The critical part of any journey is the first step. Taking the first step in the marketing analytics journey represents a willingness, commitment, and desire to become a data-driven, revenue-oriented marketing organization. But it takes more than just desire. Success with marketing analytics requires a plan that encompasses resources, preparations, potential hazards one might encounter along the way, and contingencies. This chapter provides the framework for developing such a plan.

This chapter assumes that the reader is part of an organization that has no analytics process in place and is preparing to begin this journey. As Figure 2-4 revealed, just over a quarter of marketing organizations fall into this category. Other organizations that are further along can still benefit from the information this chapter shares, using it to help benchmark and assess their own process maturity.

This journey has a beginning, but no end. As Chapter 4 shared, the marketing analytics process is a continuous loop. There are, however, some preparatory steps for those who are just starting the journey and checkpoints for those already on it. These milestones include assessing organizational readiness, studying business objectives, determining or clarifying marketing objectives, and establishing the right set of metrics. The remainder of this chapter explores these milestones in greater detail.

Assessing Organizational Readiness

If it were possible to observe how organizations with a mature marketing analytics process operate, you would notice a certain characteristic: they don’t let urgent matters get in the way of what’s important. To these organizations, analytics are very important, not just in marketing but in all business areas. This kind of operational philosophy is actually quite strategic. It’s a reliable indicator that the organization is committed to a plan that is well understood, one that is metrics-enabled, of course.

As organizations embark on the marketing analytics journey, they must first assess their readiness to do so. This path isn’t just about adding another à la carte process to the organizational menu. Instead, for analytics to effect the change and improvement of which they’re capable, organizations must weave analytics into the very fabric of their operational being. For this reason, the first thing to do when preparing to implement a marketing analytics process is to see if the organization is ready to make the journey. The initial areas to assess are the leadership and culture of the organization.

Success with marketing analytics is the product of several characteristics, the first of which is culture, and culture is a function of leadership. If you’re trying to set out on this journey, will your organizational culture allow you to succeed? Even when leadership is providing encouragement and saying “yes” to analytics, the culture of the organization can still represent a barrier. Table 5-1 provides a contrast of cultures as they relate to marketing analytics success.

Culture is a deal-breaker for many corporate initiatives. A healthy culture is a greenhouse for marketing analytics; a dysfunctional culture a desert wasteland. The attributes in Table 5-1 represent the end points on a cultural and leadership readiness spectrum for marketing analytics. You should assess where your company is on this cultural spectrum so that an analytics initiative doesn’t shrivel up and die due to a hostile cultural environment.

Organizations with some or all of their cultural attributes in the “barrier” column must understand that the environment for success with marketing analytics may not exist. The irony for these groups is that their dysfunctional cultures indicate a desperate need for the change that marketing analytics can help bring about. Yet, their cultures are a hostile environment for the marketing analytics process and the accountability it brings.

What must happen in such organizations for marketing analytics to succeed? The culture must change, moving toward the attributes listed in the “catalyst” column of Table 5-1. Such change, however, doesn’t come easily. Cultural change usually requires existing leadership to change, adopting and modeling new attitudes, or for new leadership to replace existing leadership. Either way, cultural change doesn’t occur quickly and it’s rarely painless. Still, marketing leaders should be agents for change in such organizations, advocating for cultural evolution (not revolution) that will create benefits far beyond opening the door for marketing analytics.

Does marketing analytics have any chance for success in organizations where the culture is a barrier? In fact, it does. Cultural evolution and marketing analytics can occur in parallel. Although the cultures in these organizations may not support a formal marketing analytics initiative, it can often get started in “stealth” mode. Without fanfare or even official sanction, it’s possible to start small, have some success, and then carefully expand the scope of marketing analytics. The idea is simple: create some success, and it becomes very hard for the organization to deny the value of the effort. A series of small, real marketing analytics successes can help propel cultural change.

Organizations with some or all of catalyst cultural attributes can proceed with the confidence of knowing that their environment is ideal for a marketing analytics initiative.

Skills represent the second area to assess. There are four critical skill sets necessary for success with marketing analytics: analytical ability, technical ability, insight or understanding, and communications. It is rare to find single individuals with each of these four key skills in abundance, but all of these skills must be present in the organization that wishes to pursue marketing analytics.

The first skill requirement is perhaps the most obvious: analytical ability. This ability really represents a hunger to investigate the data to learn what it can reveal and the statistical and mathematical skills to build and work with data sets and models. Someone who is analytical by nature can learn the mathematical and modeling skills. However, someone who has no taste for analytical work will struggle with it, even if they learn the skills.

