1.1What Is a Metric?

A metric is a measuring system that quantifies a trend, dynamic, or characteristic.¹ In virtually all disciplines, practitioners use metrics to explain phenomena, diagnose causes, share findings, and project the results of future events. Throughout the worlds of science, business, and government, metrics encourage rigor and objectivity. They make it possible to compare observations across regions and time periods. They facilitate understanding and collaboration.

1.2Why Do You Need Metrics?

“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind: it may be the beginning of knowledge, but you have scarcely, in your thoughts, advanced to the stage of science.”—Lord Kelvin, Popular Lectures and Addresses (1891–1894)²

Lord Kelvin, a British physicist and the manager in charge of laying the first successful transatlantic cable, was one of history’s great advocates for quantitative investigation. In his day, however, mathematical rigor had not yet spread widely beyond the worlds of science, engineering, and finance. Much has changed since then.

Today, numeric fluency is a crucial skill for every business leader. Managers must quantify market opportunities and competitive threats. They must justify the financial risks and benefits of their decisions. They must evaluate plans, explain variances, judge performance, and identify leverage points for improvement—all in numeric terms. These responsibilities require a strong command of measurements and of the systems and formulas that generate them. In short, they require metrics.

Managers must select, calculate, and explain key business metrics. They must understand how each is constructed and how to use it in decision making. Consider the following, more recent quotes from management experts:

“…every metric, whether it is used explicitly to influence behavior, to evaluate future strategies, or simply to take stock, will affect actions and decisions.”³

“If you can’t measure it, you can’t manage it.”⁴

1.3Marketing Metrics: Opportunities, Performance, and Accountability

Marketers are by no means immune to the drive toward quantitative planning and evaluation. Marketing may once have been regarded as more an art than a science. Executives may once have cheerfully admitted that they knew they wasted half the money they spent on advertising, but they didn’t know which half. Those days, however, are gone.

Today, marketers must understand their addressable markets quantitatively. They must measure new opportunities and the investment needed to realize them. Marketers must quantify the value of products, customers, and distribution channels—all under various pricing and promotional scenarios. Increasingly, marketers are held accountable for the financial ramifications of their decisions. Observers have noted this trend in graphic terms:

“For years, corporate marketers have walked into budget meetings like neighborhood junkies. They couldn’t always justify how well they spent past handouts or what difference it all made. They just wanted more money—for flashy TV ads, for big-ticket events, for, you know, getting out the message and building up the brand. But those heady days of blind budget increases are fast being replaced with a new mantra: measurement and accountability.”⁵

1.4Choosing the Right Numbers

The numeric imperative represents a challenge. In business and economics, many metrics are complex and difficult to master. Some are highly specialized and best suited to specific analyses. Many require data that may be approximate, incomplete, or unavailable.

Under these circumstances, no single metric is likely to be perfect. For this reason, we recommend that marketers use a portfolio or “dashboard” of metrics. By doing so, they can view market dynamics from various perspectives and arrive at “triangulated” strategies and solutions. In addition, with multiple metrics, marketers can use each as a check on the others. In this way, they can maximize the accuracy of their knowledge.⁶ They can also estimate or project one data point on the basis of others. Of course, to use multiple metrics effectively, marketers must appreciate the relations between them and the limitations inherent in each.

When this understanding is achieved, however, metrics can help a firm maintain a productive focus on customers and markets. They can help managers identify the strengths and weaknesses in both strategies and execution. Mathematically defined and widely disseminated, metrics can become part of a precise, operational language within a firm.

1.5What Are We Measuring?

Measuring marketing is highly challenging. For example, marketers generally agree that a firm’s brand is a key marketing asset, but different marketers all have subtly different views of what is meant by a brand. It is hard to measure something when you don’t know what exactly you are trying to measure. We, therefore, suggest that the first thing marketers need to establish is a clear definition of what they are trying to measure.

