Data Mining Techniques to Enhance Customer Lifetime Value
It is proved by many studies that it is more costly to acquire than to retain customers. Consequently, evaluating current customers to keep high value customers and enhance their lifetime value becomes a critical factor to decide the success or failure of a business. This study applies data from customer and transaction databases of a department store, based on RFM model to do clustering analysis to recognize high value customer groups for cross-selling promotions.
Helen Zhang, Gang Shen and David Jin
C. C. Lin and D. H. Shih, "Data Mining Techniques to Enhance Customer Lifetime Value", Advanced Materials Research, Vols. 225-226, pp. 3-7, 2011