INTEGRATED APPROACH OF FUZZY MULTI-ATTRIBUTE DECISION MAKING AND DATA MINING FOR CUSTOMER SEGMENTATION

This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy environment for customer relationship management. The main objective is to analyse relation between and considering complex problem of ordering customers segments, which based four criteria customer’s life time value, viz. length (L), recency (R), frequency (F) monetary value (M). proposed integrated approach involves C-means (FCM) cluster analysis as tool. experiment conducted using MATLAB 12.0 identifying eight clusters customers. two tools i.e., AHP (Analytic Hierarchy Process) TOPSIS (Technique Order Preference by Similarity Ideal Solution) are used ranking these identified clusters. applicability technique also demonstrated this paper case Indian retail sector. collected responses from nine experts industry regarding their perception relative importance evaluated weights each criterion AHP. Transaction 18 months store was analysed segment 1,600 into c-means clustering technique. Finally, were ranked Solution). findings could be helpful firms more valuable them allocate resources satisfy them. will developing different loyalty program strategies