Constrained optimization of data-mining problems to improve model performance: A direct-marketing application

Expert Systems with Applications

Volumn 29, Issue 3, 2005, Pages 630-640

  Prinzie, Anita ^a   Van Den Poel, Dirk ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Constrained optimization; Customer relationship management; Data mining; Direct marketing; Targeting

Indexed keywords

CONSTRAINT THEORY; COSTS; INDUSTRIAL RELATIONS; INVESTMENTS; MARKETING; MATHEMATICAL MODELS; OPTIMIZATION; PERFORMANCE;

CUSTOMER RELATIONSHIP MANAGEMENT; DATA-MINING (DM) MODELS; MODEL PERFORMANCE; TRADITIONAL RESPONSE MODELS;

DATA MINING;

EID: 24144449551     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2005.04.022     Document Type: Article

References (38)

1. B. Baesens, T. Van Gestel, S. Viaene, M. Stepanova, J. Suykens, and J. Vanthienen Benchmarking state-of-the art classification algorithms for credit scoring Journal of the Operational Research Society 54 6 2003 627 635
2. B. Baesens, G. Verstraeten, D. Van den Poel, M. Egmont-Peterson, P. Van Kenhove, and J. Vanthienen Bayesian network classifiers for identifying the slope of the customer - lifecyle of long-life customers European Journal of Operational Research 156 2 2004 508 523
3. P.D. Berger, and T. Magliozzi Optimal co-operative advertising decisions in direct-mail operations The Journal of Operational Research Society 43 11 1992 1079 1086
4. S. Bhattacharyya Direct marketing performance modeling using genetic algorithms Journal on Computing 11 3 1999 248 257
5. G. Bitran, and S.V. Mondschein Mailing decisions in the catalog sales industry Management Science 42 9 1996 1364 1381
6. A. Bodapati, and S. Gupta A direct approach to predicting discretized response in target marketing Journal of Marketing Research 41 1 2004 73 85
7. L. Breiman Bagging predictors Machine Learning 24 2 1996 123 140
8. W. Buckinx, E. Moons, D. Van den Poel, and G. Wets Customer-adapted coupon targeting using feature selection Expert Systems with Applications 26 4 2004 509 518
9. W. Buckinx, and D. Van den Poel Customer base analysis: Partial defection of behaviorally-loyal clients in a non-contractual fmcg retail setting European Journal of Operational Research 164 1 2005 252 268
10. J.R. Bult Semiparametric versus parametric classification models: An application to direct marketing Journal of Marketing Research 30 3 1993 380 390
11. J.R. Bult, H. van der Scheer, and T. Wansbeek Interaction between target and mailing characteristics in direct marketing, with an application to health care fund raising International Journal of Research in Marketing. 14 4 1997 301 308
12. J.R. Bult, and T. Wansbeek Optimal selection for direct mail Marketing Science 14 4 1995 378 394
13. J.R. Bult, and D.R. Wittink Estimating and validating asymmetric heterogeneous loss functions applied to health care fund raising International Journal of Research in Marketing 13 1996 215 226
14. Cullinan, G. J. (1977). Picking them by their batting averages' recency-frequency-monetary method of controlling circulation. N.Y.: Manual Release 2103, Direct Mail/Marketing Association.
15. B. Efron, and R. Tibshirani An introduction to the bootstrap 1993 Chapman & Hall NY
16. R. Elsner, M. Krafft, and A. Huchzermeier Optimizing Rhenania's mail-order business through dynamic multilevel modeling (DMLM) Interfaces 33 1 2003 50 66
17. F. Gönül, and M.Z. Shi Optimal mailing of catalogs: A new methodology using estimable structural dynamic programming models Management Science 44 9 1998 1249 1262
18. F. Gönül, and Srinivisan Estimating the impact of consumer expectations of coupons on purchase behavior: A dynamic structural model Marketing Science 15 3 1996 262 279
19. C.M. Heilman, F. Kaefer, and S.D. Ramenofsky Determining the appropriate amount of data for classifying customers for direct marketing purposes Journal of Interactive Marketing 17 3 2003 5 28
20. J.J. Jonker, N. Piersma, and D. Van den Poel Joint optimization of customer segmentation and marketing policy to maximize long-term profitability Expert Systems with Applications 27 2 2004 159 168
21. Kaslow, G. A. (1997). A microeconomic analysis of consumer response to direct marketing and mail order. PhD. Dissertation, California Institute of Technology.
22. Y.S. Kim, and W.N. Street An intelligent system for customer targeting: A data mining approach Decision Support Systems 37 2 2004 215 228
23. N. Levin, and J. Zahavi Continuous predictive modeling: A comparative analysis Journal of Interactive Marketing 12 2 1998 5 22
24. Magliozzi, Th. L. (1989). An empirical investigation of regression analysis meta-strategies for direct marketing list segmentation models. PhD. Dissertation, Boston University.
25. V.G. Morwitz, and D.C. Schmittlein Testing new direct marketing offerings: The interplay of management judgment and statistical models Management Science 44 5 1998 610 628
26. E.L. Nash The direct marketing handbook 1992 McGraw-Hill New York
27. N. Piersma, and J.J. Jonker Determining the optimal direct mailing frequency European Journal of Operational Research 158 1 2004 173 182
28. M.L. Roberts, and P.D. Berger Direct marketing management 1989 Prentice-Hall Englewood Cliffs, NJ (p. 7)
29. P.E. Rossi, R.E. McCulloch, and G.M. Allenby The value of purchase history data in target marketing Marketing Science 15 4 1996
30. G.E. Smith, and P.D. Berger The impact of direct marketing appeals on charitable marketing effectiveness Journal of the Academy of Marketing Science 24 3 1996 219 231
31. E.H. Suh, K.C. Noh, and C.K. Suh Customer list segmentation using the combined response model Expert Systems with Applications 17 2 1999 89 97
32. D. Van den Poel Predicting mail-order repeat buying: Which variables matter? Tijdschrift voor Economie en Management 48 3 2003 371 403
33. D. Van den Poel, and J. Leunis Database marketing modeling for financial services using hazard rate models The International Review of Retail, Distribution and Consumer Research 8 2 1998 243 257
34. T. Van Gestel, J.A.K. Suykens, B. Baesens, S. Viaene, J. Vanthienen, and G. Dedene Benchmarkig least squares support vector machine classifiers Machine Learning 54 1 2004 5 32
35. S. Viaene, B. Baesens, T. Van Gestel, J.A.K. Suykens, D. Van den Poel, and J. Vanthienen Knowledge discovery in a direct marketing case using least squares support vector machines International Journal of Intelligent Systems 16 9 2001 1023 1036
36. J. Zahavi, and N. Levin Issues and problems in applying neural computing to target marketing Journal of Direct Marketing 9 3 1995 33 44
37. J. Zahavi, and N. Levin Applying neural computing to target marketing Journal of Direct Marketing 11 1 1997 5 21
38. Y. Zhang, and S. Bhattacharrya Genetic programming in classifying large-scale data: An ensemble method Information Sciences 163 1-3 2004 85 101