When viewing marketing as an entity, you can perceive it as having a persona, similar to the three types Chapter 1 describes: no analytics, pseudo-analytics, or real analytics. These personas represent a spectrum of how the marketing team operates and creates value. On one end of the spectrum, marketing is reactive and operationally oriented, managed by the perpetually busy, “hair on fire” type of manager. Occupying the other end of the spectrum are organizations where marketing is a strategic asset, providing leadership to the whole company through a visionary leader executing a plan that aligns with corporate strategy. The foundation of that plan is a set of analytics that functions as guardrails to help marketing stay on course.

On the operational side of this spectrum, marketing delivers incremental value at best, and it faces a constant struggle to justify not only its budget but its very existence. On this spectrum’s strategic side, marketing is a major driver of the company’s success. Because it uses analytics effectively, marketing has no trouble proving its worth. As a strategic, revenue-generating asset, marketing easily justifies its existence and provides a return on the investment made in it.

The relevance of any marketing organization depends on its ability to shift from an operational orientation to a strategic one, and many marketers aspire to help their organizations make this transition. Making this shift is imperative for marketing to change its perception as a tolerated expense to that of a valued revenue center. From a leadership vantage point, there’s a lot riding on marketing’s ability to make this shift, because operational marketing organizations don’t enjoy much influence.

Most marketers are not ignorant of the need to make this shift, but the pace of change at times seems absolutely glacial, frustrating the marketing team and the leaders to whom they are accountable. Generating lift for marketing are a growing array of technology solutions, tools, methods, channels, skills, and leadership that marketers are developing or exploiting. Figure 2-1 depicts the tremendous diversity of the marketing technology landscape, with virtually every solution having the capability to participate in or contribute data to a marketing analytics initiative.

The very complexity of the marketing technology landscape, however, is daunting because marketers assess myriad solutions that can help them attribute business results to their activities. The technology challenges, however, are temporary, and a marketing analytics initiative can’t take flight without some supporting systems and sources of reliable data. What creates the most drag against a marketing analytics initiative are attitudes, usually within organizations but sometimes within the organizations those marketers serve.

Modern marketers generally understand how important it is to have the marketing team function as a revenue center, where that revenue contribution is quantified and reported through an analytics process. When marketing exists as an expense instead of a revenue center, it’s in jeopardy because it ranks high on the short list for cutbacks when the company experiences financial pressure. Functioning as a revenue center helps marketing not only survive but thrive when the company needs its services in difficult times. For this reason, even when CMOs haven’t completely figured out how to transform their team into a revenue center, they steadily press on with this shift because it is imperative to the long-term survival of marketing.

From a macro perspective, how is marketing viewed today—as an expense or a revenue center? Demand Metric Research Corporation completed a study¹ during the first quarter of 2014 that provides the answer. The first thing this study attempted to learn is the financial perception of marketing inside a company. Figure 2-2 displays the results from more than 250 study participants, most of whom were marketers, indicating how their marketing function is perceived inside their organization.

This data is a good indicator of the current state of marketing analytics, because the best tool for changing the perception of marketing as an expense is an analytics process. Further analysis of the data in this study reveals that of those organizations viewing marketing as an expense, half don’t use analytics at all or only to a slight extent. For whatever reasons, they are denying themselves the best means to guide their efforts and show accountability to the rest of the organization.

By contrast, for the organizations represented in Figure 2-2 that perceive marketing as a revenue center, merely 16 percent report not having an analytics process. Any company that has properly implemented customer relationship management (CRM) and marketing automation systems, and also manages the quality of data in these systems, will have access to the information necessary to demonstrate not just relevance but revenue impact. There is no other way for the modern marketing organization to function.