Watt and van den Berg distinguish theoretical and operational definitions in a way that we find useful:

“Concepts represent the ‘real world’ phenomena being explained by the theory. The scientific method requires that the nature of these concepts be unambiguously communicated to others. This requirement mandates the creation of theoretical definitions.…Concepts must also be objectively observed. This requires that we create operational definitions, which translate the verbal concepts into corresponding variables which can be measured.”⁹

The same authors differentiate constructs from concepts, arguing that the former are even more abstract than concepts and cannot be directly observed. They use “source credibility” as an example of a construct that comprises concepts such as expertise, status, and objectivity. Of course, constructs can also be operationalized in a number of ways.

To see what this means, note that marketing has a number of basic ideas that capture real-world phenomena; let us call these concepts. These basic ideas are very important to marketers and can be explained—and even formally defined—verbally. These concepts are, however, not the same as metrics. For example, loyalty is a critical concept for many marketers, but my idea of loyalty may differ from yours. Is loyalty demonstrated when I visit a grocery store every week? What if that grocery store is the only one I can easily get to? In that case, I might not feel loyal to the store, but I still visit it every week. Someone else might feel highly loyal to the same store but live much further away and only be able to visit irregularly. Which, if any, of these consumers are loyal?

We must make concrete our abstract concept of loyalty by providing an operational definition, a precise specification in numeric terms of what exactly we mean. This allows us to create metrics to keep track of how a firm is performing against the operational definitions specified. This book aims to improve measurement validity—how well you translate your ideas into numbers; we do not seek to provide new ways of looking at marketing or argue which concepts are more important than any others.

Some common ways of translating concepts into metrics are shown in Table 1.1.

Keeping a clear distinction between concepts, operational definitions, and metrics is surprisingly hard. In any given marketing team or organization, one can expect to see a certain level of confusion. We hope our book helps reduce this confusion and promote a common language, but we are realists. Indeed, we are happy to acknowledge that we also make mistakes and inadvertently refer to metrics by the name of the concept. We are trying to be clear but please contact Neil Bendle if you see areas where we can improve (just in case there is a fifth edition).

There will continue to be healthy (or at least vigorous) debates in marketing on what should be meant by various theoretical concepts and constructs. However, at the level of measurement and reporting, we believe that the field should be striving for consistency, accuracy, and reliability that allow us to at least understand what other people mean, even if we disagree with what they are suggesting. No shared understanding can happen without clear operational definitions. Providing these definitions is the primary focus of the Common Language Marketing Dictionary. The aim of this project is to improve the measurement of marketing, specifically making measurement in the discipline more consistent. It has been undertaken by MASB (Marketing Accountability Standards Board, www.themasb.org), along with MSI (Marketing Science Institute, www.msi.org), ANA (Association of National Advertisers, www.ana.net), and AMA (American Marketing Association, www.ama.org). We encourage readers to learn more about, and support, the initiative, which can be accessed at marketing-dictionary.org. We add a special plea to any professors reading the book to encourage your students to use the Common Language Marketing Dictionary (for example, by adding a link in any syllabi).

1.6Value of Information

An almost infinite number of metrics could be calculated. Even the most quantitative marketer will recognize that having more calculations doesn’t always help make better decisions. Thus, one question a marketer may want to start with is “When is a metric useful?”

A classic distinction is between data versus information versus knowledge. Data are what we have a profusion of in the world of big data. Data are in raw form and doesn’t tell us anything without being manipulated in some way. Information is data that has been converted into something that can be used by a human reader. Ideally, information gets converted into knowledge when a user understands and internalizes the information. Thus, one way of thinking about the value of information is whether it creates knowledge or not. Data that are simply being stored are not currently valuable but often has the potential to be valuable if approached in the right way. How can we extract the information from the data we have? (Clearly marketers should ensure that they have legal and ethical rights to use the data in this manner. Consent is usually a key consideration, but discussing law and ethics is beyond the scope of this book.)

