Imagine that you’re driving your car down the highway. You know where you’re going, and you have a general idea of which route to take, but you have no dashboard. You’re completely ignorant of how fast you’re going, how much fuel is in the tank, or even if the engine is overheating. If your “check engine” light is on to indicate some sort of problem, you don’t know about it. If luck is on your side, you can drive your car under these conditions to the end of your journey. But continuing to operate your vehicle over time without the information the dashboard provides is tempting fate. Eventually, a problem will occur that you can’t detect. Without the dashboard, you’re blind to the performance of the vehicle. Ultimately, driving this way will lead to consequences, some of them quite severe. You could easily end up in the ditch on the side of the road.

This vehicle metaphor applies to organizations and the analytics—their dashboards—that help them keep their marketing engines running effectively. A properly implemented analytics process helps a marketing organization avoid negative consequences. But analytics aren’t just about keeping marketing out of the ditch; analytics help optimize marketing’s performance. An analytics process, therefore, isn’t just about keeping the marketing organization out of trouble but helping it perform at its highest level.

For most companies, analytics are at the heart of how the business is managed. The finance department is perhaps most often associated with measurements and analytics with which the entire organization is familiar: revenue, profit, return on investment (ROI), return on equity (ROE), and many others. Manufacturing tracks metrics like output and defects. Human resources will measure employee retention and performance. Every department or division in a company uses analytics to make sure there is alignment with and progress toward goals. The outlier has often been marketing. Even today, 14 percent of marketing organizations don’t have an analytics process,¹ a reflection of marketing’s historical reluctance toward analytics.

This book explores marketing’s attitude toward analytics, the challenges of implementing an analytics process, insights for embracing analytics in a meaningful way, and tools for getting the answers you need on the performance of your marketing program.

Marketing Analytics Defined

The generic understanding of analytics is that they are measurements or numbers that indicate how a process is performing. This definition certainly holds true for marketing analytics, yet a deeper understanding of analytics helps marketing organizations take full advantage of what the process can do to drive better performance. To that end, here is my definition:

Marketing analytics is the process of identifying metrics that are valid indicators of marketing’s performance in pursuit of its objectives, tracking those metrics over time, and using the results to improve how marketing does it work.

The core components of this definition are worth examining more closely:

• Valid indicators: There are many things about marketing’s work and results that are measurable. Not all of them, however, are true indicators of performance. The analytics process must determine which metrics have meaning and best represent the value that marketing creates for the organization.
• Pursuit of objectives: The analytics process is ideally built to measure progress toward a set of objectives, a notion more fully explored in Chapter 5. The objectives come first, followed by an identification of the relevant performance metrics.
• Tracking metrics over time: The analytics process isn’t about taking a random, one-time snapshot of a performance measurement, but tracking measurements over time to monitor trends and direction of performance.
• Improve how marketing works: There are several reasons a marketing organization might implement an analytics process, such as accountability or justification of resources, but the noblest and ultimately most valuable reason is to improve its performance.

This book refers to analytics and metrics, often interchangeably. These terms have similar meanings. Analytics are both the process and the collective output of that process—performance information with the ideal use as a management tool. Metrics are the “atomic unit” of analytics. The marketing analytics process consists of creating a series of metrics or measurements in specific areas.

As the definition for marketing analytics implies, it isn’t just a set of numbers. Instead, it is a process that has these primary components:

1. People: The marketing analytics process is created, executed, and managed by people who own it. In most marketing organizations, the process owner is the chief marketing officer (CMO) or the marketing director.
2. Steps: The marketing analytics process consists of a sequence of steps. The steps that make up the marketing analytics process are described in Chapter 4.
3. Tools and technology: While the marketing analytics process isn’t necessarily complex, tools and technology help marketing organizations deliver greater value faster than they ordinarily might. Chapter 8 discusses the tools and technology in greater detail.
4. Input and output: Data feeds the process, with insights and decisions as the output of the process.

Like many processes, marketing analytics should have a definite beginning but no ending—it is a process that, once initiated, should continue indefinitely.

This discussion of marketing analytics has so far been conceptual. To provider greater clarity into how a marketing analytics process affects an organization, we will consider three scenarios of marketing organizations: one without an analytics process, one with a “pseudo” analytics process, and one with a real analytics process that is effective. As we examine these three organizations, we’ll look at the differences in how each is led, gets funding, operates, and makes decisions.

No Analytics Process: Flying Blind

The first type of marketing organization we examine is the one that has no analytics process. In their metaphorical marketing vehicle, they have no dashboard at all. The CMO plots the organization’s course and pilots its way by instinct. Determining the success of marketing is completely subjective, and often quite political. For this reason, CMOs who choose to fly blind with respect to analytics are often adept at playing organizational politics. Survival depends on their ability to stay in the good graces of the CEO.

