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Presented by Renaissance Research & Consulting, Inc.
Classical techniques of attitudinal segmentation, like Cluster Analysis, produce interesting groups that are not particularly useful. Targeting methods like CHAID produce groups related to an objective, and therefore useful, but they lack depth and are not interesting. This white paper presents a mix of the two methods - Hybrid Segmentation - as a method that produces segments that are both interesting and actionable.
Anyone who’s dealt with large groups of people – marketing to them, evaluating their opinions – will tell you: the world is complex. People are different in backgrounds, opinions, attitudes, and needs. It’s almost impossible to deal with them as a single, undifferentiated mass; in order to address the world (or the part of it that interests you) effectively, you need to break it down into manageable, meaningful groups. That’s called segmentation.
But many people shy away from segmentation, because it leaves them with a dilemma.
The real problem is to find a segmentation that is both useful and interesting. One possible avenue for solving this, which we at Renaissance Research & Consulting have developed successfully over a number of years, we call Hybrid Segmentation.
What is it? It is a combination of two classic segmentation/targeting techniques:
What does it do? It finds the demographic breaks that split a sample so that it segments as cleanly as possible on a set of needs or attitudes. It then produces detailed descriptive information on each segment, allowing it to be both identified, located, and interpreted.
Hybrid Segmentation can be used to answer questions like these:
How Does it Work?
We can best illustrate how hybrid segmentation works using the following example:
An attitude and usage study was conducted among a series of consumers who were in the market for an automobile in the next twelve months. Among other measures, the study asked the importance (on a five-point scale) of a series of automobile attributes:
The study also collected a full battery of standard demographics on each respondent. Both the importance and demographic batteries were input into the segmentation algorithm (as separate domains).
The hybrid segmentation process is illustrated by the tree diagram below. It proceeds in a series of steps:
The great advantage of a hybrid segmentation is that any segments that are discovered are automatically “identified”, since they come with a “built-in” demographic profile. This has two important consequences, one substantive, the other methodological:
For applications in which segments are needed that are both attitudinally granular and attached to the “real world”, hybrid methodology such as our TargetVoicesm system may be the way to get the best of both worlds.
This content was provided by Renaissance Research & Consulting, Inc. Visit their website at www.renaiss.com.
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