form of motivation. For those sales reps who are experts in their industry and understand their customers, they are likely able to estimate the probable length of time of each stage as well. It also enables them to know where each of their customers currently stands in the process, helping the salesperson organize their work effort more effectively, including mapping out which buyers need to be contacted at a particular stage of the process (B2B sales efforts usually involve buying teams, with each person having a different interest). The best salespeople keep detailed notes of each meeting with the customer, so they can identify gaps in their selling efforts to be addressed at the next meeting. The close ratio ultimately measures their success in the close process. Returning to the earlier example, if the salesperson were able to improve the close ratio to eight out of twelve potentials each month, the improvement in their close ratio is significant, plus they have gained twelve additional customers during that same time period, which will improve their future repeat sales business:

CR =r

96 × 100 144 = 67%

By using the close process and close ratio together the sales rep can more easily identify stages where potentials are lost, and use this information to improve their own future sales results, income, and the company’s business.  i K. M. Koenig and M. J. Nick. ROI Selling (Dearborn Trade Books, 2004), 250.

Chapter 103 Cost Per Call Measurement Need To know how much each salesperson’s time is worth and the expense of making each customer contact.

Solution To determine cost per call, the salesperson needs three pieces of data: – sales expenses per time period (usually one year); – total selling days per time period (same time period); and – according to Sales & Marketing Management magazine, the average compensation (base salary plus bonus and commissions) for all salespeople in the United States was US$111,135i This figure is only part of the total sales expense, however. Salespeople incur additional expenses in the course of their annual selling activities, including transportation, entertainment, and support materials expenses. The number of actual selling days is affected by nonselling demands on their time, including training, meetings, vacations, and weekends. A sales professional must budget for each of these components when forecasting their total selling expenses if they want to accurately estimate their cost per call. Table 103.1 captures these additional figuresii and shows that this salesperson’s cost per call is $270.80.

Impact Sales professionals must grow the business by finding new customers and getting existing customers to buy more products. Therefore, they must allocate their limited time toward the best customer prospects. Top sales performers succeed because they rigorously plan their activities to maximize selling time to the right customers. Measuring cost per call enables salespeople to determine the costs incurred to make each sales call. Cost per call is a useful tool in the beginning of any sales plan because it forces the salesperson to think carefully about the many expenses incurred on behalf of each customer sale. However, cost per call is one of several key planning steps. The next several chapters add depth to the sales planning effort.

  Chapter 103: Cost Per Call Table 103.1: Costs of the Salesperson and Cost per Call Compensation Salary, commissions, bonus

$,

Fringe benefits (insurance and other)

$,

$,

Direct selling expenses Automobile

$,

Lodging and meals

$,

Entertainment

$,

Communications

$,

Samples, promotional materials

$,

Miscellaneous

$,

Total direct expenses

$, $,

Calls per year Total available days

 days

Less Vacation

 days

Holidays

 days

Sickness

 days

Meetings

 days

Training

 days

 days

Net selling days

 days

Average calls per day

 calls

Total calls per year ( × ) Average cost per call ($,/)

 calls $.

 C. Galea, “2004 Salary Survey,” Sales & Marketing Management (May 2004): 28. ii Adapted from W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 127 i

Chapter 104 Break-Even Sales Volume Measurement Need To determine the break-even sales volume.

Solutioni The formula for break-even sales volume is common across industries, although the formula’s variables will vary, sometimes dramatically, by industry, and even within an industry.

BEsv = Where

CPC × NCC Cs

BEsv = break-even sales volume CPC = cost per call NCC = number of calls to close Cs = sales costs, expressed as a percentage of sales There are no universal rules governing the number of calls to close a sale. Selling consumer perishables, such as canned foods, is very different from selling mainframe computers. The canned foods salesperson may be able to close a sale in two or three calls since the buyer regularly needs to replenish inventory on store shelves. The mainframe computer salesperson may have five to six meetings, or more, over several months with their buyers before a sale is concluded. Salespeople must be familiar with the performance standards of their industry. Their own experience with customers also serves as a relevant guideline for the number of calls typically needed to close a sale. Sales people must factor in management’s expectations into their break-even analysis. Table 104.1 shows these percentages by industry.ii

  Chapter 104: Break-Even Sales Volume Table 104.1: Sales Costs for Callers as a Percent of Sales Industry

Cost per call (in $)

Number of calls needed to close a sale

Sales costs as a percentage of total sales

Business services

.

.

.%

Chemicals

.

.

.

Construction

.

.

.

Electronics

.

.

.

Food products

.

.

.

Instruments

.

.

.

Machinery

.

.

.

Office equipment

.

.

.

Printing/publishing .

.

.

Rubber/plastic

.

.

.

Using Table 104.1, each industry’s break-even sales volume can be calculated. To illustrate, we look at food products:

$131.60 × 4.8 .027 = $23,396

BEsv =

The food products salesperson now has a minimum performance benchmark that helps him or her target customers more effectively, reallocating time and resources away from those customers who do not meet the standard.

Impact Chapter 103 describes cost per call, a calculation that measures the costs of making each sales call based on projected expenses, selling days and the average number of calls per day. The example in Chapter 103 calculated the cost per call to be $270.80. However, cost per call does not factor in the number of calls required to make a sale. As implied, the break-even point is the minimum customer size needed—any customer sale below break-even should be avoided. Successful sales planning requires sales managers and their team members to carefully evaluate their customers. The break-even sales volume provides a minimum acceptable standard for determining the attractiveness of a customer account. The measure helps salespeople focus on those businesses that represent the best potential, reducing the number of less-attractive customers. Salespeople can then begin the more rigorous phases of their account planning, including profiling each customer

Impact  

account in greater detail and the main buyers within. However, business decisions are usually more complex than this simple illustration. A customer may be below the break-even threshold, yet if their business is growing at an attractive rate (for example, ahead of the pace of their competitors), then management should consider the long-term potential before dropping them. There may also be inefficiencies in the company’s sales force system that, upon correction, may change the break-even calculation and allow more customers to survive. New products may also change the relationship with customers since they may find the new offerings attractive. Even though the break-even threshold is not met due to a product’s newness, the customer’s previously profitable loyalty may suggest that the overall relationship should be nurtured, despite the initially unattractive break-even volumes. Sales professionals have many factors to consider when reviewing their customers. Break-even sales volume is a logical step since it helps focus the sales effort, improving efficiency (since the wrong accounts will not be pursued) and effectiveness (since the salesperson now knows the sales amount required to break-even). The challenge arises from the complexity of other factors that cannot be easily measured, such as long-term potential and ease of account service, yet can have a significant impact on success over the long term. Data for break-even sales volume is located in automated sales software, sales reports, and company financial reviews.  Adapted from W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 126–127. ii From Table 3-2, W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 128. i

Chapter 105 Sales Productivity Measurement Need Sales management needs to know how productive its salespeople are.

