On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities

Balaji Padmanabhan () and Alexander Tuzhilin ()
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Balaji Padmanabhan: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Alexander Tuzhilin: Stern School of Business, New York University, New York, New York 10012

Management Science, 2003, vol. 49, issue 10, 1327-1343

Abstract: Previous work on the solution to analytical electronic customer relationship management (eCRM) problems has used either data-mining (DM) or optimization methods, but has not combined the two approaches. By leveraging the strengths of both approaches, the eCRM problems of customer analysis, customer interactions, and the optimization of performance metrics (such as the lifetime value of a customer on the Web) can be better analyzed. In particular, many eCRM problems have been traditionally addressed using DM methods. There are opportunities for optimization to improve these methods, and this paper describes these opportunities. Further, an online appendix (mansci.pubs.informs.org/ecompanion.html) describes how DM methods can help optimization-based approaches. More generally, this paper argues that the reformulation of eCRM problems within this new framework of analysis can result in more powerful analytical approaches.

Keywords: Data Mining; , Optimization; , eCRM Applications (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (21)

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