It’s easy to assume that such an organization would have no marketing success, but that isn’t the case. Despite the lack of an analytics process, these marketing organizations can have some impressive (albeit intermittent) successes. The problem is one of consistency. When these organizations succeed, it’s difficult for them to understand why, because marketing is essentially an experiment with no control variables. “We were lucky” is often the marketing department’s internal response to success. Conversely, when marketing fails to produce results, it’s equally difficult to explain the failure.

A common leadership scenario for these marketing organizations is for a new CMO to succeed one who was fired for failing to produce results. A problem, of course, is that since no analytics are in place, conclusions about results—or the lack thereof—is completely subjective. The CEO can simply conclude that the CMO is not performing. This seems terribly unfair to such CMOs, but if they have not implemented a set of marketing performance metrics, they have by default placed themselves on this slippery subjective slope.

The new, replacement CMO in these organizations typically has a tenure of about 18 months. The first six months are the honeymoon period, a time for the CMO to assess what’s been done and determine what needs to happen. The new CMO understands that business as usual will not create success, so it’s a time of change. During this period, the CMO will have the greatest creative latitude, because there’s a general understanding throughout the organization that the old methods no longer work. The leadership style of the CMO in this situation is typically an amalgam of intuition, creativity, and past experience.

The second six months in the new CMO’s tenure are spent implementing the new marketing agenda. The marketing team goes into execution mode with great expectations of success. This marketing organization does not use metrics or analytics to guide decision making or measure success, so how can it know if it achieves its goals? That determination remains subjective, but everyone in the organization will develop some intuitive feeling or use their own subjective measures to determine if marketing is succeeding.

The third six-month period in the tenure of a new CMO is the results phase. It’s the start of the second year of service, and by this time, the honeymoon is generally over. The general consensus is that results are due. Quite often there are favorable business results, but are they attributable to the work of marketing? This is a rhetorical question, because measurements don’t exist to support any credit marketing might take in producing favorable outcomes. When business is good, marketing usually gets a free pass on having to prove its contribution. The CMO can reasonably expect to remain employed for another 6–12 months.

When business is bad, however, the lack of evidence for marketing’s results is usually career-ending for the CMO. It’s entirely possible that the CMO’s marketing agenda was highly effective and prevented the company from even worse performance. But there is no solid ground on which marketing can stand to make that argument, and marketing has historically been a convenient scapegoat. Whether marketing is truly to blame is a moot point. The fate of the CMO and the future of the marketing team comes down to the subjectivity of the CEO, how persuasive the CMO is, and how many political allies he or she has. If the ax falls, a new CMO will come in and the cycle begins again.

Marketing organizations that operate in an analytics vacuum usually ride a funding rollercoaster. A new CMO gets the benefit of the doubt and finds a greater willingness to make a larger investment in marketing. But for most of these marketing organizations, the funding process is a grind. The annual budget battle for marketing funding is psychological warfare, since performance data doesn’t exist to create a business case for what marketing wants to do. Success securing the funding depends on the charisma, persuasiveness, and political alliances of the CMO. Usually, marketing has to settle for incremental increases in funding and resources, and then only in good years. If marketing wants to do something ambitious outside the status quo, the funding approval process can be a political gauntlet.

From an operational perspective, marketing organizations that eschew analytics tend to function without the benefit of a strategic plan. It’s not that they are directionless, but formal marketing planning yields plans that have measurements attached to their objectives. In this scenario, there’s a plan, but it is based on intuition and is very fluid. It also exists primarily in the head of the CMO, which means the rest of the company doesn’t have great insights into what marketing is up to.

This lack of clarity about the marketing plan has a long-term damaging effect on the marketing team. The absence of a codified marketing plan that is understood throughout the company makes it difficult for the marketing team to say “no” to the many internal, ad hoc requests that all marketing organizations get. Saying “no” to a marketing request—even one that the marketing team knows is silly—costs political capital. When no analytics process exists to prove its value, marketing needs all the friends it can get in the organization. This creates a reluctance for marketing to say “no” even when the team knows it should. When the rest of the organization becomes conditioned to getting what it wants from marketing, the team gets very busy—too busy, in fact. It is perceived as the part of the company with “its hair on fire.”