What kind of analytical capability must a person or organization have to succeed in marketing analytics? Initially, the requirements aren’t very rigorous. Organizations just getting started with marketing analytics will find that tracking and analyzing basic metrics doesn’t require advanced analytical skills. It’s more simply a matter of having the discipline to do the work, which can amount to little more than reviewing the data. In the early going, much of the analytics work is as simple as capturing the data, reviewing it, and determining what to do as a result.

As the organization’s marketing analytics maturity grows, so will it’s proficiency. The progression and maturation of the marketing analytics process will lead to the need to use basic, applied statistical techniques to examine not just individual metrics but the relationship between some of them. Techniques like cross-tabulation and correlation analysis can provide a deeper understanding of the analytics data, helping explain how a change somewhere in one part of the marketing ecosystem might ripple through to affect an outcome in another part. Experience with statistical tools like SAS or SPSS can help the analyst perform this deeper analysis.

Developing a deep understanding of customer behavior has long been the Holy Grail of marketing and a marketing application of Big Data analytics. Gaining valuable insights about customers and their behavior requires marketers to exploit a wide variety and high volume of customer transaction data that is both structured and unstructured. Advanced mathematical and analytical skills are required to build the data sets and models associated with Big Data and predictive analytics. Chapter 10 will cover Big Data in greater detail. The insights available through Big Data and predictive analytics are game-changing for many companies. The advanced skills necessary to do this type of analytics work represents the most mature end of the marketing analytics spectrum, one that takes some time and experience to reach.

The second skill requirement area is technical ability: proficiency retrieving data and using analysis tools on it. This could be considered an IT skill set. The data a marketing analytics process uses as input is usually found in various systems throughout an enterprise. There isn’t a “system of record” for marketing analytics that houses all the data the process might need. Marketers will need technical skills to retrieve the data from the places where it is stored, and the technical requirements to do this range from very simple to complex.

Some data is retrieved through easily structured queries into systems that house it, using a simple graphical interface to get the job done. Other systems require database programming skills, such as the use of Structured Query Language (SQL) to retrieve what is needed out of databases where it is stored. As the marketing analytics process matures, it is highly likely that data from several sources will need to be combined into a single database to analyze it, draw important insights from it, and report results. Doing this often requires the use of a business intelligence tool. Part of the marketing analytics readiness assessment must therefore consider if marketing has access to the technical skills required to support the process.

The analytical and technical skills are often found in the same person; even when they’re not, someone who is strong in one of these skills is predisposed to learning the other one. This skill combination, however, is often not found on the marketing team, and this must change, not just for the sake of analytics but for all marketing work, which is increasingly technology-based or -driven. As Scott Brinker, author of the Chiefmartec.com blog puts it, “You must be the driver of marketing technology, not merely a concerned passenger.”²

The third skill requirement to assess is the ability to understand what the marketing analytics mean and what to do about it. Perhaps the best way to describe this is as insight. The analytical and technical skills will yield a result as an output of the process, but without the capability to draw insights from these results, the marketing analytics process will disappoint. The skill of drawing insights out of the analysis is often the result of experience, inquisitiveness, outside-the-box thinking, and the ability to see the big picture. Someone who is good at making the complex seem simple and who can see the inferences in the results will often have this skill.

This skill area is difficult to describe and even more difficult to measure. What kind of people have these skills? They are generally those who have the capacity to process a lot of input, view it objectively, draw inferences from it, and see what isn’t obvious. They have excellent critical thinking skills and are not prone to jumping to conclusions. People who have this kind of insight are able to look beyond the numbers and discern what the numbers mean. Their ability to understand the implications of the marketing analytics process output is crucial to the effort. Some may argue that what is described here isn’t a skill at all but in inborn talent. Whatever it is, having this capability is important to the success of a marketing analytics effort.

Communications are the fourth and final skill area to assess. Marketing can build amazingly accurate mathematical models of their work, perform detailed analysis of its marketing analytics data, and draw insightful conclusions about the implications of it all, but get no benefit from it if the results aren’t communicated well. The communication that must occur goes far beyond simply distributing reports. What is needed is a communicator who can speak with authority and conviction about the insights gained through the marketing analytics process.

The communications that must occur around the marketing analytics process is not mere reporting of results. (If that were the case, then a simple email message would do). Instead, what is needed is a leader who can objectively convey what is going on as reflected by the analytics, helping the rest of the organization not just understand it but believe in it. The communications that must occur are formal and informal. The person communicating on behalf of the marketing analytics process must master the board room presentation to the executives as well as the break room conversation around the water cooler.

