Driver analysis and segmentation are two things marketing research analysts do about as frequently as they run choice experiments. Worse ways of doing driver analysis are easy to identify and also easy to avoid by using demonstrably better methods. The first part of this tutorial covers how and why the poor methods should be avoided and why and how to use better methods instead. Hint: if you’re running correlation or regression, you really need better methods for driver analysis. Less happily, a constellation of mutually reinforcing problems can thwart the segmentation analyst. The longer second part of the tutorial focuses on understanding these several problems and on how to try to avoid them through (a) well-planned research objectives, (b) understanding the nature of your data with diagnostics, and (c) ameliorating as many of the problems as possible using the imperfect tools available to us, namely questionnaire construction, variable selection and clustering algorithms.
