عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Data mining is a powerful new technique to help companies mining the patterns and trends in their customers’ data, then to drive improved customer relationships, and it is one of well-known tools given to customer relationship management (CRM). Segmentation is the method of knowing the customers and partitioning a population of customers into smaller groups. The goal of this paper is developing a novel country segmentation methodology based on Recency (R), Frequency (F) and Monetary value (M) variables of Edible Fruits export from Islamic Republic of Iran to other countries during 11 years (1995-2005). 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. By using customer pyramid and decision tree, clusters are classified into four tiers: Loyal customer, Active customer, New customer and Inactive customer. Consequently, the data are used to analyze the relative profitability of each customer cluster and the proper CRM strategy is determined for them.