Data-driven Market Segmentation – A Structure-based Conceptual Framework for Managerial Decision Support.

Sara Dolnicar, University of Wollongong
Friedrich Leisch, Vienna University of Technology, Austria

Document Type Conference Paper

This conference paper was originally published as Dolnicar, S and Leisch, F, Proceedings of the Australia and New Zealand Management Academy Conference, 2003.


Market segmentation increasingly uses homogeneous groups of consumers determined on the basis of empirical market data as target segments (a posteriori-, data-driven-, post hoc segmentation) rather than splitting individuals according to single, typically socio-demographic or geographic, criteria (a priori-, commen sense segmentation). A vast amount of contributions has been made to improve methodology of identifying or constructing data-based market segments. However, real world data sets often do not contain clearly separated density clusters. Therefore all techniques used in data-based market segmentation can render multiple solutions of similar quality. So far no attempt has been made to construct a framework enabling managers to systematically choose between different segmentation solutions with regard to their practical usefulness. We propose a framework of such kind.