One way to increase the value of information is to make it easier for users to convert it to knowledge. To do this, we recommend considering how the information you have extracted, such as the metrics you have calculated, can be presented in a user-friendly way. There are now many companies, such as Tableau software (www.tableau.com), that specialize in translating information into visual representations. Such visual depictions are an excellent aid to allowing users to more easily extract the message from the information you provide them.

An alternative way of thinking about the value of information is whether the information helps take an action. Information is valuable only if it allows us to make better decisions. To cast this in terms of metrics, a metric’s value arises from its ability to improve our decisions in some way. Note that this is a very pragmatic approach, as the value of the metric depends upon what the user can do with the result. A chief marketing officer (CMO) might find estimates of the value of the brand she controls invaluable when arguing for increasing the marketing budget with her C-suite colleagues. A more junior marketer, however, may feel that he can’t impact brand value in any significant way, so knowing this number is of no value to him. The more junior marketer can, however, impact whether the product is on the retailers’ shelves and so may find distribution measures invaluable.

A related point is that people sometimes equate the value of information with the range of possible alternatives that the metric can take. Knowing the precise number for a metric that swings wildly can be very informative and thus valuable. If the metric never changes significantly, knowing its precise reading at any given point is unlikely to be very valuable. For example, information on the sales of a fashion item where consumer reaction is unpredictable can be exceptionally valuable for stock planning. Estimates for items with more predictable sales (such as matches) are less valuable because knowing the precise sales number is less likely to change the inventory order you would make without the more refined sales estimate. For items with very stable sales, your estimate based upon last year is likely to be good regardless of whether you calculate the precise metric for this year.

Testing is a critical component of marketing plans, but where should you spend your testing budget? What gives you the most information for your money? Scott Armstrong notes that this depends upon what you are trying to achieve.¹⁰ Sometimes you will want to emulate much academic research and drill down into a very specific topic. This can lead to very consistent estimates, also known as being “reliable.” This means every time you measure, you get a similar result because you measure exactly the same thing each time you measure. In everyday life, the electronic scale that weighs you every morning is reliable, and you generally get the same result if nothing changes. This approach makes sense if it is critical for you to be very precise and if small changes in a metric would radically alter your plans.

More often, however, you aren’t sure you are measuring the right thing. You want to know how the firm is performing generally, but you have a less-than-perfect understanding of what performance means exactly. You might be interested in your general health rather than your precise weight. Your weight is likely to be connected to your general health but is far from the complete picture. In such situations, you are interested in whether the measures you are using are valid and whether the measures accurately capture what you want them to capture. To assess validity, you are likely to want multiple measures, in which case you will spread your testing budget across a wider range of tests and will be more tolerant of conflicting results. To assess your health, you might look at your weight, your blood pressure, your blood sugar, the ease of your breathing, etc. These will sometimes point in different directions, but put together they give a more comprehensive picture than fixating upon a single metric—however reliably the single metric can be measured.

To have valid estimates of hard-to-define concepts, such as performance, we often recommend a variety of tests and the use of multiple metrics. As we will discuss in Chapters 13 and 14, it is often possible to have one metric look very good while the true value of the company is destroyed. Testing multiple different areas and assessing different metrics may give you a less precise picture (it is less reliable) but is much less likely to miss a major problem (it is more valid).

1.7Mastering Metrics

Being able to “crunch the numbers” is vital to success in marketing. Knowing which numbers to crunch, however, is a skill that develops over time. Toward that end, managers must practice the use of metrics and learn from their mistakes. By working through the examples in this book, we hope our readers will gain both confidence and a firm understanding of the fundamentals of quantitative marketing. With time and experience, we trust that you will also develop an intuition about metrics and learn to dig deeper when calculations appear suspect or puzzling.

Ultimately, with regard to metrics, we believe many of our readers will require not only familiarity but also fluency. That is, managers should be able to perform relevant calculations on the fly—under pressure, in board meetings, and during strategic deliberations and negotiations. Although not all readers will require that level of fluency, we believe it will be increasingly expected of candidates for senior management positions, especially those with significant financial responsibility. We anticipate that a mastery of quantitative marketing will become a means for many of our readers to differentiate and position themselves for career advancement in an ever-more-challenging environment.