Solutioni Productivity can be measured in the following ways: – Sales (revenues) per person (measured in dollars) – Profits per person (measured in dollars) – Volume sold per person (in units) Most sales productivity measures focus on revenues per person. SP =

∑S ∑S

t

p

Where SP = sales productivity ∑St = sum of total sales for all sales people ∑Sp = total number of sales people Assume a company sells real estate data and software to title companies, real estate firms, appraisers, and financial institutions. The company’s revenues are $11 million, generated by seventy-five salespeople. Sales productivity was as follows:

$11,000,000 75 = $146,667 per person

SP =

Management’s evaluation suggested that the competition’s average sales productivity was nearly 80% higher. The senior management team embarked on an aggressive growth plan that included new products and acquisitions. Within two years, revenues had grown to $42 million and the sales team numbered 100. Sales productivity changed as well:

  Chapter 105: Sales Productivity

$11,000,000 100 =$420,000 per person

SP =

Clearly, sales productivity per person improved during that period of time. This provided a key performance measure enabling us to more effectively evaluate our progress.

Impact The results of this analysis will affect decisions at the company, team, and individual level. Sales productivity measurement should inspire deeper analysis into the underlying causes of the performance (whether good or bad). Management decision making will focus more on the questions raised by the detailed sales productivity results which, in turn, are influenced by overall company goals, sales targets, sales territory definition, and segment and account strategies. Company-level decisions are complicated by hard-to-control factors. Assuming sales managers are familiar with their teams, they may conclude that a poor performance as revealed by sales productivity analysis could be due to other, less controllable factors such as unrealistic goals, a weak correlation between pay and performance, or shifting market conditions that affected the assumptions that supported the original sales plan. These must be weighed against sales management’s future compensation plans, sales targets, account objectives and, ultimately, changes in personnel. Sales management will use productivity to understand a sales representative’s individual performance as compared to colleagues or competitors. Marketing can use the results to advise underperformers about more effective segmentation or new segment opportunities. Sales management can also use the results to counsel poor performers in better account selection, time management, and selling strategies for each customer. More specifically, sales managers can use the productivity results to develop a step-by-step plan for improved individual performance. Finally, sales management must be careful not to misinterpret sales productivity data. A handful of top performers may disguise the underperformance of the rest of the team. Therefore, the sales productivity results will need to be viewed across the sales force and at the individual salesperson level. High performers will certainly generate substantial revenues, but if those results were partly secured by offering customers generous, low-cost support contracts, then the financial impact on the rest of the company could be severe. Perhaps the high performers generated strong sales, but also had higher returns due to a less thoughtful selling effort. Or, their significant sales volumes may strain the production and delivery capabilities of the firm, particularly if the revenue growth is sudden and sharp. The outcome could be unhappy

Impact  

customers, which is certainly counter to the purpose of selling and marketing in the first place. Data for sales productivity is found in both regular sales reports and financial review statements.  Jonathan Byrnes, Reconnect Sales Management to Profitability, Harvard Working Knowledge, March 1, 2004. Retrieved May 11, 2017 from http://hbswk.hbs.edu/archive/3952.html; Bill Johnson, 3 Factors to Consider When Measuring Sales Productivity, Salesvue, May 21, 2013. Retrieved May 11, 2017 from https://salesvue.com/how-do-you-measure-sales-productivity/ i

Chapter 106 Four Factor Model Measurement Need Performance appraisal of salespeople is complex. Qualitative influences like attitude, emotional resiliency, and persistence play an important role in selling success, but are difficult to objectively evaluate. While achieving consistently successful sales results is never assured, certain tasks performed by sales people are clear and measurable since they are developed with a specific eye toward growth in revenues, profits, units sold, and number of customers. These tasks are part of the selling routine and include setting personal goals, identifying customer targets, organizing the sales tactics for each customer, scheduling sales calls, closing sales and, finally, following up with the customer after the sale is complete. Since each of these activities yields a clear result, sales management needs a way to measure them.

Solutioni The Four Factor Model evaluates the salesperson’s efforts in four specific areas: – Days worked – Calls/days worked – Orders/calls – Sales $/orders The formula used is:

$ Sales = Days worked ×

Calls Orders Sales × × Days worked Call Order

Let’s look at NWR,ii a hospitality company that owns one resort, plus works in partnership with six regional hotels and resorts, representing a total of 900 hotel rooms. Salespeople are compensated for booking group business, defined as ten or more rooms per night plus one group meal and two coffee breaks during the day (minimum), each day. Table 106.1 outlines the performance of three salespeople.

  Chapter 106: Four Factor Model Table 103.1: Performance of Three Salespeople Criteria

Sales Rep 

Sales Rep 

Sales Rep 

Annual sales

$,

$,,

$,

Days worked







Total calls*

,

,

,

Group bookings







Avg. length of stay (# of nights)



.



Avg. daily rate per person per group

$

$

$

Avg. daily F&B per person per group

$

$

$

Avg. # of rooms







Total calls/total days worked







Bookings/call

.%

.%

%

Sales $/booking

$,

$,

$,

Sales expense (nonwage)

$,

$,

$,

Sales expense per call

$.

$.

$.

Sales expense per booking

$.

$.

$.