Part of the skill in communicating in this context is knowing the level of detail to convey. Marketing analytics can certainly consist of a lot of detail. Some will need to understand the intricacies of the process, whereas others will just want the results summary. The person doing the communications about the process will need to understand at all times who the audience is and what their information needs are. To use a metaphor, the executive who asks “what time is it?” doesn’t want to hear a set of instructions for building a watch as a reply. It’s easy for someone who is intimately familiar with the analytics process to overcommunicate about it, but that usually won’t win people over. A person who is adept at communicating about marketing analytics understands how to convey meaning succinctly while providing detail when it is helpful to do so.

The person who communicates about marketing analytics must also be a teacher and evangelist for the process. This requires the discernment to know who doesn’t understand the value and results of the process and then educate them. In a similar way, the communicator is also always promoting the process, ensuring that the organization understands how the results help not just the marketing function but the entire organization. The communicator is therefore a leader, teacher, persuader, defender, promoter, and advocate of the marketing analytics process.

Finally, the communicator must understand the necessity of being transparent. The organization can’t selectively choose to only communicate when the analytics indicate that marketing is producing good results. The communication must occur regardless of what the analytics show about marketing’s performance. This is the accountability dimension of the analytics process, and marketing cannot shy away from it or censor its output if the process is to work. The better marketing becomes at using analytics, the more frequently it will have good results to report. Even when it doesn’t, the right corporate culture will respect the marketing team for its transparency.

As with the first two skills requirements—analytical and technical—it is also quite possible that the insight and communications skills are found in the same person. Unlike the first two skills, these last two skills are often found within the marketing team. What is rare, however, is for a single person to possess all these critical skills. For this reason, marketing analytics is best viewed as a team endeavor, with several people coming together with the necessary skills under the direction of a leader with a vision for using analytics.

Although analytic and technical abilities are hard skills and insight and communications are soft skills, they are equally important. Table 5-2 provides a simple assessment mechanism for rating current skills required for analytics. Use it to take inventory and assess the current skills available in your organization for marketing analytics. Place a check mark in the column for each listed skill that represents your current state, and develop a plan for addressing any deficiencies.

The next major area to assess is data. Do you have access to the data you need to support the metrics you’ve defined for your marketing analytics process? The challenge is that there really is no “system of record” that contains all that marketing will need to support a robust analytics process. Chapter 4 discussed the process of identifying metrics for this process. It’s important to have the metrics identified first, so that the availability of data doesn’t overly influence what gets measured. In other words, don’t let the tail wag the dog: don’t measure what you can measure because you have the data available. Measure what you should measure, and figure out how to get the data to do so.

To assess if you have the data you need as input for your marketing analytics process, first study the metrics you’ve selected for tracking, analysis, and reporting. What data is required for these metrics? Does it exist? If so, where? If it doesn’t exist, is it obtainable? What effort is required to have access to accurate, reliable data needed for your marketing analytics program? Your data availability assessment must answer these questions.

Although there is no single system of record for marketing, some systems provide much of the necessary data, at least for the basic metrics. For example, an organization that is executing a digital marketing strategy and also using a marketing automation solution will find that much of the data it needs to measure landing page visits or clicks on call-to-action buttons (conversions) is captured automatically and easily accessible. Likewise, almost anything an organization needs to know about its website performance is available through the use of Google Analytics. Data for most of the basic sales activity metrics, web metrics, and digital marketing metrics are available in various systems such as customer relationship management (CRM), marketing automation, or web analytics systems.

As the marketing analytics process matures, metrics become more sophisticated, and they are often derived from multiple data sources. For example, calculating the cost of new customer acquisition may require data from marketing automation and accounting systems. Likewise, determining the conversion rate from qualified leads to sales for a campaign may require access to CRM and web analytics. In general, the more informative metrics, particularly the ones that show a link to revenue, are often derived from multiple data sources. If the data exists in some sort of system or database, it is often possible to automate the extraction and derivation of the metric and present it in some sort of report or dashboard. The use of tools for this purpose is discussed further in Chapter 8.

It’s always possible that the metrics the marketing organization wishes to use are not available in any existing system or source of data. When this is the case, the organization will have to determine how to get the data it needs. For example, suppose that marketing determines some sort of advocacy metric is important to track as part of the analytics process. It may decide to use Net Promoter Score³ (NPS) and therefore will implement some sort of surveying mechanism to gather the NPS data. Other metrics may also require the implementation of systems, processes, or both to collect the necessary data. Your data assessment should consider where the data could come from and what it will take to collect it.

