Segmentation Approach for Athleisure and Performance Sport Retailers Based on Data Mining Techniques

This paper seeks to compare certain customer segments from two sport footwear, apparel, and equipment retailers and to examine an objective market segmentation method, based on the recency, frequency, monetary (RFM) and the decision tree (DT) models. The case study is based on two data sets, aiming to compare the different customer segments, both from sport retail industry, and represents an application of data mining techniques in a business environment. The customer segmentation enables the customer selection for the future direct marketing campaigns based on the previous purchasing behavior. Analyzing the customers' purchasing history can help the company determine the value of each customer and therefore target or not target such customers in the future with promotional materials, based on both the customers' interests and their value. Thus, based on the results, personalized offers can be created for each of the defined customer groups, which may increase the efficiency of the overall campaign, reduce costs, and increase profitability.