Data Mining Techniques to Enhance Customer Lifetime Value

Abstract:

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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.

Info:

Periodical:

Advanced Materials Research (Volumes 225-226)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

3-7

DOI:

10.4028/www.scientific.net/AMR.225-226.3

Citation:

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

Online since:

April 2011

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Price:

$35.00

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