Table 5-3 provides a template for doing an assessment of the data your marketing analytics process requires. To use it, list each metric in the leftmost column, and under the appropriate data columns, briefly describe the source of the data. If the data does not exist (rightmost column), describe any options for obtaining it. When complete, develop a plan to address the metrics for which data does not currently exist. If the degree of difficulty of obtaining the data is too high or it’s too costly to obtain, you may need to reconsider how practical the associated metric is.

The final area of assessment is the budget. Are funds allocated to support the startup of a marketing analytics process and for sustaining it once it is in place? Resources are required to reach success with marketing analytics. The importance of completing the assessment suggested here is to understand the level of investment the process will need to work as it should. Once the funding requirement is understood, make sure the organization is willing to commit to it before proceeding.

When planning the marketing analytics budget, some of the places to invest may include some or all of the following:

• Staffing: additional headcount to properly own and administer the marketing analytics process. It’s likely that additional staff are needed for the first two skill areas discussed previously: analytical and technical abilities.
• Systems: the necessary systems for collecting, tracking, analyzing, and reporting on data needed as input to the marketing analytics process.
• Training & and education: even if the staff is available, the skills may not be. Training and education are often needed to equip the team that will manage the marketing analytics process, and to provide some level of continuing education.
• Outside consulting, services or expertise: the fastest path to effectiveness in marketing analytics may go through outside expertise. Consulting and services can often help accelerate the implementation and success of the process.

Marketing analytics isn’t an expensive endeavor, but it requires some funding if it is to have impact. Figure 2-5 summarized data collected from more than 700 executives and marketing professionals about the percent of their budget allocated to analytics. As that graph and the related discussion in Chapter 2 reveals, the return on marketing analytics is proportional to the investment made. Those organizations allocating the greatest portion of their marketing budget to analytics are claiming the get the most from their efforts.

What is the right level of investment in marketing analytics? As Chapter 2 discussed, that level appears between 6 and 10 percent of the marketing budget. This level is a guideline. Common sense should prevail when it comes to funding marketing analytics, making sure that the funding is adequate to enable the success of the process.

Reviewing Objectives

Marketing’s work should support corporate objectives. When developed the right way, marketing’s strategy and objectives are built from a deep understanding of corporate goals and objectives. Marketing’s purpose, is after all, to help the organization succeed in pursuit of those objectives.

Marketing analytics should directly reflect the organization’s marketing strategy, and less directly the corporate objectives on which that strategy is based. For this reason, an important part of getting started with marketing analytics is to determine, refine, or clarify both sets of objectives: marketing’s and the corporation’s. These objective must remain in clear focus as the marketing team is putting together its own strategy and the analytics that measure how well it is working. A clearly discernible thread of continuity should run from the marketing analytics process through the marketing strategy to the corporate goals and objectives.

Marketing analytics implementation planning should begin with a review of corporate goals or objectives, which are typically stated at a fairly high level. Corporate objectives represent what the organization wishes to accomplish. The marketing strategy is an expression of how to meet those objectives, and analytics are then the success indicators.

For example, a common business or corporate objective is to improve profitability. All departments within the company should determine what strategy they should execute in pursuit of this and all other corporate objectives. Marketing may determine that it will pursue two strategies to improve profitability: increase market penetration of current solutions in established markets and improve customer retention. Marketing will then plan its work around these two elements of strategy, each of them cascading into multiple tactics or projects.

Of course, each initiative should have some metrics associated with it. When the marketing initiatives and metrics are developed from the top down as described here, the organization has some level of assurance that there is alignment between the top-level corporate objectives and the things marketing is doing. Having alignment or continuity between corporate objectives and marketing’s work is imperative. One way to ensure it exists is to start the strategy planning process by using the corporate objectives as input and keeping those objectives in mind throughout.

Although starting the marketing planning and analytics process with corporate objectives doesn’t guarantee success, it does ensure you’re oriented properly. This approach, as Stephen Covey describes it, “begins with the end in mind.” The chances that the ensuing strategy and metrics are the right ones are much higher.

This planning process of deriving the marketing strategy from corporate objectives is not difficult to understand, and not too difficult to complete assuming that a clearly articulated set of corporate objectives exists. What if there are no stated corporate goals and objectives? Is marketing just to develop its strategy and related analytics in a vacuum? What is marketing to do in this situation?

