The Second Key to An Effective Marketing Dashboard

Posted on by Chief Marketer Staff

If you missed part one of this series, we outlined the pros and cons of using a dashboard approach to measuring marketing effectiveness versus an analytical modeling process. Ultimately, you’ll likely need elements of both to develop a comprehensive measurement structure. But in some cases, it makes sense to start with a dashboard and build your knowledge and understanding rather than investing in rocket science analytics that may miss their insight target completely.

To recap: there are 5 Keys to designing and deploying an effective marketing dashboard. They are:

  1. Building cross-functional alignment on the role of marketing in the organization;
  2. Mapping the knowledge base to identify possible critical metrics;
  3. Providing a financial (versus purely strategic) framework for bridging short- and long-term results from marketing investments;
  4. Building a comprehensive brand scorecard; and,
  5. Designing a highly engaging user interface.

The first installment provided guidance on building the cross-functional alignment of influential stakeholders to get the foundation of credibility under your marketing measurement plan. Now, let’s look at the second key:

Mapping the Knowledge base to identify possible critical metrics

It’s amazing how much information is piled high within most large companies today, just waiting to be turned into insight. Which is exactly how you should think of it. Mounds of raw materials (information) stored in file cabinets, hard drives, and the brains of staff, waiting to be transformed and distilled into finished goods (insights). Here are some of the types of raw materials piled up around the company…

  • Data. There are some aspects of marketing effectiveness for which you have data. You did X, and Y happened. Three years of transactional records prove it.
  • Experiments. You may have done some experiments and tested A versus B in various combinations of markets, including control segments.
  • Research. You have marketing research instead of data. According to a survey of 404 customers, 78% found #1 to be more motivating than #2, and 81% of those reported higher purchase behavior.
  • Experience. Perhaps all you have are the experiential observations of managers from around the business who’ve seen enough cycles of “do X, get Y” and have some insights into the correlations between the two.

Like any manufacturing effort, turning this information into insight requires a transformation process. This is where we benefit from the consensus built earlier around defining the role of marketing. Turning information into insight requires, as a first step, taking the definition of the role of marketing and asking “what do we need to know to measure our effectiveness in fulfilling these roles?” and “What questions do we need to answer to help us know?” And therein lies the transformation process – identifying the critical questions that need to be answered.

Once we’ve made a list of the things that we need to know, we can check our inventory of informational raw materials to see if we already know it somewhere within the organization. More likely, we’ll be checking to see if we know it beyond rhetorical wisdom to a level of certainty required to make important decisions on this knowledge.

But what about all those (perhaps the majority of) questions for which we have no consensus on what we know or the quality of our knowledge? The transformation process takes each of these unanswered questions and ranks them on a two dimensional axis of anticipated value of knowing compared to the expected cost or difficulty of getting the information (see Figure 4).

For key information needs in quadrant 1 (high value, easy to get), we should immediately allocate resources to obtaining the answers. Those in Quadrant 2 (low value, easy to get), are likely just distractions to be ignored and filled with reasonable assumptions. Elements in Quadrant 3 (low value, difficult/expensive to get) are traps to avoided. But the ones in Quadrant 4 (high value, difficult/expensive to get) are where we really need to focus.

Without some agreement on how to answer these Quadrant 4 questions, or at least proxy for the answers in the near term while we chip away at them over time, efforts to agree on critical metrics for marketing effectiveness will revert to opinion-gridlock. We need to engage team members, vendors, and outside experts in the development of specific plans to close these knowledge gaps. In the near term, the goal is to come up with the best possible approach to making educated guesses. Granted, the answers may be far from perfect and leave us hungering for greater certainty, but the mere process of approaching the unknowns in this disciplined manner is likely to spread confidence amongst key decision makers in the C-suite. The process will show that we’re making deliberate progress and have a better grasp on our knowledge priorities today than we did yesterday. What seems so small a step can often be a very transformational one in migrating past persuasion-laden arguments to a more fact-based assessment.

In pursuing this process, you’ll begin to develop hypotheses about the relationships between key pieces of information and diagnostic or predictive insights.

– What is the relationship between customer satisfaction and increased profitability?
– Which brand equity components are most likely to cause prospects to buy and customers to buy more?
– At what point in the sales process are prospects most likely to respond to an attempt to close?

These hypotheses lead to the identification of the key risk factors and opportunities to enhance quality and efficiency of marketing initiatives. Those are the initial superset of potential critical metrics for your dashboard. These factor and opportunities help narrow-down your scope of interest to those hypotheses which are most likely to have the greatest impact on marketing effectiveness.

In the early stages, you may have dozens of these hypotheses about key metrics. Rigorously sorting and prioritizing them to eliminate duplicates and redundancies will help reduce the number from ridiculous to merely challenging. At that point you can conduct some simple simulation exercises to help prioritize the remaining candidate metrics.

If this is your first attempt at a comprehensive dashboard, you shouldn’t fear juggling 30 to 40 metrics. The key will be assembling them in a presentation structure that helps promote the recognition of patterns of insight across them, so you can deliberately and consistently refine your focus to the 10 to 15 which matter most.

We’ll pick up this thread in the next installment, and look at how to build measurement structures to bridge the short- and long-term impacts in a financial context.

Parts 3 through 5 of this series will appear here in subsequent issues.

Pat LaPointe is Managing Partner at MarketingNPV (www.marketingnpv.com) – a consulting firm that builds marketing measurement frameworks, analytical processes, and marketing dashboards for Global 1000 companies across industries. He is also the author of Marketing by the Dashboard Light. How to Get More Insight, Foresight, and Accountability from Your Marketing Investments.

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