Modern marketers won’t argue that the way for the marketing function to operate is as a revenue center, one that is indispensable to the rest of the organization. What characterizes an “indispensable” marketing organization? We need some characteristics more detailed than “produces revenue” to understand how these kinds of marketing organizations operate and differ from the ones perceived as cost centers. Figure 2-3 reveals the three key characteristics of marketing organizations described as “we would not achieve our business objectives without marketing’s contribution”—or in other words, indispensable—in a survey on marketing analytics.² When using these three characteristics to compare these indispensable marketing organizations to all marketing organizations, there are significant differences.

The first characteristic of an indispensable marketing organization is strategic orientation. This implies that there is a plan that drives what marketing does. Ideally, this plan results from a strategic planning process involving the key stakeholders in the company. This plan aligns very closely with corporate goals and objectives, and there are milestones and measurements to track progress.

By contrast, marketing organizations that exist as cost centers are more likely to have an operational orientation. This doesn’t mean they have no plan, but the plan is often ignored or even abandoned. These marketing organizations are request-driven and more reactive. They resemble the type of marketing organization described in Chapter 1 that is flying blind with respect to analytics.

The second characteristic of indispensable marketing organizations is that they have a high degree of alignment with the sales teams that they support. They work together, and not apart in silos, and they have compatible or even shared goals.

The third characteristic of indispensable marketing organizations is that they are very or completely analytics-driven. Analytics are at the heart of how these marketing organizations work. They rely on analytics and metrics to validate their efforts and show accountability to the rest of the organization.

The marketing organizations exhibiting these characteristics are not at risk of having the perception that they are an expense. Furthermore, analytics don’t occupy a silo separate from other characteristics. Analytics enable the first two characteristics discussed above. We’ll examine the current state of marketing analytics to see how prevalent these indispensable marketing organizations are.

The State of Marketing Analytics

Marketers will always face the challenge of demonstrating value and relevance to the organizations they serve. Marketers, although sometimes reluctantly, generally agree that an analytics process provides the most compelling evidence of their contribution. What is the current state of analytics across the marketing community at large?

Figure 2-4 provides a graph, summarizing the views of more than 700 company presidents, CEOs, CMOs, vice presidents of marketing, marketing directors, marketing managers, sales managers, and product and brand managers on the status of marketing analytics in their companies. A survey³ of this group inventoried the state of their analytics efforts using the following response categories:

• Avoidance: We’re trying to avoid analytics unless required to use them.
• Searching: We want to do something and are searching for the best way to start.
• Experimenting: We’re experimenting to identify the best set of analytics, but they aren’t yet influencing behavior or activity.
• Low visibility: We’re tracking meaningful analytics, but they don’t yet have visibility outside of the marketing organization.
• High visibility: We’re tracking meaningful analytics, and they have visibility throughout the organization.

In this era of modern marketing, just over a third of companies report that they are tracking meaningful analytics. The same group of participants were also asked to rate their marketing process using a scale in which 1 equals “avoidance” and 5 equals “meaningful and visible results.” This analysis reveals that large companies (more than 1,000 employees) report greater analytics progress with a mean score of 3.46, compared to small companies (100 employees or fewer) whose mean score was 3.17.

There is also a relationship between company size and the state of analytics:

• 33 percent of small companies are either avoiding analytics or searching for the best way to start.
• 26 percent of medium-sized companies (between 101 and 1,000 employees) fall into these same two categories.
• 19 percent of large companies fall into these categories.

It seems that the larger the company, the more likely that its marketing department is using analytics. Small companies may feel less compelled to pursue a marketing analytics initiative for a number of reasons. Quite often, there is an “all hands on deck” mentality in small companies, and everyone pitches in to do whatever is necessary for the company to succeed, and this includes marketing. The various functions within a small company usually have proximity to one another, literally working side by side. In this setting, everyone seems to know what everyone else is doing, so the need for the accountability that analytics provides isn’t as urgent.

