RIS ID
9785
Abstract
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.
Publication Details
This paper was originally published as: Dolnicar, S & Leisch, F, Data-Driven Market Segmentation - A Structure-Based Conceptual Framework for Managerial Decision Support, Proceedings of the Australia and New Zealand Management Academy Conference, Adelaide, South Australia, 1-3 December 2003.