Integrating AHP and Data Mining for Effective Retailer Segmentation Based on Retailer Lifetime Value

Data mining techniques have been used widely in the area of customer relationship management (CRM). In this study, we have applied data mining techniques to address a problem in the business-to-business (B2B) setting. In order to continue its business in a manufacturerretailer- consumer chain, a manufacturer should improve its relationship with retailers. In this regard, segmentation is a useful tool for identifying groups of similar retailers in order to improve retailer loyalty by developing and implementing segment-specific marketing strategies. Therefore, this study proposes a methodology for retailer segmentation based on the value-based segmentation and the analytical hierarchy process (AHP). The proposed methodology is implemented by using the data of a firm in the hygienic industry in Iran. As a result, having found six groups of retailers and labelled them according to their performance, we provide some possible measures that can be taken in order to improve the relationship between the firm and its retailers

Keywords:

Data mining , Value-based segmentation , Clustering , AHP