In a previous post “A 3-Step Approach to Marketing Analytics” we outlined a simple methodology for the application of measurement and analytics in marketing. Despite widespread acceptance of the need to be more analytical and metric oriented in marketing, many marketers still struggle.

This post explores step one “Understand” in more detail to identify the types of questions marketers should ask and the marketing analytics capabilities that empower the answers to these questions.


As marketers we consume tremendous amounts of time, energy, and budget executing what we hope to be meaningful marketing campaigns. We all know, probably too well, that attempts to conduct analytical results in marketing are rarely straightforward. Marketing by nature is both an art and a science, and sometimes the art just doesn’t translate to numbers. But, every qualitative result starts with one or more variables. Therefore, before embarking on any marketing analytics initiative, marketers should seek to understand all facets of the outcome and the variables that make up the decision up front.Marketing Analitycs The 3 Step Approach to Marketing Analytics: Step 1 – Understand

Try to Understand:

  • The Problem Itself
  • The Availability of Data
  • The Strategic Outcome Desired
  • The Assumptions
  • The Technology Requirements

Framing the Problem

It’s helpful to pre-define exactly what business challenge you are trying to solve and then back into the variables required to sufficiently answer the questions.

  • What information is available to you?
  • Have you developed a working hypothesis of what you ”think” is the answer?
  • What business problem, challenge, or question do you need to solve?
  • What would the analysis look like?
  • Can the result be translated into business strategy?
  • Why do you need to know the answer to a problem?
  • Does knowing the answer to this question have a material impact on current corporate objectives

Common Asked Questions in the “Understand” Phase

Let’s begin with an example. Let’s say Jane owns a book store on a popular street in Paris. Jane does reasonably well in sales and consistently spends the same amount on marketing each year. But, what keeps Jane up at night is the fact that she really doesn’t know how effective her marketing is. Could she shift dollars to other channels and get better results? Are there certain customer segments that react differently to different marketing strategies? Jane needs to understand her customers. She also needs an understanding of the type of results that will definitely tell her how to allocate her budget. She needs to understand what customer data is available for analysis. She needs to understand which marketing analytics capabilities are accessible to her.

At this point, Jane is largely trying to answer questions that revolve around strategic issues such as:

  • Propensity to buy a particular product/service
  • Best communication channel for a particular message/offer
  • Breakdown of recipients/customers

Enabling the “Understand” Phase with Technology

The next question is: what types of tools and technologies might be necessary to physically measure one or more of the above questions?

Descriptive analysis: Descriptive analysis delivers an aggregated and consumable way of describing large volumes of data that would otherwise be impossible to interpret. For example, instead of analyzing behavior from each customer, Jane may choose to analyze the average number of times customers come in over a given period of time and the products they bought each time. Thus, in aggregate Jane may be able to ascertain some key segmentation trends. Descriptive statistics should be readily accessible in your conversational marketing technology – along with an aggregate repository for storing customer data.

OLAP technologies: OLAP stands for Online Analytical Processing. While it’s not typically in the marketer’s handbook of vernacular, OLAP provides multi-dimensional analytical queries, especially on large volumes of data. This allows marketers to cut and layer data attributes for analysis. For example, all products purchased in March by customers who spent more than $20 last year.

Data visualization: They say a picture is worth a thousand words. Well for marketers, it’s also a great way to analyze and isolate trends in large volumes of data. Marketers are by nature creative, and while a spreadsheet or table could have all the answers, it might not be so obvious until it’s graphically displayed in a chart, figure, or infographic.

Integrating the “Understand” Step with Conversational marketing

The underpinning of conversational marketing is numerical analysis. Marketing today is about building a 1:1 dialogue with prospects and customers. The right message at the right time in the right channel is possible, but it demands organizations concentrate on strategies that are justified by customer behavior and analytical results. Without the right understanding of customer interests and behavior, attempts to sustain such dialogues will fall flat.

In my next post, we will explore step two (Execute) of the three-step approach in greater detail. Stay tuned!