All of us in the direct response industry talk about the importance of gaining further understanding of our client’s customer.   And today, frankly, we’re all in direct response in one way or another. So we employ the use of syndicated data to reveal demographics of the category, we ask our clients for studies against their own customers and we even conduct surveys ourselves in order to gain additional insight. What we are often missing in this exploration is capitalizing on our client’s own database and improving our understanding of the complexity of a target through segmentation.There is actually a wealth of information sitting in our client’s current customer database that is too often ignored. Our role as leaders in the direct response field is help, through database segmentation, to provide creative and media with an in-depth understanding of who we are trying to reach. By employing the use of long-established tools such as Prizm and GfK MRI, for example, to segment our clients’ data, we are able to not only improve testing and expand our media program, but greatly improve the creative messaging as well.

Here is an illustration of how segmentation can improve communication. Years ago, I was involved in creating the media strategy for a national pizza chain located in the Midwest. When I looked at the customer data, it appeared that a pizza purchaser was just about anybody. You needed to be an adult 18-54 and be breathing for us to sell you a pizza. It was easy to develop a media plan against such an extremely broad age cell.

However, during our planning process we went a step further and by using a combination of syndicated data we were able to actually see that this broad target was comprised of two groups of heavy pizza consumers: busy suburban moms with children present in the household and young male college students. We could make the decision to try to attract these two groups with one bland message, or we could actually create two very disparate campaigns and increase our success by speaking to these two groups in their own language.

How does the process work? We take Prizm and run our client’s database against the clusters to determine the highest indexing clusters. Once we identify the clusters, we combine clusters into groups we call Super Clusters. Then we run each Super Cluster against GfK MRI to obtain a wealth of information about the group, including not only demographic and media habit information but also extensive psychographic and purchase behavior data.

Once we obtain the segments, each group each group should be approached as its own campaign. Messaging should be focused on what appeals to that particular segment. We would be hard pressed to create a campaign that not only appeals to a busy mom but to a young male college student as well; generating two campaigns appealing to each improves our communication and our media program.

As we view the future of the television industry with addressable media around the corner, you can see how employing the use of segmentation today prepares us for the extreme nature of the segmentation of tomorrow. Used intelligently, these consumer insights can improve our clients’ business dramatically.

This commentary is insightful. I recommend it to others.