This operational pattern demonstrates the value of having an analytics-based marketing plan. When such a plan is in place, it’s easy to refer to it as the reason for denying resources to these ad hoc requests that come from all corners of the company. Marketing can comfortably say “no,” because there’s a bigger, more important commitment: the marketing plan, which represents a success blueprint. Any requests that are inconsistent with the plan represent harmful distractions, to which the CMO and marketing team can say “no” with authority. But when no plan exists, as is often the case for these kinds of organizations, saying “no” comes across as arbitrary to those who request the team’s services and resources.

These marketing organizations are firmly on the intuition side of the decision-making fence. This means that virtually every decision has a significant degree of uncertainty associated with it. In fairness, even organizations that have an effective analytics process can’t remove all uncertainty from their decisions. Even though having no analytics process means that decisions are essentially educated guesses, these organizations have a lot of conviction about the guesses they make.

A Pseudo-Analytical Marketing Program: Half the Gauges Are Dark

The next type of marketing organization we examine is one that has a pseudo-analytics process in place. In the metaphorical vehicle that is conveying this marketing team, there is a dashboard, but some of the gauges aren’t working or are simply ignored. The other possibility is that the marketing team doesn’t know how to read the gauges and understand what they mean. In many ways, this marketing team resembles the story of the Emperor’s New Clothes. Because they have some numbers related to marketing, they feel clothed, but many in the company recognize their nakedness.

As with the marketing organizations that are flying blind, these pseudo-analytical organizations can produce success. The difference is that these organizations attempt to use metrics as part of its marketing process. Some numbers related to what marketing is doing are leveraged, often with a high degree of devotion. The flaw in their approach, however, is that the numbers aren’t true indicators to marketing’s performance. There is no clear connection between the metrics, which reflect some marketing activity, and business results. The simple fact is that some metrics are in use that can actually create a false sense of accomplishment. The marketing team understands that it should have some metrics that define its performance. So it feels good about having some, but the pseudo-analytics process it uses doesn’t produce metrics that have real meaning or offer strategic insights to the team.

There are two common leadership scenarios in marketing organizations using pseudo-analytics. A leader who knows analytics are important but just doesn’t understand how to define meaningful performance metrics represents the first scenario. A lack of experience, skills, time, or mentoring prevents this CMO from understanding how to use analytics as a performance gauge and gain insights for improving marketing’s effectiveness. What tends to happen is that this leader latches onto whatever analytics are easily available. A range of interesting analytics are often forged into some kind of dashboard, often including things like:

• Productivity measures: projects completed, ads designed, meetings held, and so on.
• Marketing measures: web analytics (e.g., page views, unique visits), social media follows, direct mailers sent, and so on.
• Internal client satisfaction: some measure of how well the marketing team is serving the organization, often a measure of responsiveness.

These metrics are very activities-centric, but they don’t provide much insight into how marketing is actually contributing to achieving the organization’s revenue goals. The executives who are recipients of this organization’s analytics dashboard may nod and smile while reviewing them, but they have unexpressed frustration about what the metrics truly mean. In the boardroom where conversations are about revenue, earnings, ROI, EBITDA,² and other key financial metrics, no one, yet alone this marketing leader, knows how to connect the marketing team's activities to business results.

The other leadership scenario seems more nefarious, involving a marketing leader who uses analytics as a smokescreen. This CMO understands that the organization expects marketing to use analytics, so he or she does, throwing up a smokescreen of metrics that obscure what marketing is really doing. As with the first leadership scenario, the analytics process in use by this CMO also employs metrics that don’t really connect marketing activities to business results. If there is a difference in this leadership scenario and the first one, its that sometimes analytics are reverse-engineered to help justify the CMO’s predetermined course of action. They simply provide cover for the CMO.

This second leadership scenario does seem like the product of a scheming CMO, but it’s rarely the result of some evil plot. Instead, it’s a product of fear—a fear of having analytics that reveal marketing’s failure to perform. This fear is fueled by an insecurity—that he or she can’t risk having metrics show that marketing doesn’t work or doesn’t know what it’s doing. This fear is legitimate, and anyone who has been part of the marketing community long enough can probably recount a story or two about how analytics were used punitively against the marketing organization. In these situations, analytics aren’t the problem; the culture is to blame.

With either leadership scenario, the pseudo-analytics process creates opaqueness, and the CMO is content with that outcome. Since no one outside of marketing can really understand what the analytics coming out of marketing mean, they have to go to the CMO for interpretation. The explanation these inquiries produce sound something like, “It’s hard for someone without a marketing background to understand them, but trust us: these are good numbers.” As long as business results are reasonably good, most people in the organization accept this explanation, even while scratching their heads. The truth, however, is that marketing organizations that use pseudo-analytics are on the same, slippery, subjective slope as those who use no analytics. When financial pressures cause executives to inspect with a critical eye what’s really happening, marketing can’t answer the difficult questions about its contribution.

