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Customer-Adapted Coupon Targeting Using Feature Selection

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Author Info
W. BUCKINX
E. MOONS
D. VAN DEN POEL ()
G. WETS

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Abstract

The management of coupon promotions is an important issue for marketing managers since it still is the major promotion medium. However, the distribution of coupons does not go without problems. Although manufacturers and retailers are investing heavily in the attempt to convince as many customers as possible, overall coupon redemption rate is low. This study improves the strategy of retailers and manufacturers concerning their target selection since both parties often end up in a battle for customers. Two separate models are built: one model makes predictions concerning redemption behavior of coupons that are distributed by the retailer while another model does the same for coupons handed out by manufacturers. By means of the feature-selection technique ‘Relief-F’ the dimensionality of the models is reduced, since it searches for the variables that are relevant for predicting the outcome. In this way, redundant variables are not used in the model-building process. The model is evaluated on real-life data provided by a retailer in FMCG. The contributions of this study for retailers as well as manufacturers are threefold. First, the possibility to classify customers concerning their coupon usage is shown. In addition, it is demonstrated that retailers and manufacturers can stay clear of each other in their marketing campaigns. Finally, the feature-selection technique ‘Relief-F’ proves to facilitate and optimize the performance of the models.

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File URL: http://www.FEB.UGent.be/nl/Ondz/wp/Papers/wp_03_201.pdf
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Publisher Info
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 03/201.

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Length: 37 pages
Date of creation: Nov 2003
Date of revision:
Handle: RePEc:rug:rugwps:03/201

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Related research
Keywords: Data mining; Classification; Feature selection; Retailing;

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This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. W. Buckinx & D. Van Den Poel, 2003. "Customer Base Analysis: Partial Defection of Behaviorally-Loyal Clients in a Non-Contractual FMCG Retail Setting," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/178, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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  2. Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April. [Downloadable!] (restricted)
  3. D. Van Den Poel, 2003. "Predicting Mail-Order Repeat Buying: Which Variables Matter?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/191, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. A. Prinzie & D. Van Den Poel, 2005. "Constrained optimization of data-mining problems to improve model performance: A direct-marketing application," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/298, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
  2. A. Prinzie & D. Van Den Poel, 2005. "Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/292, Ghent University, Faculty of Economics and Business Administration. [Downloadable!]
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