Application of cluster analysis for data driven market segmentation

Abstract

Despite the wide variety of techniques available for grouping individuals intomarket segments on the basis of multivariate survey information, clusteringremains the most popular and most widely applied method. Clustering is a popular and widely used method for identifying or constructing data based market segments. Over decades of applying cluster analysis procedures for the purpose of searching for homogenous subgroups among consumers, questionable standards of using the techniques have emerged one of such is the black-box approach ignoring crucial parameters of the algorithm applied or the lack of harmonization of methodology chosen and data conditions. This research work is all out to capture: which standard of application of cluster analysis have emerged in the academic marketing literature, compare their standards of applying the methodological knowledge about clustering procedures and delineate sudden changes in clustering habits. These goals are achieved by systematically reviewing some data-driven segmentation studies that apply cluster analysis for partitioning purposes.

Keywords: Clustering, Black-Box Approach, Data-driven market segmentation and Homogeneous subgroup