MARK JEFFERY is the Director of Technology Initiatives and Senior Lecturer in the Center for Research in Technology and Innovation at the Kellogg School of Management. He has more than thirty publications in management, scientific, and technology journals, and has published twenty-four original case studies with Harvard Business School Publishing. At Kellogg, he directs multiple executive programs including Strategic Data-Driven Marketing and Driving Strategic Value from IT, and teaches in custom executive programs for many organizations including Microsoft and DuPont. He is also the Managing Partner of Agile Insights LLC, a marketing and technology consultancy (www.agileinsights.com).

Mark Jeffery is the Director of Technology Initiatives and Senior Lecturer in the Center for Research in Technology and Innovation at the Kellogg School of Management. He has more than thirty publications in management, scientific, and technology journals, and has published twenty-four original case studies with Harvard Business School Publishing. At Kellogg, he directs multiple executive programs including Strategic Data-Driven Marketing and Driving Strategic Value from IT, and teaches in custom executive programs for many organizations including Microsoft and DuPont. He is also the Managing Partner of Agile Insights LLC, a marketing and technology consultancy (www.agileinsights.com).

Data-Driven Marketing

John Wiley & Sons

Chapter One

Why 80 Percent of Companies Don't Make Data-Driven Marketing Decisions-And Those Who Do Are the Leaders

A senior marketing manager in a Fortune 100 company once told me: "Every week I have to go to a gun fight, the senior executive leadership meeting, and I am tired of going to this gunfight carrying only a knife." His frustration was the result of having no concrete data to answer hard questions about the value of marketing activities in his division. We are living in difficult times, and marketing measurement and data-driven marketing are becoming increasingly important. Now more than ever, managers need to justify their marketing spending, show the value that they create for the business, and radically improve their marketing performance.

Why is data-driven marketing so difficult for many organizations? There are many reasons, ranging from "we don't know how" to the challenge that branding and awareness marketing activities are fuzzy and don't directly impact sales revenues in a short time period. The challenge is compounded by the exponential growth of data. International Data Corporation (IDC) estimates that data storage is growing at 60 percent per year, which suggests the volume of stored data is doubling approximately every 20 months. These vast amounts of data are overwhelming and marketers struggle, with limited time and resources, to measure the efficacy of what they do.

A few marketers and organizations, however, have mastered data-driven marketing principles and marketing metrics. Invariably, these individuals are heroes within their firms, are promoted faster, and rise to more senior positions. As we will see, organizations that embrace marketing metrics and create a data-driven marketing culture have a competitive advantage that results in significantly better financial performance than that of their competitors.

A few years ago, I asked Barry Judge, now senior vice president and chief marketing officer (CMO) of Best Buy, who Best Buy's primary competitor was. He said Wal-Mart. Not so surprising since Wal-Mart is the world's largest retail channel; and with its amazingly efficient supply chain and economy of scale, driving price and margins to the bare minimum, the company has radically changed the global retail landscape. However, I thought he was going to say Circuit City, so I asked why he did not.

"They just don't get it," he told me.

Circuit City's marketing strategy was to constantly run sales. This drew customers into stores and drove sales revenues. But since the advent of Wal-Mart, margins in retail are thin, so running sales actually loses money for the business; that is, it has a negative profitability. The result, as Judge put it, is a "death spiral," where continual sales are needed to drive revenues that continuously lose money.

Of course, the Circuit City story is now history; the firm went bankrupt and liquidated in January 2009. A similar story has played out across mid-tier retail in the United States over the last two decades: Marshall Field's in Chicago and John Wanamaker, the venerable Philadelphia retailer, for example, are now consolidated, along with hundreds of other well-known regional retailers that were unable to compete profitably. These stores now fly the Macy's flag.

But Best Buy is different. Sure, a significant amount of the marketing budget is spent on demand generation marketing-this is marketing designed to get customers into the stores. However, Best Buy spends more money on branding, customer relationship management, and infrastructure to support data-driven marketing compared with competitors. Best Buy also keeps score: measuring the results of marketing initiatives in a feedback loop of adaptive learning to optimize its marketing.

Best Buy marketers analyze customer purchasing characteristics and demographics on a store-by-store basis. For example, they identified one segment in certain geographies, which they called "Jills." This segment is a "soccer mom" who may well be working but is also running the family. She also makes the primary electronics purchasing decisions for the household. Based on these data, Best Buy customized the marketing for specific stores where there are a significant number of Jills in the surrounding population. The marketing included large in-store banner advertising of moms with kids using electronics, direct-mail advertising, and changing up the product mix to appeal to Jills. The resulting sales lift (percentage change) in these stores was then measured before and after the marketing activities.

This example illustrates the marketing divide: a few firms "get" marketing, and many do not. The result is that firms that get marketing have a competitive advantage, and those that do not often struggle, gradually losing market share and/or profitability, to end up eaten by competitors or to go out of business.