Sales expense as % of total sales .%

.%

.%

Four Factor Total**

$,,

$,

$,

Notes: *Calls defined as: telephone, client tours of hotels, visits to client sites. Most calls were by telephone. **Sales Rep 1 = 230 × 12 × .036 × $6,222 = $618,218 Sales Rep 2 = 225 × 15 × .027 × $17,413 = $1,586,760 Sales Rep 3 = 231 × 16 × .030 × $8,313 = $921,745

Impact The Four Factor calculations show dollar sales totals nearly the same as the total annual sales for each salesperson. The numbers are interesting, given the sizable differences between sales reps, but sales management will want to review the performances and their underlying causes with greater scrutiny. For example, Sales Rep 2’s Four Factor results are higher than her annual sales. The most obvious factor is her sales dollars per booking average. Her total dollar per group is larger because the number of rooms her groups book is substantially higher, as is the average length of stay for her groups. Before concluding she is superior, sales management should review her territory, because the customers in her territory may be substantially larger than those of Sales Reps 1 and 3. So Sales Rep 2’s customers may simply book more rooms per group as a result of being larger. Her typical customer’s average length of

Impact  

stay is also longer, which may signal she is more effective at selling hotel space, perhaps by emphasizing unique features that business groups find attractive (such as few distractions and more business services), hence the customers decide that their productivity will be improved by staying one night longer. An examination of each sales rep will be required to determine if changes are warranted, particularly given Sale Rep 2’s performance, or if each is already maximizing their potential given the kind of territory each has. The Four Factor Model provides direction for sales management on where to look next to improve performance. Industrial selling cycles are longer and more complex than their consumer selling counterparts, so each of the Four Factors will have a different baseline performance than that shown in Table 106.1. But the impact on decision making will be similar since sales management will compare the results to other salespeople on their team, or against competitors and/or industry standards.  i W. L. Cron, T. E. DeCarlo, and D. J. Palrymple, Sales Management (John Wiley & Sons, Inc., 2004), 545; Mark Hebner, Profitability and a Four-Factor Model, IFA.com, August 2, 2013. Retrieved May 23, 2017 from https://www.ifa.com/articles/profitability_four-factor_model/ ii Adapted from information provided by Northwest Resorts, Inc.

Chapter 107 Sales Variance Analysis Measurement Need To measure the differences and see where the deviations occurred.

Solutionsi There are several formulas used to calculate sales variances: 1. Sales value variance 2. Sales price variance 3. Sales volume variance 4. Sales mix variance The formulas for each will be outlined below, but for illustration purposes, the focus will be on sales value variance, sales price variance, and sales volume variance (italicized above), since these are three of the most common variables used to assess sales performance. The sales mix variance is best applied to companies with multiple products within several product lines. Readers are encouraged to visit the resources listed for this chapter, should they want more detailed treatments of these formulas. 1.

Sales value variance:

This measures the difference in monetary value between actual sales and budgeted sales (in monetary terms) in time period t (usually one year). SValVt = Sa – Sb Where SValVt = sales value variance during time t Sa = actual sales Sb = budgeted sales If actual sales are more than budgeted sales, then this formula will return a favorable variance. Whether positive or negative, sales managers will want to determine the source of this variance. If the variance is positive, then it is due either to higher actual prices compared to budget, or higher actual volume compared to budget. The converse would be true if the variance were negative. With price as one of the determinants, sales management would now want to measure the sales price variance.

  Chapter 107: Sales Variance Analysis 2. Sales price variance: The sales price variance explains the difference between actual price received and the price budgeted at the beginning of period t. SPVt = Qa(Pa – Pb) Where SPVt = sales price variance during time t Qa = actual quantity sold during time t Pa = actual price per unit Pb = budgeted price per unit Actual price differences result from promotional or volume discounts, allowances, giveaways, or bundled offerings (such as two-for-one deals), all of which are tools used by salespeople to gain a buyer’s commitment. Correspondingly, their use affects the final price received. 3. Sales volume variance: Sales volume variance measures the difference in actual quantity sold during time t versus the budgeted quantity, multiplied by the budgeted price per unit. SVVt = Pb(Qa – Qb) Where SVVt = sales volume variance during time t Pb = budgeted price per unit Qa = actual quantity sold during time t Qb = budgeted quantity sold during time t Sales volume variances are caused by several factors. Changes in price or quality, delivery delays, shifting market trends, and competitor promotions are among the key influences. Marketers and sales management must review sales results closely to understand the source of the variances.

Illustration To illustrate sales value variance, sales price variance, and sales volume variance, let’s assume that Company A sells three products, known as X, Y, and Z, respectively. Company A budgeted the following sales for 2012:

Solutions  

Sales Budgeted for 2012 Product X: 100,000 units sold at $25 each

= $2,500,000

Product Y: 50,000 units sold at $30 each

= $1,500,000

Product Z: 25,000 units sold at $35 each

= $ 875,000

Budgeted sales

$4,875,000

Sales Actual for 2013 Product X: 90,000 units sold at $28 each

= $2,520,000

Product Y: 45,000 units sold at $32 each

= $1,440,000

Product Z: 30,000 units sold at $34 each

= $1,020,000

Actual sales

$4,980,000

The next steps are to examine the sales value, sales price, and sales volume variances. Company A had a favorable sales value variance. In this case, the actual sales of all three products exceeded the budgeted amount by $105,000, shown as follows: SValVt = Sa – Sb SValVt = $4,980,000 – $4,875,000 Sales value variance = $105,000 The sales price variance for each product shows the following: Product X = 90,000 (28 – 25) = $270,000 Product Y = 45,000 (32 – 30) = $90,000 Product Z = 30,000 (34 – 35) = ($30,000) Sales price variance = $330,000 The overall SPV was favorable, whereas Products X and Y had favorable individual SPVs, Product Z had an unfavorable variance. The sales volume variance for each product shows the following: Product X = $25 (90,000 – 100,000) = ($250,000) Product Y = $30 (45,000 – 50,000) = ($150,000) Product Z = $35 (30,000 – 25,000) = $175,000 Sales volume variance

$225,000

  Chapter 107: Sales Variance Analysis The overall sales value variance was unfavorable. Products X and Y both had unfavorable sales value variances, but Product Z had a favorable variance. A quick check of the sales price variance and sales volume variance should verify the sales value variance figure: Quick Check Sales price variance

$330,000

Sales volume variance ($225,000) Total variance

$105,000

The quick check agreed! 4. Sales mix variance: Sales mix variance measures the impact of different mixes of products sold. This is useful for companies with multiple products and product lines where management needs to understand the financial implications to the company of the actual product mix sold versus the budgeted product mix: SMVt = Qt (A% – B%) CMb Where SMVt = sales mix variance during time t Qt = actual quantity (in units) of all products sold [in time t] A% = actual sales mix percentage B% = budgeted sales mix percentage CMb = budgeted contribution margin per unit

Impact Sales managers develop budgets for their business plans that outline how the department’s money is going to be allocated between revenues and costs for a specific period of time, usually for the forthcoming year. Once the year has been completed, the actual financial performance is compared to the original budget. Sales management needs sales variance analysis as the methodology used. Sales variance analysis enables company management to identify the impact of specific variables on overall sales performance. If management reviewed only total sales results, then they would conclude that the business performed better than planned (using this chapter’s example). But the sales variance analysis sheds light on

