Digital Profiles: A New Way To Look At Segmenting Buyers

How many of you find segmenting customers utterly unsatisfying?

You go into your favorite Web Analytics package, and you profile conversion rates across prior visitors. Well, that's fun for about five minutes, then ... zzzzzzzzzzzzzzz, you're sleepin'.

Or maybe you are a cataloger with an RFM scheme from 1987. You know that 7-9 month 1x $100 - $149 AOV customers responded at a 2.94% rate in your August catalog. What does that actually tell you about your customer? Be honest with yourself ... what does it actually tell you about the customers that make up that segment?

What about the OLAP/cube-based wonk who takes twenty-three unique attributes and slices and dices on those attributes ... which is fun, except for the fact that most business leaders can handle one or two or at most three dimensions at one time before becoming completely overwhelmed.

In my time as a consultant, there's two consistent themes that recur:

• Web Analyst or Business Intelligence Analyst: "We have all of this data and nobody at an Executive level ever listens to what we say. We share our results with them, and they just stare at us, and then they make decisions on gut feel and instinct. Why do they do this when we have all of the data and metrics to prove our point?"

• Business Leader: "We have all of this data, and nobody can make any sense of it in an actionable manner. It's like these analysts are speaking a foreign language. I don't understand how customers interact across all of my business units, and my web analyst and business intelligence analyst can't explain it to me in an actionable way."

In the Fall of 2009, I decided that I'd heard each end of the argument too many times, that maybe it was time that somebody did something about the problem.

For the past twelve months, I've been working with a concept called "Digital Profiles". I like to think of Digital Profiles as "Modern Segmentation for Savvy Marketers". For the past eight months, I've thrown a "Digital Profile" component into new Multichannel Forensics projects, for free ... sometimes the embryonic product yielded outstanding results ... sometimes, the results didn't really resonate. That's ok when you're providing something for free.

Now, in the Autumn of 2010, I finally have a systematic process that solves a key business problem.

In the next several weeks, I am going to introduce you to the concept of "Digital Profiles", a methodology that segments customers into unique groups that exhibit similar behavior across a wide variety of dimensions.

In our discussions, we'll explore a multi-channel retailer with about 100,000 twelve-month buyers, a retailer that markets via the following channels:

• Print.
• Online.
• E-Mail.
• Search.
• Social.
• Mobile.
• Retail Stores.

This retailer has nine merchandise divisions (think about tabs running across the top of the website, nine unique areas of merchandise).

This retailer categorizes each zip code as not being in a store trade area, being in one store trade area, being in two store trade areas, or being in three-plus store trade areas.

This retailer categorizes each zip code on the basis of Zip Code Forensics.

This retailer tracks customer recency, frequency, and monetary value.

In other words, this retailer has too much data! This retailer does not have a systematic way to classify customers based on combinations of behavior across physical channels, advertising channels, merchandise divisions, and geography.

I will show you that this methodology combines customer activity across all of these variables, yielding sixteen actionable customer segments. The customer segments can be imported into offline campaign management, execution, and analysis. The customer segments can be imported into your Web Analytics solution, allowing you to analyze customer behavior in new and exciting ways.

In fact, if I were a product manager at Unica, Webtrends, Coremetrics or Omniture, I'd be paying really close attention to this series of posts, because Digital Profiles can be used to unlock complicated customer behavior that normal software applications struggle to illustrate to the end user.

Tomorrow, we begin by illustrating how to generate the data necessary to build Digital Profiles.