Authors
Abstract
Financial Service Providers (FSPs) like other organizations can use Customer Lifetime Value (CLV) as an instrument to achieve their targets in Customer Relationship Management (CRM). Although various studies have been done about this concept, CLV case studies are scarce in banking industry. In this research, in order to present a model to determine CLV in banking industry, customers with current account in a bank in Iran were studied. Determining the relative importance of R, F and M variables that are used to cluster customers, ranking the clusters of customers according to their CLV and understanding the best strategies for bank to treat with each cluster are among the other goals of this study. Three main variables were used to apply the model; a) Recency: the length of time since the last transaction (in days), b) Frequency: number of positive transactions and c) Monetary: balance of account (in Rials). Also wR , wF and wM were used as the relative importance of R,F and M variables. We used the ideas of experts and marketing managers and the data of transactions from the random samples of 382 corporate customers and 5113 individual customers, who had current account in 33 branches of a bank in Tehran. The analytical Hierarchy Process (AHP) was applied to determine wR , wF and wM in evaluating CLV. Then WRFM model was used to cluster the customers and rank them based on their CLV for two groups of corporate and individual clients Clustering and Discriminant Analysis techniques were implemented for this section. Finally, the best strategies for bank to treat with each cluster of the customers was determined.
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