In collaboration with Saurabh Mishrah and Alex Krasnikov, I have surveyed 252 firms capturing $53 billion of annual marketing spending on marketing performance management and return on marketing investment (ROMI) best practices. The research demonstrates the existence of a divide between market leaders and laggards. A few statistics from the research highlight the gaps in stark contrast:

Fifty-three percent of organizations do not use forecasts of campaign ROMI, net present value (NPV), customer lifetime value (CLTV), and/or other performance metrics. (See Chapter 5 for the essential financial metrics and Chapter 6 for CLTV. Free downloadable templates accompany all financial metric examples.)

Fifty-seven percent do not use business cases to evaluate marketing campaigns for funding. (For best practices, examples, and templates, see Chapters 5 and 9.)

Sixty-one percent do not have a defined and documented process to screen, evaluate, and prioritize marketing campaigns. (For best practices and examples, see Chapters 3 and 11.)

Sixty-nine percent do not use experiments contrasting the impact of pilot marketing campaigns with a control group. (For best practices and examples, see Chapters 2 and 3.)

Seventy-three percent do not use scorecards rating each campaign relative to key business objectives prior to a funding decision. (For best practices and examples, see Chapter 3.)

I was shocked by these findings, since they suggest that the majority of marketing organizations do not have professional processes in place to manage marketing and that most do not use marketing metrics in their day-to-day marketing activities. After all, if there is no business case or ROMI defined prior to campaign funding, how can you measure success after the fact? The divide is even more pronounced when we look at marketing organizations' use of data:

Fifty-seven percent do not use a centralized database to track and analyze their marketing campaigns (see Chapters 2, 6, 9, and 10).

Seventy percent do not use an enterprise data warehouse (EDW) to track customer interactions with the firm and with marketing campaigns (see Chapters 8 through 10).

Seventy-one percent do not use an EDW and analytics to guide marketing campaign selection (see Chapters 2, 6, 8 through 10).

Eighty percent do not use an integrated data source to guide automated event-driven marketing (see Chapters 8 through 10).

Eighty-two percent never track and monitor marketing campaigns and assets using automated software such as marketing resource management (MRM) (see Chapter 11).

The vast majority of organizations therefore do not use centralized data to manage and optimize their marketing. The leaders, however, are on the other side of the divide and are the smaller percentage of firms, less than 20 percent, that actually do data-driven marketing and use metrics for measurement in their day-to-day marketing activities. As we will see later, these firms have significantly better financial and market performance relative to competitors.

Why is there a marketing divide, and why is it so hard for organizations to do data-driven marketing? These statistics are symptoms of why data-driven marketing and marketing measurement are so difficult for many organizations: the internal processes do not support a culture of measurement, and they also do not have an infrastructure to support data-driven marketing and marketing metrics. But beyond these high-level processes, my experience is that most marketers are overwhelmed with data and do not know where to start in terms of measuring the right things to drive real results. Furthermore, 55 percent of managers report that their staff does not understand metrics such as NPV and CLTV. (Financial metrics such as NPV are discussed in Chapter 5, and Chapter 6 is all about CLTV.)

Don't be discouraged if your organization is one of the 80 percent that does not use data-driven marketing and/or you are not familiar with these metrics-this book is about the simple secrets of the leaders. The goal of this book is to give you transparent metrics, tools, examples, and a road map to actually do data-driven marketing and apply marketing metrics in your organization.

The 15 Essential Marketing Metrics

When I first started executive training at Microsoft in 2003, some Microsoft marketers suggested that what they needed was a "killer app" (software application) for ROMI. What was funny to me is that Microsoft makes the killer app: it is called Microsoft Excel. The spreadsheet is an incredibly powerful tool.

In this book, I focus on relatively simple, but effective, metrics and frameworks for marketing measurement and data-driven marketing, and Excel is a great tool to get started. More advanced tools and techniques exist for linking marketing to sales. These techniques are indeed useful; regression, for example, is often used by packaged goods firms to correlate marketing spending with revenues. However, these methods have significant limitations, including the need for large, clean data sets, which often are not available to most companies. The approach of this book is therefore to focus on a framework for marketing measurement, balanced scorecards with the few key metrics that point to value, and approaches for analysis that are relatively straightforward to implement. (As a side note, regression definitely has its uses. In Chapter 9, I discuss how Meredith Publishing uses regression to figure out what product a customer might buy next, and I compare regression analysis with other data-mining methods such as decision trees for EarthLink customer retention marketing.)

To get started, there is a lot you can do with Excel, and I provide downloadable spreadsheet templates for all of the quantitative examples in this book. For ongoing data-driven marketing, you will most likely want to automate the process, and especially if you have a large customer base, you will need marketing infrastructure, including a database and more sophisticated analysis tools. Approaching this journey is the focus of the next chapter, "Where Do You Start?" and Chapter 10 answers the question "What's it going to take?" in detail for infrastructure.

