Using Data Mining Techniques with RFM Model to Estimate Customer Lifetime Value: a Case Study
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Abstract
Through this paper, we aim to find a simple and practical way to segment customers on the basis of their profitability, as we explain the concept of customer lifetime value (CLV) RFM model and data mining (DM), and by applying the RFM model to an industrial organization transaction database with a data mining technique represented by the aggregate K-means Clustering algorithm, we estimated the lifetime value of each group of customers obtained, the results showed that using this method facilitates the allocation of resources and the development of appropriate marketing strategies.
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