The funding situation with pseudo-analytics doesn’t differ much than that for organizations with no analytics process. It’s still an annual battle for incremental budget increases. One difference is that marketing can cite improvements in the metrics as justification for funding requests. Never mind that the analytics put forth by marketing may not really indicate how marketing is performing; the fact that there are numbers at all lends a veneer of credibility that marketing wouldn’t otherwise have. Even though the executives who approve the budget don’t understand the work of marketing well, they will often accept their budget rationale on faith.

For big funding requests, these marketing organizations fare better than those using no analytics. Because ambitious projects require some sort of business case, justification is based on a set of metrics that tangentially support what marketing wants to do. Numbers, even the wrong ones, are persuasive when no one understands how to challenge them. Any discussion of ROI, however, is just speculation, because there are no metrics—or a culture of using them—that allows for the calculation or even estimation of ROI.

Operationally, these marketing organizations are busy. Busy-ness is the common denominator of any marketing organization, but these organizations aren’t necessarily busy doing the right things. Without the guardrails of a good analytics process, the organization is never sure of whether it is on the right path or how effective it really is. The pseudo-analytics it uses are oriented more toward tracking activity instead of results. Units of marketing tasks performed, such as mailers sent, web pages updated, brochures printed, or ads placed indicate how busy marketing has been, but not what it produces in the way of results.

As for decision making, these marketing organizations rely both on intuition and the pseudo-analytics, but more on the former than the latter. They are reluctant to lean too heavily on their analytics, because they don’t have complete confidence in them. Of greater concern is having the analytics become master over the marketing department, so marketing maintains an arm's-length relationship with its analytics. As long as they provide cover for what marketing wants to do, the analytics are useful. But allowing analytics to influence decision and strategy is unthinkable, because it risks putting analytics in the driver’s seat instead of the CMO.

This orientation puts marketing squarely on the fence with respect to decision making. It doesn’t have the benefit of a good analytics process, nor does it rely fully on intuition but instead a murky combination of pseudo-analytics and gut feeling. This produces uncertainty, and the bigger the decision marketing has to make, the more uncertainty there is about it. For this reason, these organizations tend to have less conviction about the big decisions they make than those with no analytics process.

A True Analytics Program: The Real Deal

The final scenario examines a marketing organization that has a real analytics process in place and uses it. What is meant by “real” is a process that tracks metrics that provide true and direct indicators of marketing’s performance and contribution. Using these metrics, the marketing team and the company it serves can determine with precision how marketing influences revenue. Furthermore, these analytics are a management tool that helps marketing optimize its efforts and produce the best possible outcomes. In this marketing team’s metaphorical vehicle, all the dashboard gauges and indicators work, and the team knows how to read them. When the check engine light comes on, immediate problem determination and resolution takes place. The metrics and performance data this process produces not only guides the marketing team, it is shared freely with the rest of the organization.

Unlike marketing organizations that are flying blind or using pseudo-analytics, these organizations consistently produce success, and because they use an effective analytics process, they have no difficulty demonstrating their value to the rest of the company. Success is almost never the result of luck or a good guess by the CMO. Instead, it comes from using analytics to measure what marketing does, and then pivoting when the analytics indicate a need for it, or staying the course when managers confirm it is the right one.

It’s easy to assume that these organizations put analytics in the driver’s seat and simply go wherever the numbers lead them. Analytics are critical success factors for marketing, but they don’t call the shots here. The correct understanding of this relationship is to see the CMO as the true master of marketing, with analytics as a trusty servant. As my colleague Stephan Sorger put it in a webinar we taught, “Analytics are good servants, but poor masters.”³

Strategies are devised and implemented, campaigns developed and launched, all with a reliable set of built-in metrics to measure impact.

The output of the analytics process is constantly monitored to determine:

1. Performance: what do the metrics reveal about the results marketing is producing?
2. Validity: are the right metrics in use to provide a true and precise indication of performance?

If the metrics reveal that a marketing initiative or campaign isn’t working, changes are made to produce better results. Marketing doesn’t just continue to do the same thing hoping that the results will magically improve. Instead, it recognizes what the analytics process is telling it: change must occur. Likewise, the metrics themselves are constantly under scrutiny to make sure they are accurate indicators of performance. These marketing organizations know that in the area of analytics, it’s easy for expediency to take over, leading to measuring what’s easy instead of what’s relevant.

