How Do You Segment Your Customers?

For years, traditional segmentation has focused on what I affectionately call the "four P's" of data. I coined these four P's from several sources over a decade ago in an attempt to define data into useful categories, and I've carried the concept forward in all my work. At its primary level, data is categorized into: Personal Data, Profile Data, Preferential Data and Performance Data.

Traditional rules say that we need to identify the right customers, try to predict their purchase behavior, and influence that behavior through marketing. What is missing in this formula is how to reach these customers. Whom can we possibly reach through e-mail, and how does traditional segmentation help us understand that? When the average open rate for B2C marketers is less than 35 percent, there is a vast majority of your database that is unresponsive to e-mail for some reason, and no form of traditional segmentation will help you figure this out.

I spoke at the DMA conference this year for an audience of more than 150 attendees, moderating a panel with American Airlines, Coca-Cola, Sony U.K. and Marketing Sherpa analyst Stephan Turnquist. Our purpose was not only to expound upon best practices for e-mail marketing, but to challenge the traditional approach to customer segmentation.



For part of this session, I walked the audience through a series of questions, asking them about their personal demographics (age, sex, marital status), financial status (income, FICA score), travel behaviors such as airline preference and participation in loyalty programs (for my American Airlines panelist), purchase behavior of consumer electronics (for my Sony panelist), beverage preferences and consumption patterns (for my Coca-Cola panelist) and then asked how many had purchased the Marketing Sherpa Benchmark report from 2004. I followed this with a series of questions about their e-mail personas: how many e-mail accounts they had (one poor soul had 27 addresses); how many times a day they check their e-mail; and how their patterns change for business e-mail versus personal, by season, and so on. Over half the audience had checked their business e-mail before 8:00 A.M. on a Sunday. There was even a handful of participants answering e-mail as I spoke, on their Blackberrys and Treos.

Part of this process was to help the audience crystallize what questions they should be asking, but even more to discover what questions they should try to answer through their analysis. While you can't get this information from nonresponders or nonparticipants, you can model your top customers and your most active responders, and see which of these traits will help you identify other, similarly active segments to reach.

My question to the group was: which method of segmentation are you practicing today, and how is this helping you increase your reach and response through e-mail?

I could see some people struggling with this concept, but no one really challenged it. Most struggled with understanding how to get this data and how to form an empirical decision to support it. As I often like to say in this column, marketing is an effort in tacit learning, for which there are no clear instructions that will help you become GREAT. The net is, we are in a business of making decisions--and data helps support these decisions. The challenge is in understanding what data is most important and how much you are willing to invest in gathering, mining and storing that data.

While most of us strive to get more out of what we do today, we also need to challenge traditional approaches in order to get to a new level.

I will leave you with some food for thought, borrowed from one of those motivational posters you see on corporate walls: "Positive perspective removes the rust from our minds and helps us see beyond the box we've built for ourselves. Large obstacles seem smaller, long distances can be made shorter and the unknown becomes familiar. Pausing to take a different view and appreciating everything more fully helps us understand where we are going."

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