Impact  

the performance of individual products. Interestingly, Products X and Y had favorable sales price variances, but unfavorable sales volume variances (the actual prices for which the products sold more than offset the lower than expected unit sales). Conversely, Product Z had an unfavorable sales price variance due to the lower actual price for which products were sold versus budget, but it also had a favorable sales volume variance. Company management would want to carefully review the reasons for these performance swings. All three products are somewhat price elastic, meaning that customers are sensitive to price changes. Perhaps the competition offers equivalent Products to X and Y, but at better prices. Therefore, management might consider either improving product quality or finding ways to reduce costs. The small price decrease for Product Z (less than 3%) led to a 20% increase in units sold (30,000 actual vs. 25,000 budgeted) and a positive sales volume variance of $175,000. Furthermore, Product Z’s actual sales were $145,000 higher than budgeted ($1,020,000 actual vs. $875,000 budgeted), a 16.6% increase in sales. For Product Z, the 3% price decrease resulted in a disproportionate, positive percentage increase in sales volume variance and actual sales. Sales management would want to analyze these results more closely to better understand why Product Z’s results were superior to those of Products X and Y and determine whether similar results might be replicated in the future. There are many reasons for these results beyond the simple explanations offered here. Sales variance analysis provides meaningful insight into your businesses performance. While it raises more questions for management, it also offers guidance on where to look for the answers.  G. J. Steven, Sales Variances: Time for the Hard Sell? Napier University, N.D. Retrieved May 15, 2017 from http://www.cimaglobal.com/Documents/ImportedDocuments/CI_Sept_00_p23_24.pdf; Cynthia Hartman, Sales Variance Analysis, Chron, N.D. Retrieved May 26, 2017 from http://smallbusiness.chron.com/sales-variances-analysis-24147.html; Tutorsonnet, Sales Variances, N.D. Retrieved May 29, 2017 from http://www.tutorsonnet.com/sales-varianceshomework-help.php i

Chapter 108 Sales Volume Variance Measurement Need To measure the impact from volume changes.

Solutioni Sales volume variance is calculated by: SVVt = SQVt + SMVt Where SVV = sales volume variance in time period t SQVt = sales quantity variance in time period t SMVt = sales mix variance in time period t To solve, the marketer first needs to solve for SQV and SMV. These are calculated as follows: SQVt = PPPSt – EPASt Where SQVt = sales quantity variance in time period t PPPSt = projected profit based on projected sales in time period t EPASt = expected profit from actual sales in time period t* *Note: This is calculated as though profit increases or decreases proportionally with changes in the level of salesii

SMVt = EPASt – PPASt Where SMVt = sales mix variance in time period t EPASt = expected profit from actual sales in time period t

  Chapter 108: Sales Volume Variance PPASt = projected profit from actual sales in time period t**

**Note: The sum of projected profit from all units soldiii

Returning to Glob Toys from Chapter 43, we can now compute the results: SQVt = $400,000 – ($990,000 ÷ $1,000,000 × $400,000) = $4,000 SMVt = $400,000 – (120,000 × $2) + (50,000 × $4) = –$40,000 Solving for the sales volume variance: SVVt = $4,000 + (–$40,000) = –$36,000

Total sales variance Using the results from Chapter 43, the marketer can now calculate their total sales variance: TSVt = SPVt + SVVt = –$190,000 + (–$36,000) = –$226,000

Impact Chapter 107 discussed sales price variance, which helps marketers understand how price changes impact actual sales. Volume changes also have an important impact, and this needs to be measured. Several factors affect sales volume variance: 1. Customer needs changed resulting in an increase/decrease in quantity ordered 2. Unexpected cost increases forced an increase in price during time period t 3. Competitors introduced a new product that attracted customers away 4. Production delays forced competitors to cancel commitments

Impact  

The implications differ for each of these factors and marketers will need to adjust their plans accordingly to ensure their products perform closer to expectations.  i C. Gilligan, and R. M. S. Wilson, Strategic Marketing Management: Planning, Implementation & Control (2005), 781–783; Accounting Explained, Sales Volume Variance, 2011–2013. Retrieved June 3, 2017 from http://accountingexplained.com/managerial/standard-costing/sales-volume-variance ii Ibid. iii Ibid.

Chapter 109 Sales Enablement Measurement Need To determine how effective salespeople are at doing their jobs and getting the work done.

Solutioni Sales enablement is a comparative measure, assessing if there is improvement in a targeted sales capability arising from new training, practice, and/or more deliberate focus. Determining effectiveness is based on leading and lagging indicators: – Leading indicators are measurable variables that provide a clearer line of sight to future performance: o Example: sales training programs that upskill the field sales force to a recognized industry certification. If the entire sales force undertakes this training, then it indicates the likelihood of improved sales success in the future based on the company’s performance indicators. – Lagging indicators are measurable variables that change due to external factors, trends, and market signals: o Example: growth in average customer size and/or growth in existing customer share of wallet arising from the salesperson’s heightened awareness of trends that might impact their customer’s business and, therefore, enables the salesperson to tailor their solutions more specifically to the anticipated customer need. Other measures that help determine sales enablement and sales effectiveness:ii – Lead to customer conversion rate – Win/loss rate against key competitors – Website downloads of key sales people’s thought leadership white papers and articles that inspire customers to purchase – Net Promoter Scores (NPS), which asks users whether they would recommend the company, salesperson, and/or solutions in the future based on current experience.

  Chapter 109: Sales Enablement

Impact Selling is resource intensive, requiring people, time, and capital investment in training and support solutions. Every salesperson hour is expensive, so providing the proper training, certification, and similarly related professional tools will give salespeople a better chance to use their limited time effectively.  Accent, What Is Sales Enablement? A Modern Definition for B2B Sales. Retrieved August 2, 2017 from https://accent-technologies.com/blog/2015/12/15/what-is-sales-enablement-a-moderndefinition-for-b2b-sales/; Eric Estrella, How Do You Measure Sales Enablement? Sales Benchmark Index. Retrieved August 2, 2017 from https://salesbenchmarkindex.com/insights/how-do-youmeasure-sales-enablement/ ii Debbie Farese, 9 Smart Ways to Measure Your Sales Enablement Efforts, Hubspot. Retrieved August 2, 2017 from https://blog.hubspot.com/marketing/measure-sales-enablement i

Chapter 110 Net Promoter Score® Measurement Need To understand whether the targeted stakeholder would recommend the company and its solutions to others.

