Direct marketers have to understand the issues and choices involved in customer segmentation to be able to manage such a project effectively from conception to implementation. Any number of common pitfalls can stand in the way of success. We’ll suggest how they can be avoided.
Goals
Several important considerations must be addressed before you start to segment your customer file. The fundamental goal is to identify groups, segments or clusters of customers (the terms are interchangeable) that from a marketing perspective are meaningfully different from each other.
Obviously we could create segments that differ demographically or in terms of behavior. But will these differences lead to a variety of marketing strategies that will be more effective than a single approach that treats all existing or potential customers the same way?
Intuitively, you know that your customer base, be it 50,000 or 5 million, is not homogeneous. In other words, at any point in time it will contain some good customers, some bad ones; some new customers, some old ones; some young, some old; some rich, some less rich, some poor; some price sensitive, some not; some extremely loyal, some not loyal at all. The list goes on and on.
And, because of this diversity, it makes little apparent sense to market to all customers the same way, i.e., the same level of marketing effort, the same offer, the same copy, the same creative. Yet this is what direct marketers do, perhaps without realizing it, when they search for the best control package in direct mail (the package that works best across all customer files) or the one best script in outbound telemarketing.
When pressed on this, many DMers will point to tests that clearly show that the control packages they’ve developed over time have out-pulled the segmented packages tested against them. So, assuming the testing was done correctly, the question is: Was there something wrong with the segmentation strategy itself, or are the weaker results due to how the strategy was implemented? We think it’s more the latter.
So let’s start our look at the way segmentation projects are initiated.
The first thing you need to decide on is the type or kind of variables you want to build your segmentation around. The three primary types are demographic, behavioral and attitudinal.
Demographic Segmentation
In segmentation systems based on demographic data the emphasis is on describing customers in terms of their personal characteristics (young singles, young families with children, affluent empty nesters, etc.), which through further research can lead to an understanding of their needs, wants and behavior.
While there are several ways to collect customer demographic information, the most common approach is to purchase demographic enhancement data from an outside supplier. The supplier matches your customer list against a large compiled consumer database using name, address and phone number, and then appends the demographic data from the compiled database onto your file.
Because compiled databases and matching technologies are not perfect, you will never obtain demographic data for every customer. Usually, hit rates will range from 50% to 80%. Records that do not receive this type of demographic data can be backfilled (or approximated) by appending geodemographic data
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