It’s a reality that not every organization’s leadership understands the value of intentionally developing and then communicating the top-level objectives to the employees. It’s not that such objectives don’t exist—they often do inside the head of the leader—it’s that they’ve never been communicated well (or at all). The reasons for this lack of communication vary: failure to see the need, lack of leadership or communication skills, or just the assumption that they’re obvious to everyone and therefore don’t need communicating. Whatever the reason, in this situation marketing must do its best to discern the corporate objectives before setting a strategy in place. The solution is often as simple as sitting down with the CEO for a discussion of objectives.

The thing to keep in mind as you start a marketing analytics process: always make sure that the analytics track and measure the execution of the marketing strategy, and that the marketing strategy is based on corporate goals and objectives.

Establishing Metrics

All the planning for marketing analytics eventually comes down to selecting appropriate metrics, putting a process in place to measure and track them, and then doing something with the data.

When you’re just getting started with analytics, it’s not wise to put every conceivable marketing metric in place. Instead, start with a few of the most relevant metrics and build the portfolio up over time as you gain proficiency with the analytics process. In fact, what is likely to happen is that the initial set of metrics you select will lead you to other metrics you’ll want to track as well.

What is the right set of metrics for a marketing analytics process? The answer depends entirely on an organization’s marketing strategy. As discussed in the previous section, the best or right set of metrics are derived from the marketing strategy. There are some categories of metrics that are commonly used in the marketing analytics process. These include metrics for the marketing process, customers, lead generation, and social/digital marketing.

Your portfolio of metrics should include some that indicate how productive the marketing team is. As previously cautioned, these can easily become “vanity” metrics, but when they’re used properly, they help the team understand how efficiently it is working. Example metrics in this category include assets created, impressions generated, year-to-date budget status or ROI, a subject covered in detail in Chapter 6. The right metrics in this category are those that help the CMO and the marketing team know how well it is getting its work done.

The metrics portfolio should also include some customer metrics. These metrics serve as the vital signs for customers and are one of the most important marketing metrics categories. A number of important metrics fall into this category, including customer lifetime value (CLV), customer satisfaction, customer retention rates, Net Promoter Score (NPS), cost of new customer acquisition, and customer churn rates. Almost all of these metrics are tremendously valuable when it comes to understanding the economics of marketing’s work and its impact on revenue.

Any business needs a steady stream of new prospects or leads to generate sales and grow. The metrics associated with lead generation activities are a very important part of many marketing analytics efforts. In fact, lead generation is the primary activity for many marketing teams, and because much of the work of lead generation is digital, there’s a rich set of data available for collection and analysis. Performance of lead generation processes is tracked a number of ways, including new leads by channel (e.g., email marketing, social media marketing, mobile marketing), new leads by campaign, lead flow or volume, new opportunities created, qualified leads created, conversion rates, cost per lead/qualified lead, and of course revenue generated.

The final category of metrics is broad and expansive: digital marketing. Within this category, there are sets of metrics for measuring the growing list of digital marketing channels. Some of these digital marketing metrics are:

• Website: traffic sources, most visited pages, search ranking, visits or unique visits, time of site or page, bounce rate, and exit pages are all potentially important for measuring website performance.
• Social media: social network reach (followers, fans, subscribers, or contacts), shares/retweets, engagement, posts, and referral traffic. Your social media metrics should include your blog.
• Email marketing: database or list size, number of sends, open rate, click-through rate, and bounces are all standard metrics for email marketing.
• Digital advertising: this includes pay-per-click and other forms of paid, digital media. Key metrics could include impressions, click-throughs, inquiries, landing page views, conversion rate, opportunities identified, revenue generated, and program ROI.

What is presented here is just a sampling of the metrics available to support a marketing analytics program. Each organization will have a slightly different portfolio to support its process. The right ones measure marketing’s success in the execution of its strategy and show real results. Organizations that are getting started with marketing analytics should select just a few to launch their process; as they mature, they will want to have metrics for each of the categories described here.

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¹David Raab, “Winning the Marketing Measurement Marathon,” September 2010, http://www.marketo.com/_assets/uploads/Winning-the-Measurement-Marathon-final.pdf.

²Scott Brinker, “Rise of the Marketing Technologist,” Chiefmartec.com blog, April 18, 2010, http://chiefmartec.com/2010/04/rise-of-the-marketing-technologist/.

³See http://www.netpromoter.com/why-net-promoter/know/.