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

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Although most data mining (DM) models are complex and general in nature, the implementation of such models in specific environments us often subject to practical constraints (e.g. budget constraints) or thresholds (e.g. only mail to customers with an expected profit higher than the investment cost). Typically, the DM model is calibrated neglecting those constraints/thresholds. If the implementation constraints/thresholds are known in advance, this indirect approach delivers a sub-optimal model performance. Adopting a direct approach, i.e. estimating a DM model in knowledge of the constraints/thresholds, improves model performance as the model is optimized for the given implementation environment. We illustrate the relevance of this constrained optimization of DM models on a direct-marketing case, i.e., in the field of customer relationship management. We optimize an individual-level response model for specific mailing-depths (i.e. the percentage of customers of the house list that actually receives a mail given the mailing budget constraint) and compare its predictive performance with that of a traditional response model neglecting the mailing depth during estimation. The results are in favor of the constrained-optimization approach.

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Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 05/298.

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Length: 36 pages
Date of creation: Mar 2005
Handle: RePEc:rug:rugwps:05/298
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  1. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
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  7. Jan Roelf Bult & Tom Wansbeek, 1995. "Optimal Selection for Direct Mail," Marketing Science, INFORMS, vol. 14(4), pages 378-394.
  8. W. Buckinx & E. Moons & D. Van Den Poel & G. Wets, 2003. "Customer-Adapted Coupon Targeting Using Feature Selection," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/201, Ghent University, Faculty of Economics and Business Administration.
  9. Piersma, Nanda & Jonker, Jedid-Jah, 2004. "Determining the optimal direct mailing frequency," European Journal of Operational Research, Elsevier, vol. 158(1), pages 173-182, October.
  10. Jonker, J-J. & Piersma, N. & Van den Poel, D., 2002. "Joint optimization of customer segmentation and marketing policy to maximize long-term profitability," Econometric Institute Research Papers EI 2002-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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  1. Mercadotecnia de bases de datos in Wikipedia Spanish ne '')
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