My perspective is to concentrate on as few metrics as possible that capture the most value for marketing. In summary, the 15 essential metrics for marketing I define are:

1. Brand awareness

2. Test-drive

3. Churn

4. Customer satisfaction (CSAT)

5. Take rate

6. Profit

7. Net present value (NPV)

8. Internal rate of return (IRR)

9. Payback

10. Customer lifetime value (CLTV)

11. Cost per click (CPC)

12. Transaction conversion rate (TCR)

13. Return on ad dollars spent (ROA)

14. Bounce rate

15. Word of mouth (WOM) (social media reach)

Again, don't worry if you are not familiar with some or all of these metrics. They are explained in detail with examples in Chapters 3 through 7.

The first 10 metrics are what I call the classical marketing metrics. Metrics numbered 1 through 5 are the essential nonfinancial metrics discussed in Chapters 3 and 4: these metrics define the efficacy of branding, customer loyalty, comparative marketing activities, and marketing campaign performance. Metrics numbered 6 through 9 are the essential financial metrics every marketer should know. Note that return on investment (ROI) is not one of these metrics-we will discuss why in Chapter 5. Rounding out the top 10 is CLTV, the essential financial metric for customer value-based decision making; Chapter 6 is entirely devoted to this metric.

Over 100 years ago, John Wanamaker said the famous line: "Half the money I spend on marketing is wasted-the problem is I don't know which half." More recently, a CMO told me: "Half the money I spend on marketing is wasted, but today I know which half: TV advertising." His comment reflects the rise of the new media for marketing, the network (both Internet and cell phone), and the ability to track marketing activities in this medium like never before.

Of the 15 essential metrics, the last 5, metrics numbered 11 through 15, are what I call the "new age marketing metrics": search engine marketing effectiveness is captured by metrics numbered 11 through 13. Bounce rate, metric #14, is the key metric to understand how good your web site is, and the new frontier of social media marketing is captured by metric #15, word of mouth. Chapter 7 covers these metrics in detail with lots of examples. Feel free to jump to Chapter 7 at any time-it is an in-depth discussion of Internet marketing best practices. However, throughout the following chapters, I give multiple examples of how to use the Internet to radically improve marketing performance. Let's start the journey with a few general case examples of data-driven marketing and how to use marketing metrics in practice.

Case Examples

So what do you do if you are a small company with a small customer base? The answer is that you can purchase lists that are targeted. A few years ago, I received a postcard mailer at my house. On the front was a picture of a nice golf course with the slogan: "Mark, A Special Invitation." What caught my eye was that it was specifically for me.

Wow, I felt special. Of course, we all know the scenario-we sort our mail into piles: bills in one, letters from Mom in another, and junk in the third. The junk mail is summarily tossed in the trash. Hence, traditional direct mail is incredibly expensive, due to the high printing and mailing costs, and is often ineffective since customers don't look at it. However, the postcard I received was different.

First, somehow they knew I like golf, possibly surmised from my purchasing history, and second, it was addressed to me, Mark. The customization and targeting meant that I put the card on one side-it did not go directly in the trash. There are then good odds I will look at the back. The back was particularly interesting. There was a custom web uniform resource locator (URL): www.companyname.com/Mark.Jeffery. Realize that anyone who types in the URL and clicks return can be tracked and followed up with a phone call as a lead, even if he or she doesn't complete the web form to provide more information.

Figure 1.1 is a similar example for the 2008 Porsche Turbo Cabriolet new product launch. A stamped "raw" metal plate was delivered to existing Turbo Cab owners to coincide with the press announcement of the new product launch. The mailing provided personalized log-in credentials and encouraged visits to the web site with: "The raw Porsche 911 Turbo Cabriolet awaits your color selection." On the web site, the customers chose their favorite color and ordered a personalized Turbo Cab poster.

The design of the campaign, integrated with the Internet web site, enabled end-to-end tracking. There were 2,700 unique log-ins with an average session time of almost 15 minutes, and 5,670 posters were ordered. Interestingly, there was also a significant WOM component, with nearly 500 send-to-a-friend invitations. (See essential metric #15-WOM, in Chapter 7.) The campaign overall had a 30 percent response rate, and 38 percent of Turbo Cab buyers during this period received the mailer.

The response rate and time on site is truly amazing given the high cost of the product ($130,000) and target demographic: busy executives, lawyers, and doctors. But what's great about this example is that the direct-mail marketing was designed for measurement and was integrated with the Web, enabling the capture of customer response data and identifying potential leads.

(Continues...)

Excerpted from Data-Driven Marketingby Mark Jeffery Copyright © 2010 by John Wiley & Sons, Ltd. Excerpted by permission.
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