The use of analytics is part of the marketing culture that everyone embraces. Culture is a function of leadership, so the CMO sets the expectations and models the use of analytics as part of the marketing culture. The CMO is the analytics process owner, and ideally a thoughtful person who understands not to use analytics as a whip to punish poor results. When analytics are used punitively, they’re immediately rejected, or manipulated to only generate favorable data, eroding the value of the process. To keep the process working like it should, these CMOs eliminate the fear of negative consequences from using analytics to expose the poor performance of a marketing initiative. Instead, the CMO creates a culture around analytics that rewards identifying problems and underperformance so resolutions can occur.

The budgeting process is rarely just a formality for any type of marketing organization. However, those with analytics at the core of their culture have a much easier time getting funding. One reason is because the value of marketing is known: the analytics its uses allow it to clearly show the entire organization how it helps create revenue. Because it is able to tie revenue directly to its activities, marketing’s ROI is known. Although it may take some effort to analyze and present the data, because these marketing organizations have a real analytics process, justifying spending is never speculation. It’s much easier to do because the necessary data is available.

The analytics discipline of these marketing organizations are also helpful when it comes to justifying ambitious, out-of-budget projects. Sometimes, the organization will sense an opportunity that requires funding not in the budget, as well as the agility to exploit it quickly. The C-suite is far more likely to make these investments when marketing has the ability to measure the results. This ability is no guarantee that the endeavor will succeed, but at least the organization will know the outcome with certainty. There’s no fuzzy speculation about what kind of returns are coming from these investments.

These organizations tend to operate with greater authority and conviction than those that are flying blind or using pseudo-analytics. For any significant marketing activity or campaign, a prerequisite is identifying metrics to determine its success. This operational approach builds in a healthy level of skepticism about success: the marketing team doesn’t usually celebrate success—or condemn something as a failure—unless the metrics provide the proof.

Using the analytic process as a guide, the marketing team maintains a steady focus on producing results, continuously refining what it does to constantly improve, generate more revenue, or increase the margins. This orientation feels very different from the first two types of organizations where activity is celebrated. When analytics are at the heart of the marketing team’s culture, activities are meaningless unless they produce a result the business cares about. One effect this attitude generates is an intolerance for empty activities or busy work that produces no value.

It’s easy to get a mental picture of these marketing organizations as dispassionate number crunchers that do whatever the numbers dictate. That picture is an inaccurate portrayal of how they make decisions. Of course the numbers matter, but an organization that just followed the numbers wouldn’t provide the leadership or creativity that an organization needs from its marketing function. What happens instead is that the CMO drives the development of strategy, usually in close collaboration with the marketing team and key organizational stakeholders.

Part of this decision making is always ample consideration given to determining the right metrics for evaluating how the strategies and tactics are working. Marketing analytics don’t remove all the risk from what marketing does, but they enable marketing to more quickly and accurately determine if results are within acceptable risk parameters. For this reason, these kinds of marketing organizations are usually more comfortable taking risks than the other two types.

There’s no mistaking on which side of the fence these marketing organizations are: firmly on the analytics side. This doesn’t mean that intuition plays no role in how these organizations operate, but it does mean that intuition is always paired with a set of metrics. Intuition has value and remains a key part of how these marketing organizations develop strategy. Intuition may lead, but verification metrics always follow. For this reason, these organization know better than the other two the degree to which they can trust their intuition.

Table 1-1 provides a summary of each type of marketing organization this chapter examines.

Not Three of a Kind

The three kinds of marketing organizations put under the microscope in this chapter have one thing in common: they all fall within the “marketing” box on the organizational chart. While those that are flying blind and those that use pseudo-analytics share several characteristics, there are few similarities between them and the one that uses real analytics.

Marketing professionals that have had experience working in all three kinds of organizations almost always find the last kind the best place to work. The reason is because in the first two kinds, marketing is viewed as an expense, a necessary one perhaps, but still an expense. Should economic pressures affect companies that view marketing this way, the marketing functions is one of the first place the company makes cuts.

By contrast, in marketing organizations that use a real analytics process, the value of marketing is known and understood by the entire company. Here, marketing is a revenue center, and its performance makes it an invaluable contributor to the company’s success. Marketing organizations that do not learn how to transform themselves from cost centers to revenue centers are transient. Their future is never certain; their existence is often in jeopardy. The reason marketing organizations should adopt a real analytics process is so they can make the transformation from a cost to a revenue center, and provide ongoing proof of that transformation. The remainder of this book discusses how to create such a marketing organization.

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¹“Sales & Marketing Analytics: Gauging and Optimizing Performance,” p. 7, Demand Metric benchmark report, December 2013.

²Earnings before interest, taxes, depreciation, and amortization.

³See http://www.demandmetric.com/content/eworkshop-learning-love-analytics.