A hybrid approach for market segmentation and market segment evaluation and selection: an integration of data mining and MADM

Abstract

Decision making in marketing becomes more and more sophisticated and two important issues in marketing decisions are market segmentation and segment evaluation and selection. These decisions are two focal points of all companies which many strategies are followed or influenced by them. Decision making is based on information and data mining aims to extract useful information form implicit, unknown and raw data. Clustering techniques are one of the widely used data mining tools which have been used for dividing market into different segments. In recent years, numerous papers about using data mining or multi attribute decision making (MADM) for marketing decisions have been published. MADM tools are used as a natural approach for evaluating alternatives with respect to conflict criterion.Thus, this study aims to integrate these two fields for improving quality of market segmentation's decisions. The proposed methodology is a combination of data mining tools for market segmentation and MADM tools for evaluation and selection of the best market. More precisely, clustering is used to divide a whole market into different segments. Two MADM tools including, step-wise weight assessment ratio Analysis (SWARA) and complex proportional assessment of alternatives with grey relations (COPRAS-G), were applied for market segment evaluation and selection. The most desirable features influencing the choice of a market segment evaluation and selection are identified based on literature study. Grey relation analysis allows incorporating the vague and imprecise information in to the decision model. A real-world data on a laptop market is put forward to illustrate the performance of the proposed methodology. The proposed model could help companies to segment, evaluate and select the best market.