Solutioni The Net Promoter Score® (NPS®) is calculated using a 0–10 scale as shown here: Question: On a scale of 0–10, how likely are you to recommend X (marketer’s company/solutions) to another (friend, colleague, company, etc.)?

The answers are tagged as: – detractors: defined as dissatisfied customers; – passives: defined as indifferent customers; and – promoters: defined as committed/loyal customers.

To calculate:

= NPS

(Promoters − Detractors) × 100 (Respondents)

  Chapter 110: Net Promoter Score® To illustrate, assume marketing had 500 survey responses: – 150 were detractors (0–6 range) – 100 were passive (7–8 range) – 250 were promoters (9–10 range)

= NPS

(250 − 150) × 100 (500)

NPS® = 20

Impact Interpreting Net Promoter Score® results is relative to NPS® scores for organizations in the company’s competitive sector. The very highest score possible is 100 and the lowest is –100. Thus, the result of 20 in the illustration may be either very good or cause for concern depending on competitive data. As described, data for NPS® comes from survey responses as well as industry data reflected in industry trade journals, and/or consulting reports.  i Bain & Company, Measuring Your Net Promoter Score, N.D. Retrieved May 11, 2017 from http://www.netpromotersystem.com/about/measuring-your-net-promoter-score.aspx; SurveyMonkey, Online NPS surveys, N.D. Retrieved May 11, 2017 from https://www.surveymonkey.com/mp/net-promoter-score/; Adam Lashinsky, Survey Monkey Benchmarks Success, April 17, 2015. Retrieved May 11, 2017 from http://fortune.com/2015/04/17/surveymonkey-benchmarking/

Index A ABC (activity-based costing) 88, 93, 94, 194 ABF (Activity-based filtration) 237, 238 Absolute index 295, 299, 300, 303 Accounting 8, 14, 24, 28, 93, 122, 126, 161, 285 Activity quota 329, 331, 332 Activity-based filtration (ABF) 237, 238 Actual price 3, 165, 356, 359 Actual revenues Absolute Index 300, 303 Additional costs 94, 285 Advertising 46, 177, 178, 179, 183, 201, 202, 232, 249 Advertising campaign 179, 183, 185, 188, 201, 249 Advertising-to-sales ratio 176, 201, 202 Airbus 9, 10 Airlines 9, 10, 45 Allowances 153, 156, 158, 267, 309, 331, 356 Annual sales 352 Ansoff 43, 46, 111, 283 Ansoff Matrix 43, 44, 46, 109 AR (Activity Ratio) 239, 240 Asian perspective 46, 161, 164, 178 Assets 25, 26, 28, 46, 72, 278 Average calls 322, 332, 342 Average cost 134, 135, 136, 342 Average customer 134, 137, 259, 260, 261 Average inventory 269, 273 Average retail price 2, 24, 25, 27, 75, 76 Average sales 209, 213, 215, 217, 219, 317, 318, 335, 336 Average transaction size 252, 259, 260 Average Transaction Value (ATV) 260,261 B Behaviors 100, 188, 260, 261, 292, 293, 294, 329, 331 BMW, 35, 76, 78 Bounce rate 221, 247, 248 Brand Ambassador 292, 293 Brand assets 71, 72, 73 Brand awareness 71, 72, 179 Brand contribution and review analysis 64, 81, 82, 84

DOI 10.1515/9781501507304-012

Brand equity 64, 65, 66, 68, 71, 73, 74, 76, 138 Brand image 76, 78 Brand loyalty 71, 72 Brand premium 64, 75, 76, 78, 107 Brand scorecards 64, 71, 72, 74 Brand valuation 64, 67, 68 Brand value 66, 68 Branding strategies 66, 67, 69 Brands 63, 64, 65, 66, 68, 74, 76, 137, 179 Break-even sales volume 295, 343, 344, 345 Budgets 15, 57, 97, 101, 187, 293, 355, 358, 359 Business development costs 50 Business leaders 5, 21, 38, 65, 75, 269 Buyers 101, 119, 254, 269, 281, 282, 288, 294, 343 – actual 119, 196, 255, 281 – total 118, 281 C Calculation 151, 156, 215, 219, 229, 232, 285, 286, 289 California Management Review 204, 205, 206 Calls 323, 324, 335, 336, 341, 342, 343, 344, 352 – total 321, 335, 342, 352 – total number of 322, 331 Campaign 106, 107, 118, 119, 120, 196, 200, 210, 220 Capital, invested 25, 28, 72 Carrying Inventory 272 Cash flow 28, 105, 106, 107, 140 CBV, 137 Charge 3, 76, 110, 114, 186, 236, 237, 286 Churn Rate 89, 125, 126, 127 Clicks 177, 225, 229, 230, 231, 232, 233, 235, 236 Close ratio 213, 252, 281, 295, 337, 338, 339 CLTV, 133, 134, 135 Commissions 235, 306, 309, 341, 342 Committed buyers 129, 130, 131

  Index Company 14, 18, 27, 68, 86, 126, 160, 210, 318 – consumer products 99, 184 – publicly-traded 17, 21 Company finance 164, 178 Company management 310, 358, 359 Company sales 33, 214, 235 Company sales force 309 Company’s ability 23, 25, 27 Company’s business 158, 318, 339 Company’s products 15, 20, 41, 129, 133, 139, 140, 189, 192 Company’s success 31, 33, 155, 157 Competition 9, 15, 44, 46, 144, 146, 157, 161, 254 Competitors 23, 35, 76, 96, 126, 156, 157, 184, 232 Complex products 192, 324 Components 7, 24, 63, 97, 172, 178, 312, 341 Consumer franchise 89, 129, 130, 131 Consumer promotions 205, 206 Consumers 86, 143, 149, 179, 183, 184, 205, 270, 285 Contribution 82, 171, 172, 328 – segment’s 91, 297 Contribution margin 298, 331 Conversion rate 113, 114, 115, 199, 200, 209, 215, 219, 220 Correction factor 134, 136 Cost figures 100, 135 Costs 113, 114, 117, 193, 232, 236, 253, 254, 312 – administrative 47, 49, 118, 119, 309 – carrying 271 – high 254 – higher 110, 126, 253, 254 – indirect 93, 94, 119, 312 – lifecycle 145, 146 – lower 145, 146, 235, 310 – operating 253 – payroll 49, 50 – promotion 99, 204 – retailer’s 289 CPA (Cost per action) 221, 235, 236, 237 CPC (cost per click) 119, 221, 231, 232, 233, 236, 343 CPL (Cost per lead) 89, 117, 118, 119, 120 CPP (cost per point) 193, 194

