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Optimal selection of households for direct marketing by joint modeling of the probability and quantity of response

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  • Otter, Pieter W.
  • Scheer, Hiek van der
  • Wansbeek, Tom

    (Groningen University)

Abstract

We present several methods for the maximization of expected profits when households are selected from a mailing list for a direct mail campaign. The response elicited from the campaign can vary over households, as is the case with fund raising or mail order selling. The decisions taken by the household are (a) whether to respond and, in the case of response, (b) the quantity of response, e.g. the sum donated or the monetary amount of the order. We jointly model both decisions and derive a number of profit maximizing selection methods. We empirically illustrate the methods using a data set from a charitable foundation. It appears that modeling both aspects of the response yields considerably higher profits relative to selection methods that are based on solely modeling the response probability.

Suggested Citation

  • Otter, Pieter W. & Scheer, Hiek van der & Wansbeek, Tom, 2006. "Optimal selection of households for direct marketing by joint modeling of the probability and quantity of response," CCSO Working Papers 200606, University of Groningen, CCSO Centre for Economic Research.
  • Handle: RePEc:gro:rugccs:200606
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    File URL: http://irs.ub.rug.nl/ppn/297681680
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    References listed on IDEAS

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    1. Manning, W. G. & Duan, N. & Rogers, W. H., 1987. "Monte Carlo evidence on the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 35(1), pages 59-82, May.
    2. Hay, Joel W & Leu, Robert & Rohrer, Paul, 1987. "Ordinary Least Squares and Sample-Selection Models of Health-Care Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 499-506, October.
    3. Arabmazar, Abbas & Schmidt, Peter, 1982. "An Investigation of the Robustness of the Tobit Estimator to Non-Normality," Econometrica, Econometric Society, vol. 50(4), pages 1055-1063, July.
    4. Hsiao, Cheng & Kim, Changseob & Taylor, Grant, 1990. "A statistical perspective on insurance rate-making," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 5-24.
    5. Hartman, Raymond S, 1991. "A Monte Carlo Analysis of Alternative Estimators in Models Involving Selectivity," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 41-49, January.
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