Abstract
The main theme of this paper is the use of so-called fuzzy clustering methods for market definition and segmentation. Market boundaries are formed according to substitutive relations between brands as seen by homogeneous segments of potential or actual customers. The classification types partition, overlapping classification and fuzzy partition are explained. Segmentation of customers is conceived as a pre-processing step of market definition. Segments are aggregates of customers homogeneous with respect to the substitutive relations between brands. Several fuzzy clustering methods are presented. Evaluation procedures specialized in fuzzy classifications or suited for fuzzy and non-fuzzy classifications are dealt with. One of these procedures is an enlargement of the ADCLUS-model for fuzzy membership values of objects. An empirical pilot study demonstrates and compares the methods discussed. Diverse hard and fuzzy clustering methods are used to form homogeneous segments of customers and sets of competitive brands. External and internal validity of this classifications are determined.
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