SEGMENTATION BASED ON DATA WAREHOUSE INFORMATION

Throughout this book, there is an ongoing discussion about two ways of doing needs-based segmentation depending on whether it is generated from a DW or from questionnaire data, where needs-based segmentation is defined as a categorization of customers with similar buying criteria, which could be based on prize or different product features like the safety of a car, the comfort of a car, the carbon footprint of a car.

If your needs-based segmentation is based on DW data, to a certain extent, the segmentation must have been created based on your own organization’s customer information through the use of analytic techniques. The benefit of this sort of analysis is that it is relatively easy to make segmentations of your full customer base (depending on your data quality). That is, you know on a one-to-one basis which customers belong to which segment. This is in contrast to a situation where you have five segments based on an abstract segmentation model, but you do not know which customers fall into which of the five categories.

Internet-based companies are an interesting example of stores that naturally could focus on a one-to-one relationship with their customers since they have vast amounts of transactional data from the web logs and eventual transactions. These web logs can inform companies about how the customers came to their homepage, how they click around, who purchases what and how often, what typically is purchased together, ...

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