Estimating customer lifetime value based on RFM analysis of customer purchase behavior: Case study

Since the increased importance is placed on customer equity in today’s business environment, many firms are focusing on the notion of customer loyalty and profitability to increasing market share. Building successful customer relationship management (CRM), a firm starts from identifying customers’ true value and loyalty since customer value can provide basic information to deploy more targeted and personalized marketing. In this paper, customer lifetime value (CLV) is used to customer segmentation of a health and beauty company. Two approaches are used: in the first approach, RFM (Recency, Frequency, and Monetary) marketing analysis method is used in order to segmentation of customers and in the second approach, the proposed extended RFM analysis method with one additional parameter called Count Item is used. Comparing results of these approaches, shows that adding count Item as a new parameter to RFM method makes no difference to clustering result, so CLV is calculated based on weighted RFM method for each segment. The results of calculated CLV for different segments can be used to explain marketing and sales strategies by the company.