1.8Where Are the “Top Ten” Metrics?

Working on this book, we received many requests to provide a short list of the “key” or “top ten” marketing metrics. The intuition behind this request is that readers (managers and students) want to be able to focus their attention on the “most important” metrics.

Although some readers may have enjoyed reading the earlier editions from cover to cover, it is safe to say that none of the authors have had that pleasure. We view the book as a reference book—something to keep on the shelf and use when confronted with a new or less familiar metric. The list of metrics covered is therefore long so as to be useful for those occasions. It is not intended to be a guide to the X number of metrics you must apply to monitor marketing. It is this view of the book as a reference guide that helps explain why we do not rate or rank the long list of metrics. We see you pulling the book from the shelf as needed rather than us pushing our preferred metrics upon you.

Specifically, the reasons for us not providing the short list of “really important” metrics are as follows.

First, we believe that any ranking of marketing metrics from most to least useful should depend on the type of business under consideration. Thus, what metrics you prefer depend upon what you need them for. For example, marketers of business-to-business products and services that go to market through a direct sales force don’t need metrics that measure retail availability or dealer productivity.

Second, even what might begin as a short list tends to expand rapidly as metrics come in matched sets. For example, if customer lifetime value is important to your business (let’s say, financial services), then you are also likely to use measures of retention and acquisition costs. The same notion applies to retail, media, sales force, and internet traffic metrics. If some of these are important to you, others in the same general categories are likely to be rated as useful, too.

Third, businesses don’t always have access (at a reasonable cost) to the metrics they would like to have. Inevitably, some of the rankings presented will reflect the cost of obtaining the data that underlie the particular metrics. Some metrics may be interesting to know but are not worth considering if they cost more to obtain than the value of the information and insight they provide. The size of the organization thus matters. Small organizations may use metrics that are cheaper to obtain, whereas larger organizations are more likely to be able to realize the full value from expensive, proprietary, or custom-created metrics. The same goes for stages in the product life cycle. Managers of newly launched products often have different concerns and metrics to monitor them than do managers of mature products.

Fourth, we believe that some metrics currently ranked lower by managers will ultimately prove to be very useful when managers fully understand the pros and cons of a particular metric. For example, for many years, advocates for Economic Value Added (EVA) have argued it is the “gold standard” of profitability metrics, but when we discuss it with many managers, it ranks far below other financial performance measures, such as Return on Investment (ROI). We believe one reason for the low ranking of EVA is that this metric is less applicable at the “operating level” than for overall corporate performance. So even within the same business, depending on where a manager sits in the organization, some metrics are more relevant than others. Also, like EVA, many metrics that we have included are relatively new to marketing, and many managers don’t understand them well or know how they might be relevant to their particular business. Customer Lifetime Value is another metric that is gaining acceptance but is still unfamiliar to many managers. If all these metrics were perfectly understood, there would be no need for a book of this type.

We included the results of our survey of marketing managers in the second edition of this book so that readers could learn what metrics other managers thought were potentially useful. However, we became less convinced that the survey results were useful because metric use and understanding remain an awfully long way from where we want them to be. In the third and fourth editions, we have not included the survey and have instead used the space to explore more metrics.

Here we simply note the key points from the survey. For one thing, managers value the profit-related metrics Net Profit, ROI, and Margin most highly, even though these metrics have less to do with day-to-day marketing decisions. We presume this is because those are the metrics they are asked about by the people who control budgets. Customer Satisfaction was the most popular “non-financial” metric. Sales-related metrics, such as Sales Total, also proved popular.

1.9What Is New in the Fourth Edition?

The fourth edition of this book has significant changes. In addition to reviewing and clarifying the text from the third edition, we have included a number of major additions.

