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

Author

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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)

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.

Suggested Citation

  • Balaji Padmanabhan & Alexander Tuzhilin, 2003. "On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities," Management Science, INFORMS, vol. 49(10), pages 1327-1343, October.
    • Handle: RePEc:inm:ormnsc:v:49:y:2003:i:10:p:1327-1343
    DOI: 10.1287/mnsc.49.10.1327.17310
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    References listed on IDEAS

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