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Optimal Mailing of Catalogs: A New Methodology Using Estimable Structural Dynamic Programming Models

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Author Info

  • Füsun Gönül

    (Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890)

  • Meng Ze Shi

    (Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890)

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    Abstract

    We investigate the key determinants of the optimal direct mail policy in a dynamic environment where customers maximize utility and the direct mailer maximizes profits. We measure the sensitivity of the customers to receiving a catalog in the mail, while controlling for customer characteristics such as elapsed time in responses and number of purchases. We apply our model to a database from a national cataloger that markets nonseasonal products. We summarize the results of our model that are valid for these types of products. We find that the dynamic model significantly outperforms its single-period counterpart. We find that it is not optimal to mail to individuals at low recency levels because they are likely to buy anyway. It is better to save the mailing dollars for customers at higher recency levels. We find that it is optimal to mail to customers who have purchased only a small or a medium number of times to induce them to continue to buy from this catalog and not switch to others. It is not necessary to mail often to customers who have purchased many times before from the company unless they have high recency values. We find that under the optimal mailing policy the cataloguer enjoys higher profits than under the current mailing policy.

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    File URL: http://dx.doi.org/10.1287/mnsc.44.9.1249
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 44 (1998)
    Issue (Month): 9 (September)
    Pages: 1249-1262

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    Handle: RePEc:inm:ormnsc:v:44:y:1998:i:9:p:1249-1262

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    Web page: http://www.informs.org/
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    Related research

    Keywords: Structural Models; Principle of Optimality; Catalogs; Mailing Policy;

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    Citations

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    Cited by:
    1. Baumgartner, Bernhard & Hruschka, Harald, 2005. "Allocation of catalogs to collective customers based on semiparametric response models," European Journal of Operational Research, Elsevier, vol. 162(3), pages 839-849, May.
    2. Gonul, Fusun F., 1998. "Estimating price expectations in the OTC medicine market: An application of dynamic stochastic discrete choice models to scanner panel data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 41-56, November.
    3. Sander Triest & Maurice Bun & Erik Raaij & Maarten Vernooij, 2009. "The impact of customer-specific marketing expenses on customer retention and customer profitability," Marketing Letters, Springer, vol. 20(2), pages 125-138, June.
    4. Mercedes Esteban Bravo & José M. Vidal-Sanz & Gökhan Yildirim, 2012. "Valuing customer portfolios with endogenous mass-and-direct-marketing interventions using a stochastic dynamic programming decomposition," Business Economics Working Papers wb121304, Universidad Carlos III, Departamento de Economía de la Empresa.
    5. Wagner Kamakura & Carl Mela & Asim Ansari & Anand Bodapati & Pete Fader & Raghuram Iyengar & Prasad Naik & Scott Neslin & Baohong Sun & Peter Verhoef & Michel Wedel & Ron Wilcox, 2005. "Choice Models and Customer Relationship Management," Marketing Letters, Springer, vol. 16(3), pages 279-291, December.
    6. Bart Bronnenberg & Jean Dubé & Carl Mela & Paulo Albuquerque & Tulin Erdem & Brett Gordon & Dominique Hanssens & Guenter Hitsch & Han Hong & Baohong Sun, 2008. "Measuring long-run marketing effects and their implications for long-run marketing decisions," Marketing Letters, Springer, vol. 19(3), pages 367-382, December.
    7. 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.
    8. Jonker, J-J. & Piersma, N. & Potharst, R., 2002. "Direct Mailing Decisions for a Dutch Fundraiser," ERIM Report Series Research in Management ERS-2002-111-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
    9. Durango-Cohen, Elizabeth J., 2013. "Modeling contribution behavior in fundraising: Segmentation analysis for a public broadcasting station," European Journal of Operational Research, Elsevier, vol. 227(3), pages 538-551.
    10. Bose, Indranil & Chen, Xi, 2009. "Quantitative models for direct marketing: A review from systems perspective," European Journal of Operational Research, Elsevier, vol. 195(1), pages 1-16, May.
    11. W.R Buckinx & D. Van Den Poel, 2003. "Predicting Online Purchasing Behavior," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/195, Ghent University, Faculty of Economics and Business Administration.
    12. Jonker, J-J. & Piersma, N. & Potharst, R., 2002. "Direct Mailing Decisions for a Dutch Fundraiser," Econometric Institute Research Papers ERS-2002-111-LIS, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Naik, P. & Piersma, N., 2002. "Understanding the role of marketing communications in direct marketing," Econometric Institute Research Papers EI 2002-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. 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.
    15. J.-J. Jonker & N. Piersma & D. Van Den Poel, 2003. "Joint Optimization of Customer Segmentation and Marketing Policy to Maximize Long-Term Profitability," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 03/214, Ghent University, Faculty of Economics and Business Administration.

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