First, we now have a dedicated focus on sponsorship metrics, which we have included in Chapter 10. How much firms benefit from sponsorship is a topic that is both fiendishly difficult to measure and also critical for many of them. One need only think of how much Visa, Coke, and various beer companies invest in their partnerships. Sponsorship is often a strategic decision involving large commitments of resources over extended periods of time, such as when naming a stadium or sponsoring a golf or tennis tournament. We hope that this new edition will positively contribute to bringing more standardization and accountability to sponsorship so marketers can feel more confident in their investments.

Second, we have added sections in Chapter 12 on the interface among financial markets, accounting, and marketing metrics. We have provided this information for marketers who are involved in C-suite decisions or who hope to be in the future. Chapter 12 outlines difficulties in assessing the impact of marketing on the ultimate financial objectives of a publicly listed for-profit firm. We also note challenges marketers face in using financial accounting data for their decisions.

Third, in the 15 years since the first edition of this book was published, “omni-channel” has become a major marketing concept. In a new section, we outline how marketers can measure their activities where there are multiple channels and sources of communication that consumers may access as part of a single purchase decision. We look at channel dependencies, how search and distribution interact, and online distribution metrics. We have broken off distribution measures from sales and created a new Chapter 7 featuring the new metrics.

Fourth, a completely new section of the book outlines changes that have occurred in the world of marketing metrics and accountability. We note progress that is being made by MASB on creating more discipline in marketing measurement. We highlight work by the International Organization for Standardization (ISO) at a multi-country level to improve brand evaluation.

Finally, in addition to these major changes, we have added some individual metrics such as Return on Advertising Spend.

We very much hope you enjoy this new edition of Marketing Metrics.

1.10New Developments in the World of Marketing Metrics

Since the first edition of this book was published in 2006, there has been considerable progress in the world of marketing metrics. This section of the book outlines some of these developments and mentions some bigger issues related to the topic.

Organization of the Text

This book is organized into chapters that correspond to the various roles played by marketing metrics in enterprise management. Individual chapters are dedicated to metrics used in promotional strategy, advertising and sponsorship, and distribution, for example. Each chapter is composed of sections devoted to specific concepts and calculations.

We present these metrics in a sequence that may appear somewhat arbitrary, but there is a rationale behind it. In organizing this text, we have sought to strike a balance between two goals: (1) to establish core concepts first and build gradually toward increasing sophistication and (2) to group related metrics in clusters, helping our readers recognize patterns of mutual reinforcement and interdependence. In Figure 1.1, we offer a graphical presentation of this structure, demonstrating the interlocking nature of all marketing metrics—indeed of all marketing programs—as well as the central role of the customer.

The central issues addressed by the metrics in this book are as follows:

• Chapter 2, “Share of Hearts, Minds, and Markets”: Customer perceptions, market share, and competitive analysis

• Chapter 3, “Margins and Profits”: Revenues, cost structures, and profitability

• Chapter 4, “Product and Portfolio Management”: Metrics behind product strategy, including measures of trial, growth, cannibalization, and brand equity

• Chapter 5, “Customer Profitability”: The value of individual customers and relationships

• Chapter 6, “Sales Force Management”: Sales force organization, performance, and compensation

• Chapter 7, “Channel Management”: Distribution coverage and logistics

• Chapter 8, “Pricing Strategy”: Price sensitivity and optimization, with an eye toward setting prices to maximize profits

• Chapter 9, “Promotion”: Temporary price promotions, coupons, rebates, and trade allowances

• Chapter 10, “Advertising and Sponsorship Metrics”: The central measures of advertising coverage and effectiveness, including reach, frequency, rating points, and impressions; models for consumer response to advertising; and sponsorship-relevant metrics

• Chapter 11, “Online, Email, and Mobile Metrics”: Specialized metrics for web-based, mobile, and email campaigns

• Chapter 12, “Marketing and Finance”: Financial evaluation of marketing programs

• Chapter 13, “The Marketing Metrics X-Ray and Testing”: The use of metrics as leading indicators of opportunities, challenges, and financial performance

• Chapter 14, “System of Metrics”: Decomposing marketing metrics into component parts to improve measurement accuracy, add managerial insight into problems, and assist marketing model building