Credit sales 253, 254 CTR (Click Through Rate) 177, 221, 229, 230 Customer acquisition costs 89, 113, 114, 115, 116 Customer brand value 89, 137, 138 Customer equity 105, 106, 107, 133 Customer inquiries 243, 244 Customer lifetime value 89, 133, 134, 136 Customer losses 89, 139, 140, 141 Customer loyalty 121, 123, 210, 318 Customer profitability 89, 94, 99, 100 Customer relationships 1, 100, 102 Customer segments 37, 91, 95, 119 Customer traffic, hourly 252, 265, 266 Customers metrics 85, 86, 87, 88, 89 D DAC (direct advertising costs) 117, 118, 119 Data drive 211, 214, 216, 218 Departments 29, 93, 161, 293, 312, 316 Direct clicks 225, 227, 229, 231, 232 Direct marketing 196, 207, 209, 210, 211, 214, 215, 216, 220 Direct Marketing Association (DMA) 15, 120 Direct marketing campaign 195, 199, 200, 209, 214, 215, 217, 219 Direct marketing gross profit 215, 216 Direct marketing net profit 207, 215, 217, 218 Direct marketing return 207, 219, 220 Direct marketing revenue goals 207, 209, 210, 213, 214 Direct marketing ROI, 219, 220 Discounts 131, 156, 157, 158, 203, 204, 205, 287, 288 DM, 209, 210, 213, 214, 215, 217, 219 DMA (Direct Marketing Association) 115, 120 Dollars/units 37 E Earnings 17, 18, 19, 20, 125, 273 Earnings-based value 2, 17, 18, 20 Employees 63, 77, 82, 252, 258, 274, 279, 280, 290 – full-time 279, 280 EPASt 361 EPS (earnings per share) 17, 18, 19 Equity 24, 25, 26, 27, 28, 29, 74, 76, 106

Index  

Estimate 134, 136, 147, 148, 160, 161, 185, 241, 242 Expenses 8, 44, 50, 97, 274, 313, 331, 341 Exposure 185, 187, 188, 189, 190, 191, 192 F Factor model 295, 351, 352, 353 Factors 20, 38, 133, 140, 270, 274, 345, 352, 362 Finance 7, 11, 14, 34, 36, 161, 173, 270, 272 Financial performance 1, 7, 18, 27, 29, 136, 278 Financial Times 11, 29, 97 Firms 3, 25, 34, 37, 46, 50, 77 Five Ambassadors 292, 293, 294 Fixed costs 159, 160, 161, 173 – total 171, 172 Focus groups 86, 180, 184, 188 Forecast sales 57, 58, 61 – total 317, 318 Forecasters 52, 53, 58, 60 Forecasting 55, 56, 57, 62, 341 Forecasts 54, 55, 58, 60, 269, 305, 322 – naïve 57, 58 – time series 61 Framework 43, 44, 145, 282 FS, 306, 317, 318 G GF (Good Forever) 19, 20 Ginormatical Fladgits 160 Glob Toys 165, 166, 362 Global Publishing 14, 23, 24, 25, 26, 27 GMROII, 273, 274, 275 Goals 115, 119, 120, 122, 213, 214, 324, 325, 331 – direct marketing profit 207, 213, 214 Good Forever. See GF Goods, markdown 154, 169, 170 Gross margin 273, 274, 275, 327, 331 Gross profit 2, 7, 8, 9, 10, 134, 207, 215, 217 Growing customer value 15, 38, 40, 69, 74, 97, 145, 146, 173 Growth 18, 19, 20, 38, 39, 43, 46, 83, 365 – company’s 17, 37, 38 Growth opportunities 15, 43, 44 Growth rates 18, 28, 68, 133 GRPs (Gross rating points) 175, 176, 189, 190, 191, 192, 193

H Harvard Business Review 26, 29, 46, 94, 100, 111, 123, 136, 141 HCT (hourly customer traffic) 252, 265, 266 Households 147, 148, 185, 189, 190, 191 I, J, K IAC, 117, 118, 119 Income 5, 185, 261, 321, 339 Income statement 14, 24, 26, 29, 97, 100, 136, 164, 202 Increasing net profits 14, 15 Independent sales force 309, 310 Independent sales representative analysis 309, 310 Industry 24, 26, 68, 114, 115, 202, 254, 307, 343 – financial services 180 Industry average 27, 280, 305, 307 Industry standards 305, 307, 353 Information sales people 102 Integrated marketing communications (IMC) 175, 291 Interest 13, 14, 55, 207, 275, 282, 337, 338, 339 Internet 88, 175, 179, 185, 187, 223, 251, 262, 294 Inventory 166, 269, 270, 271, 273, 274, 275, 289, 290 Inventory investment 273, 274 – gross margin return on 252, 273, 274, 275 Inventory levels 169, 271, 290 Inventory turnover 252, 269, 270, 272 Investment 26, 28, 44, 163, 219, 220, 241, 270, 274 Investopedia 5, 8, 15, 24, 26, 29, 270 Investors 17, 18, 27, 28 L Lenovo 151, 152 Leverage 5, 28, 139 Leveraging brand equity 66, 67, 69 Lifetime value 100, 134, 135 – customer equity and customer 89, 133, 134, 136 Locations 87, 99, 115, 118, 187, 192, 256, 289 Losses 83, 107, 139, 140, 204, 205