As we consider the state of marketing analytics, the amount of funding analytics initiatives receive is a good indicator of importance. The things companies invest in reveal their priorities and the seriousness of their endeavors. Although marketing analytics don’t represent a massive outlay, it does require some funding and resources if the process is to have impact. The data summarized in Figure 2-5 provide a view of how much of the marketing budget is earmarked for analytics.⁴

When analyzed further, the data in Figure 2-5 provides insights into the relationship between analytics funding and effectiveness. Eight percent of participants in this study are investing more than 10 percent of their marketing budgets on marketing analytics. For this elite group, 50 percent of them also report they are tracking meaningful analytics that have visibility throughout the organization (Figure 2-4). This represents a level of analytics maturity that is almost double that for organizations spending between 6 and 10 percent of their budget and triple that of organizations spending less than 5 percent of their budget. This analysis makes clear that more investment leads to greater visibility of the analytics data. Does that visibility also equate to better results? Although visibility is important, results are what matters.

Additional analysis of the budget data in Figure 2-5 shows an apparent point of diminishing returns on investing in marketing analytics. The marketing organizations that are allocating between 6 and 10 percent of their budget on marketing analytics are getting the best results, with 51 percent of them reporting the highest rate of improving marketing results with analytics. For the elite group that is spending more than 10 percent of their budget, 45 percent report this highest rate of improvement, and for those budgeting less than 5 percent on analytics, 40 percent fell within this highest rate of improvement. It seems, therefore, that the sweet spot is to allocate between 6 and 10 percent of the marketing budget toward analytics.

Attitude Toward Marketing Analytics

The presence of a marketing analytics process within a company isn’t necessarily an indicator of a favorable attitude toward analytics. Indeed, when it comes to marketing analytics data that is measured and tracked, almost one-fourth of companies report that “no one seems to be using it.”⁵ In some companies, executives send the marketing team on a forced march to analytics. In such a case, resistance to the analytics process is quite high. Although the process often gains some converts, it’s still an uphill climb against the passive-aggressive response marketing often exhibits to having analytics forced upon it.

Less common is the pro-analytics marketing team that can’t get the attention of the rest of the company about the value the process can provide. Here, too, it is likely that over time, the marketing team can win over converts to the process. In either case, real results from the analytics process are very convincing.

These two positions reflect the varying attitudes that can exist within an organization about analytics. For any initiative, the biggest barriers are often attitudinal, so as we review the marketing analytics landscape, it’s helpful to understand the prevalence of the attitudes that shape it. The Demand Metric study also gives insight into the range of attitudes that exist toward analytics and how widely they are held. Figure 2-6 summarizes this data about attitudes.

Of the five attitudes presented in Figure 2-6, only two represent negative attitudes, and those are held by just 8 percent of the survey sample. The remaining three attitudes are positive. In the following paragraphs, we’ll explore these attitudes in detail.

The least prevalent attitude contends that it is impossible to define a meaningful set of marketing analytics. To assert with absolute certainty that it isn’t possible to derive a set of metrics that have meaning is simply a sophisticated declaration of unwillingness. Of course it is possible for any marketing organization, through adequate thought and planning, to identify a set of metrics that are effective performance indicators. Although this attitude is rare—perhaps because few CEOs will tolerate it—it is associated with CMOs who don’t want facts or analytics data to interfere with their marketing agenda. To simply dismiss analytics with a declaration that it isn’t possible to measure the results of marketing’s efforts is either complete ignorance or arrogance. Although it’s true that barriers may exist to accurately measuring marketing’s business impact, none of them are insurmountable.

The second attitude from Figure 2-6 that is negative also isn’t very prevalent: just 5 percent of the sample in this study report that analytics are too easily misinterpreted by those outside of marketing. There are three drivers that often account for this attitude. The first is a legitimate fear that those who don’t understand or appreciate the analytics might use them inappropriately. The second is the fear that the analytics will reveal marketing’s poor performance. The third driver is arrogance.

