Article ID: | iaor20073837 |
Country: | United States |
Volume: | 49 |
Issue: | 10 |
Start Page Number: | 1327 |
End Page Number: | 1343 |
Publication Date: | Oct 2003 |
Journal: | Management Science |
Authors: | Tuzhilin Alexander, Padmanabhan Balaji |
Keywords: | e-commerce |
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.