  Index Loyal customers 15, 65, 133, 134, 135, 136, 196, 200, 210 Loyalty 102, 121, 122, 126, 130, 134, 210, 310 Loyalty cards 135 M MacInnis 66, 67, 68 Mailers 113, 114, 115, 195 Mailings, random 114, 115 Maintenance costs 145 Management 25, 26, 27, 134, 305, 307, 329, 358, 359 Managers 18, 20, 50, 51, 100, 102, 134, 135, 136 Manufacturers 99, 156, 171, 285, 286 Margins 4, 5, 13, 14, 23, 24, 95, 170, 204 Markdowns 169, 170 Market 9, 20, 33, 37, 38, 42, 63, 85, 190 – mass 55, 119, 158 – new 15, 86, 115, 144 – target 38, 42, 46, 149, 185 Market conditions 5, 153, 165, 166, 291, 318, 329 Market demand 13, 17, 31, 39, 40, 54, 61 Market growth 31, 37, 38, 39, 318 – projected 317 Market growth rate 37, 38 Market penetration 31, 41, 42, 43, 44, 45, 46, 109 Market research 55, 86, 97, 188 Market share 33, 34, 41, 42, 43, 44, 101, 152, 155 – relative 31, 35, 36, 37 Market share index 41, 42, 43, 45, 46 Market-based management 24, 26, 29, 38, 40, 69, 74, 145, 146 Marketers 91, 115, 119, 130, 131, 196, 210, 220, 278 – online 229, 262 Marketing 11, 48, 66, 121, 172, 226, 227, 233, 241 Marketing activities 17, 47, 49, 57, 97, 156, 172, 196, 255 Marketing budgets 50, 130, 178, 214 Marketing campaigns 180, 189, 190, 191, 192, 213, 214, 220, 240 Marketing communications 48, 137, 178, 215, 220, 237, 324

– direct 207, 209, 213 Marketing costs 7, 66, 67, 68, 144, 151, 152 Marketing departments 118, 161 Marketing efficiency 50, 68 Marketing efforts 2, 9, 40, 45, 115, 121, 180, 200, 201 – direct 207 Marketing expenses 13, 95, 97, 131, 202 Marketing investments 1, 17, 66, 97, 249 Marketing management 46, 161, 164, 178, 195, 292 Marketing managers 33, 34, 107, 134, 180 Marketing metrics, direct 207 Marketing objectives 191 Marketing pieces, direct 209, 213, 214, 215, 217, 219 Marketing plans 1, 29, 37, 50, 57, 62, 91, 92, 139 Marketing programs 10, 50, 54, 99, 100, 105, 107, 282, 286 – direct 115, 196 Marketing ROS, 95, 97 Marketing strategies 63, 91, 157 Marketing team 50, 209, 213, 215, 235 Marketing terms 181, 194 Marketing tool 210, 281 Mark-up 155, 159, 160, 171 MCPU (marketing cost per unit) 144, 151, 152 MDTS (Milo’s Dog Taxi Service) 129 Measurement 7, 9, 23, 25, 99, 195, 196, 209, 210 Media 31, 115, 175, 178, 187, 191, 192, 193, 201 Media campaign, social 241, 242, 246 Media companies 185, 188, 190 Media vehicle 175, 179, 185, 186, 189, 191, 192, 193, 232 Merchandise 169, 251, 274, 277, 287 Metrics 115, 125, 126, 226, 227, 229, 259, 261, 262 MGP (markdown goods percentage) 154, 169, 170 Milo’s Dog Taxi Service (MDTS) 129 Money 47, 49, 125, 126, 134, 267, 270, 273, 274 Moving average, weighted 58, 59, 60 MSP (manufacturing sales price) 171, 172

Index  

N Net marketing contribution 95, 96, 97 Net profit 13, 14, 15, 23, 24, 25, 26, 27, 217 Net profit before tax (NPBT) 23, 25, 26, 27, 28, 29 Net Promoter Score 84, 295, 365, 367 Net sales 169, 252, 267, 271, 331 – shrinkage to 252, 289, 290 – total 169, 289 Net sales contribution 88, 91, 92, 295, 297, 298 NPS (Net Promoter Scores) 84, 365, 367 O Online 119, 200, 201, 229, 231, 232, 237, 251, 254 Online retailers 209, 261, 262, 263 Operating expenses 8, 13, 14, 217 Operations 8, 15, 25, 93, 135, 169, 252, 257 Owners 27, 118, 129, 257 P Palrymple 307, 310, 316, 342, 345, 353 Pay Per Click (PPC) 177, 178, 233 Pay Per Lead (PPL) 221, 237, 238 P/E ratio 17, 18, 19, 21 PEG, 17, 18, 20 PEG ratio 18, 20, 21 Penetration 46, 137, 147, 148, 149, 153 Penetration rates 147, 148, 149 Perceptions 21, 88, 161, 178, 196, 270 Performance 8, 17, 18, 21, 278, 348, 351, 352, 353 – actuals 60, 166 – baseline 205, 353 – company’s 35, 37 – historical 20, 305 – salesperson’s 295, 336, 337 Period actual 58, 59, 60, 61 Person 185, 225, 226, 293, 294, 318, 347, 348, 352 PICC (Percent inventory carrying costs) 252, 271, 272 PNPR, 47, 48 PPC (pay per click) 177, 178, 233 Premium price 75, 78, 146, 286 Price 75, 153, 155, 156, 157, 158, 270, 329, 359 – budgeted 165, 356

– discounted 203, 204 – final 55, 156, 158, 356 – mark-up 159, 160, 161 – regular 203, 204, 205 – selling 169, 260, 285, 286 Price changes 38, 166, 359 Price promotions 42, 210, 260, 262, 265 Pricing 46, 48, 93, 94, 160, 161, 173, 175, 187 – mark-up 153, 159, 160, 161, 163 – target return 153, 163, 164 Pricing strategies 1, 76, 153, 156, 157, 158, 172, 192 Product sales 3, 91, 286, 287, 293, 321, 330, 332 Productivity 25, 259, 274, 279, 280, 347, 348, 353 Profit goal 213, 214, 215, 217 Profit Impact 171, 172 Profit quota 331 Profit targets 213, 214 Profitability 24, 25, 26, 28, 29, 97, 121, 122, 214 Profits 23, 25, 106, 107, 159, 171, 172, 204, 279 – projected 166, 361, 362 Promotion profit 176, 203, 204, 206 Promotions 78, 131, 203, 204, 205, 258, 260, 262, 278 Q Quotas 291, 327, 328, 329, 330, 332 R Radio 179, 185, 187, 189, 192 Rates 38, 121, 125, 229, 230, 232, 267, 270, 274 Ratio 11, 28, 29, 48, 49, 177, 283 – price/earnings growth 17 – program/nonprogram 31, 47, 48, 49 – value-to-volume 2, 9, 10 Recall 78, 175, 179, 180, 183, 184, 188 Recruiting 295, 311, 312, 315, 316 Reputation 63, 65, 71, 72, 76, 77, 82, 151, 156 – company’s 65, 76, 143, 153 Resolution time 221, 243, 244 Response rate 106, 107, 195, 196, 199, 200, 209, 215, 219