The first underlying reason of the attitude that analytics are too easily misinterpreted by nonmarketers is a healthy fear of the consequences. Analytics, particularly when first implemented, don’t always have a happy story to tell. If marketing is completely transparent with its analytics data, some who are outside the marketing group could seize the opportunity to use the data for political gain. What really needs to occur, however, is for marketing to have the chance to use the data to improve, and this may require completing several cycles of measurement and analysis. It’s harder for this to happen if a dysfunctional culture exists in the company. In such a culture, marketing may have good reason to fear complete analytics transparency. It is an unfortunate fact that in corporate environments, not all cultures are healthy. Anyone who has been in marketing long enough can probably share experiences of communicating analytics and performance data transparently, and then getting punished for it.

A second driver of the attitude that analytics are too easily misinterpreted by nonmarketers is insecurity. The roots of this insecurity come from the CMO knowing that meaningful analytics will reveal marketing’s poor performance. Even in the absence of analytics data, marketers have pretty good intuition about the kind of impact their work is having. A survival strategy for marketing managers who are insecure about their team’s performance is to avoid analytics and front the team with a flurry of activity and communicate in platitudes about the results. It strikes fear in the hearts of these CMOs when the CEO suggests—or decrees—the use of analytics. An almost automatic response in such situations is “analytics are too easily misinterpreted by nonmarketers.” The goal is to portray marketing as some sort of dark art, a practice so arcane that only those within its fraternity can hope to understand the analytics. The irony here is that a proper analytics initiative would provide this marketing organization with improvement data, vanquishing the fear of being “outed.”

A third driver is simply arrogance. When arrogance is in play, marketing is essentially communicating to the rest of the organization that what it does is beyond comprehension by outsiders. From the outsider’s perspective, there isn’t a perceptible difference between insecurity and arrogance as the driver of this attitude, because both portray marketing as beyond comprehension. In either case, however, the net effect is to build a smokescreen to hide marketing’s true performance, and this comes from a willful decision to oppose marketing analytics. The fact remains that proper education and communication about the meaning of the marketing analytics data removes the concern over misinterpretation.

The third attitude depicted in Figure 2-6 acknowledges that analytics could provide marketing with some needed credibility. Marketing organizations that don’t use analytics data to account for their contribution are susceptible to having their credibility questioned. At worst, marketing’s very existence is threatened when its credibility within the organization it serves is questioned. At best, when marketing has a credibility problem, it will struggle to gain acceptance for the strategies and campaigns it wishes to deploy. The 20 percent of the survey sample who chose this attitude response option acknowledge one of the benefits of having an analytics process: the credibility of having data to prove marketing is effective. With that credibility comes a great deal of latitude and empowerment for the CMO. Chapter 3 explores this issue in greater detail.

The fourth attitude depicted in Figure 2-6, held by 25 percent in the survey’s sample, is that analytics could help show the value marketing creates. This attitude communicates the reality about how marketing organizations can demonstrate their effect on revenue—through analytics. There is no other way for a CMO to account for the share of revenue directly attributable to marketing except through a set of metrics that link marketing’s activity to business results. Every marketing organization should aspire to show proof of its value to the company. Even when marketing organizations create intrinsic value through inspiring, creative campaign development and execution, they still need to offer proof of the value they deliver. An analytics process provides that proof.

The fifth and final attitude depicted in Figure 2-6 is the most widely held. Almost half the survey sample responded that analytics are vitally important as a dashboard to help manage marketing processes. This attitude represents the ultimate goal of an analytics process: using the output from it as a management tool to continuously improve what marketing is doing. Analytics help show that marketing has credibility, and they are a way to demonstrate marketing’s value. These benefits flow out of using analytics as a dashboard to guide marketing’s efforts. This attitude, therefore, represents the primary analytics goal for marketers. Build an analytics process that serves as an effective dashboard to guide marketing’s work, and credibility and demonstrable value will follow.

Marketing Analytics Challenges

It’s easy enough to find some marketing metric on which to measure and report. However, creating an analytics process that measures and tracks meaningful things is complicated and sometimes difficult for most companies. The challenges to building an effective analytics process are broad in scope, ranging from attitudes, skills, technology, and resources. Just 6 percent of companies claim not to have any challenges related to marketing analytics.⁶ Figure 2-7 summarizes the biggest challenges that companies have with their marketing analytics efforts.

