Methods in segmentation

Abstract

Irrespective of the method used, market segmentation analysis is exploratory in nature. This means that any analysis, with any kind of data, will lead to a result, and different competing solutions might emerge where no clear best solution is discernible. It is critical, therefore, to be aware of all potential methodological pitfalls. This chapter discusses all steps required for successful application of both common sense and data-driven market segmentation. Critical decisions are highlighted. In particular, in data-driven market segmentation: (1) data should be collected carefully and in view of the intended segmentation analysis; (2) the sample size should be sufficient to accommodate the number of variables in the segmentation base; (3) data structure should be explored to learn about the most appropriate segmentation concept and to select the most suitable number of segments; (4) a suitable algorithm should be chosen; and (5) segments should be profiled in detail to meaningfully inform target segment selection and, ultimately, the development of an effective marketing mix.