  Index Responsibilities 1, 20, 119, 270, 316, 318, 331, 332 Retail businesses 159, 274, 289 Retail margins 170, 171, 172, 252, 285, 286 Retail price 75, 145, 156, 171, 172, 285, 289 Retailers 99, 169, 257, 265, 274, 277, 285, 286, 288 Retention 126, 134, 253, 329 Retention rate 89, 121, 122 Return on advertising spend 221, 249 Return on customer 89, 106, 107, 108 Revenue targets 40, 209, 210, 211, 213, 300, 332 Revenues 3, 4, 5, 7, 8, 99, 210, 280, 347 – total 8, 13, 37, 66, 68, 81, 99 Review Analysis 64, 81, 82, 84 RI (Relative Index) 37, 295, 303, 304 RMP (retail margin percentage) 252, 285, 286 ROA (Return on Assets) 2, 24, 25, 26, 27, 28, 29 ROAS (Return on Ad Spend) 249, 250 ROCSM (Return on CustomerSM) 105, 106, 108 ROE, 27, 28, 29 ROS, 23, 24, 28, 29, 96, 161 RTS, 267 S Sales 15, 23, 129, 130, 277, 278, 305, 324, 343 Sales & Marketing Management 341, 342 Sales – actual 57, 58, 61, 329, 355, 357, 359, 361, 362 – baseline 204, 205, 318 – budgeted 355, 357 – company’s 33, 101, 280 – field 62, 102, 305, 306, 316 – forecasted 59, 60, 317, 318 – increased 178, 281 – incremental 203, 204, 205 – profitable 270, 274, 277, 285 – projected 165, 317, 319, 361 – return on 2, 23, 24, 26, 28, 161 Sales call 335, 341, 344 Sales contribution, financial 91, 297 Sales costs 343, 344 Sales dollar 14, 15, 23, 252, 253, 254, 352

Sales efforts 97, 339, 345 Sales enablement 295, 365, 366 Sales expense 341, 352 Sales force, dedicated 309, 310 Sales force budget 305, 306 Sales force dollars 305, 306 Sales force size 305, 306, 317, 318, 321, 325 – total 306, 311 Sales force sizing strategy 325 Sales management 299, 301, 307, 310, 316, 328, 332, 348, 353 Sales managers 295, 313, 344, 348, 355, 358 Sales metrics 291, 292, 293, 294, 295, 333 Sales performance 59, 303, 333, 355, 358 Sales performance dilemma 301, 304 Sales person 291, 323, 329, 335, 338 Sales plans 158, 324, 341, 348 Sales price variance (SPV) 153, 165, 166, 355, 356, 357, 358, 362 Sales productivity 295, 347, 348, 349 Sales reps 300, 307, 312, 324, 330, 335, 339, 352, 353 Sales targets 40, 160, 274, 300, 348 Sales team 158, 291, 301, 331, 335, 347 Sales value variance 355, 356, 357, 358 Sales variance analysis 295, 355, 356, 358, 359 Sales variances 355, 359 Sales volume quotas 328, 329, 332 Salespeople 311, 312, 317, 318, 321, 327, 331, 341, 351 Sales/profits 252, 279, 280 Segment profitability 89, 95, 96, 97 Segments 85, 87, 88, 91, 97, 146, 297, 298, 323 Selling 133, 270, 274, 285, 287, 291, 292, 329, 333 Selling effort, total 321, 322 Senior management 48, 85, 102, 163, 195, 236, 240, 330, 331 Services 3, 39, 63, 77, 78, 93, 94, 129, 159 SFB, 305, 306 SFD, 306 SFP, 306 SFS, 306, 317, 321 Share of customer 89, 101, 102, 103 Shoppers 281, 282

Index  

– total number of 282 Shrinkage 252, 271, 289, 290 Smalltownmarketing.com Retrieved 211, 214, 216, 218 SMVt 358, 361, 362 SNS, 289, 290 Social media 84, 88, 221, 239, 240, 242, 243, 245, 249 S-of-determining-sales-force-size 325 Sources 5, 33, 34, 65, 66, 67, 87, 88, 254 SPPE, 279, 280 SPSF (sales per square foot) 252, 277, 278 Stock 17, 19, 27, 261, 270, 271, 274 Strategic marketing management 97, 131, 167, 173, 363 Strategies 24, 26, 38, 40, 68, 69, 145, 146, 282 Suppliers 82, 100, 155, 246, 253, 254, 270, 278, 287 SValVt 355, 357 SVVt 356, 361, 362 T TAC (total advertising costs) 117, 118, 119 Target customers 116, 119, 192, 196, 199, 205, 210, 232, 235 Target marketing 211, 214, 216, 218 Target return price 163, 164 Target segment 41, 45, 336 Tariffs 156, 157 Taxes 13, 14, 24, 26, 28, 29, 129, 156, 157 TDABC (time-driven activity-based costing) 93, 94 Team 4, 110, 287, 291, 300, 323, 328, 348, 353 Television 110, 179, 185, 187, 189, 192, 210 Territory 297, 298, 300, 301, 304, 327, 328, 333, 352 Time period 39, 41, 121, 165, 255, 257, 338, 341, 361 – beginning of 110, 125, 139 Time series analysis 31, 57, 58, 60, 61, 62 Top performers 292, 293, 294, 311, 348

Top sales performers 292, 341 Total inquiry response time 243 Total sales 91, 201, 202, 274, 277, 279, 297, 305, 344 Total sales variance 166, 362 TPC (transactions per customer) 252, 255, 256 TPH (transactions per hour) 252, 257, 258, 265 Transactions 135, 252, 255, 256, 257, 259, 261, 262, 263 – total number of 255, 259, 261 Turnover 269, 270, 311, 312, 313 Turnover rate 295, 311, 312, 322, 323 U Uncommitted buyers 129, 130 Unit price 165, 166, 167 Unit sales 35, 159, 163, 164, 165, 166, 329 Units 33, 35, 151, 163, 171, 204, 329, 356, 357 USC’s Marshall School 66 V Value 17, 20, 24, 26, 65, 100, 133, 145, 204 Variables 46, 48, 51, 52, 54, 57, 139, 140, 203 – dependent 28, 51, 52, 54, 55 – independent 51, 52, 54, 55 W, X Website 223, 225, 227, 229, 231, 232, 235, 237, 247 WOM, 225, 226, 227, 231, 232 Workload approach 295, 321, 322, 324 Www.smalltownmarketing.com/formula.html 211, 214, 216, 218 Y, Z YPEG, 17, 18, 19, 20 YPEG Ratio 18, 20