It’s worth noting what isn’t a big challenge to marketing analytics: buy-in or support. Over half the participants in the survey from which this data is drawn are marketing leaders: CMOs, brand managers, vice presidents of marketing, marketing directors, or marketing managers. What they tell us through this survey is that getting the buy-in from their own teams is negligible as a challenge. Members of the marketing team understand that it is in their best interest to have an analytics process. The challenge of securing the support of the executive or management team is also negligible. Rightly so, because what executive or manager would essentially communicate to the marketing team that it doesn’t desire accountability, ROI, or measurable value by failing to encourage an analytics initiative? The lack of support from above or below is not a serious challenge to analytics for CMOs.

The greatest challenge is not having the systems or infrastructure to measure and track marketing analytics. The modern marketing organization uses multiple channels, most of them digital, and the campaigns and content that marketing produces are consumed across multiple devices. The problem this environment creates is not a lack of analytics data, but a plethora of it. The volume and variety of data coming at the marketing team can leave it feeling like it’s drinking from the fire hose. To capture and fully exploit it as part of an analytics process requires some technology. The data is simply too vast and varied to deal with through manual processes. The analytics initiative needs a technology assist to capture the data and make sense of it. Chapter 8 explores some of the tools, systems, and technologies that the modern marketer can use to overcome the systems challenge of marketing analytics.

The lack of time or staff for marketing analytics represents another significant challenge. Implementing an analytics process is a strategic endeavor, and for busy organizations, taking the time to plan and execute it seems analogous to changing the tires on the vehicle while it’s still in motion. These busy marketing organizations look forward to a time when things are calm enough to allow them time to conduct the proper planning to implement analytics well. However, there is no such thing as slack time in busy organizations. Most are busy because in the absence of an analytics process, activity is the evidence of progress. The organizations that claim to not have the time for analytics are the very ones that need it most. To them, the notion of stopping the marketing vehicle, even to make enhancements that will enable better performance, is anathema.

Staffing for analytics is a challenge that reflects priorities. Few marketing organizations—even those that guide their efforts with an effective analytics process—claim to have all the staff they need. An analytics process is the foundation for marketing excellence and achievement. It’s unthinkable to fail to devote staff to the process because this factor is critical to marketing’s long-term success. Staffing the analytics function should have top priority, because the output of the process can help make the business case to staff and fund other areas of marketing.

The lack of knowledge or expertise presents another challenge to marketing analytics. The question marketers should ask is: knowledge or expertise of what? As long as there has been a marketing discipline, it’s been important to understand the customer and products well. This will never change. When analytics enter the picture, it’s natural to assume that statistical prowess is necessary. It certainly isn’t a liability to understand statistical processes, but neither is it an imperative.

What’s increasingly critical for the modern marketer are technical skills, or perhaps more accurately, technology skills. The ability to effectively use the software and technology at our disposal is fast becoming the critical distinction on marketing résumé. Skilled modern marketers that are at the top of their profession blend the traditional creative skills of marketing with ­technical skills. “Software is marketing’s interface to reality,” says Scott Brinker.⁷

Modern marketers don’t need to know how to use every solution depicted in Figure 2-1, but there’s a good chance they will use one solution from most of the categories. These solutions enable the capture and tracking of the performance data for an analytics process. The good news for marketers is that the capabilities of these solutions continue to expand while they become easier to use. Still, having a firm grasp on the technology for marketing is no longer a luxury but a necessity, and marketers cannot outsource the technical part of marketing to the IT department. Modern marketing organizations must invest in acquiring and growing their technical capabilities, not just for success with analytics but for all of marketing’s work.

The final challenge that Figure 2-7 summarizes is identifying and tracking meaningful analytics. Although selected by just 16 percent of participants in the study, it is perhaps the most difficult challenge to overcome in the journey toward becoming data-driven. Once all the other challenges are overcome—systems, resources, staffing, and skills—this challenge remains.

