Data-mining application for country segmentation based on the RFM model

For effective Customer Relationship Management (CRM), it is important to gather information on customer value. Segmentation is the method of knowing the customers and partitioning a population of customers into smaller groups. This paper develops a novel country segmentation methodology based on Recency (R), Frequency (F) and Monetary value (M) variables. After the variables are calculated, clustering methods (K-means and fuzzy K-means) are used to segment countries and compare the results of these methods by three different criteria. Customers are classified into four tiers: Top-active, Medium-active, New customer and Inactive. Then a customer pyramid is drawn and the customer value is calculated. Consequently, the data are used to analyse the relative profitability of each customer cluster and the proper strategy is determined for them.customer segmentation; data mining; RFM model; customer relationship management; CRM; recency; frequency; monetary value; clustering; data analysis; customer clusters.