Marketers don’t have to stick their toe very deeply into the analytics pool to understand the seriousness of this challenge. The activities of modern marketing create lots of data. It’s relatively easy to pick something, start tracking it, and make some summary graphs with trend lines headed in what seems like the right direction. The problem is one of relevancy. It’s gratifying, for example, to know that a particular email blast had a higher than average open rate, or to know how many times a social media post is shared. These things are relatively easy to count, but how do they count in terms of creating value? As William Bruce Cameron put it, “not everything that can be counted counts, and not everything that counts can be counted.”⁸

The challenge for marketers is to identify metrics that matter. This process cannot begin with looking for whatever metrics are available or just tracking existing marketing processes. Instead, the metrics identification process has to start with understanding the strategic objectives marketing is pursuing. It is a top-down approach. To do otherwise is putting the horse before the cart. Marketing must determine what metric provides evidence of effectiveness, value, or meaningful outcomes in the pursuit of its objectives.

After identifying the best metrics, the ideal is for those metrics to come directly out of some system in real time and an easy-to-understand, shareable report. Sometimes, this occurs. More often, however, there is no easy, direct path for getting at the best set of metrics for an analytics process. Marketers will find they must derive the right set of metrics from multiple sources, blending and calculating numbers to arrive at something that truly indicates how a process is performing and what value it is producing. This is a process of planning, testing, and refining. It can easily take several reporting cycles to get it right, and even then, it requires periodic validation to determine if the numbers still have meaning.

Marketing Analytics Capabilities

This chapter has explored the landscape, attitudes, and challenges associated with marketing analytics. Having provided the big picture, we conclude with a brief, high-level discussion of the capabilities and limitations of marketing analytics.

So far in this book, a number of metaphors have represented marketing analytics: dashboards, a servant, guardrails, and so on. These metaphors accurately convey an understanding of what marketing analytics do: provide direction and guidance. When properly implemented, the analytics process emits a steady stream of information that is useful for:

1. Understanding marketing’s performance. For internal use, the metrics an analytics process uses tell marketing how it is performing. To use the dashboard metaphor, when the gauges are in the green, marketing can continue performing its work with confidence, even accelerating its efforts. When the gauges are in the yellow, it’s an indication that something is about to fail and needs attention. When the gauges are in the red, marketing knows with certainty that something is broken, and the broken process requires either an overhaul or abandonment in favor of something better.
2. Reporting marketing’s performance. For external use, the output of the analytics process, or at least part of it, is useful to show the rest of the organization that it is getting a return on its investment in marketing. Sharing the results of it’s work create confidence in across the organization in what marketing is doing, helping the CMO keep marketing’s seat at the big decisions table.

Analytics deliver these important capabilities to the marketing organization. There are also limitations. Analytics don’t lead. The process is not the functional equivalent of auto-pilot for the marketing team. For the marketing function to thrive and provide the greatest value to the companies it serves, it requires strong, visionary leadership from the CMO. The CMO’s vision for marketing should include an analytics process. The combination of vision and analytics produces the highest performing marketing function that can fully account for its work and sustain its contribution. It represents what every CEO wants from marketing.

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¹“Marketing Report Card: Keeping Our Seat at the Table,” Demand Metric Research Corporation, March 2014. http://www.demandmetric.com/content/marketing-report-card-benchmark-report

²Ibid.

³“Marketing Analytics in 2013: Benchmarks, Insights & Advice,” Demand Metric Research Corporation, March 2013. http://www.demandmetric.com/content/marketing-analytics-benchmark-report

⁴Ibid.

⁵Ibid.

⁶Ibid.

⁷Scott Brinker, The Marketing Technologist: Neo of the Marketing Matrix. http://chiefmartec.com/2013/12/marketing-technologist-neo-marketing-matrix/

⁸William Bruce Cameron, Informal Sociology: A Casual Introduction to Sociological Thinking. New York: Random House, page 13.