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Dynamic Catalog Mailing Policies


  • Duncan I. Simester

    () (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Peng Sun

    () (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • John N. Tsitsiklis

    () (Laboratory for Information and Decision Systems and Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)


Deciding who should receive a mail-order catalog is among the most important decisions that mail-order-catalog firms must address. In practice, the current approach to the problem is invariably myopic: firms send catalogs to customers who they think are most likely to order from that catalog. In doing so, the firms overlook the long-run implications of these decisions. For example, it may be profitable to mail to customers who are unlikely to order immediately if sending the current catalog increases the probability of a future order. We propose a model that allows firms to optimize mailing decisions by addressing the dynamic implications of their decisions. The model is conceptually simple and straightforward to implement. We apply the model to a large sample of historical data provided by a catalog firm and then evaluate its performance in a large-scale field test. The findings offer support for the proposed model but also identify opportunities for further improvement.

Suggested Citation

  • Duncan I. Simester & Peng Sun & John N. Tsitsiklis, 2006. "Dynamic Catalog Mailing Policies," Management Science, INFORMS, vol. 52(5), pages 683-696, May.
  • Handle: RePEc:inm:ormnsc:v:52:y:2006:i:5:p:683-696

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    References listed on IDEAS

    1. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    2. Gabriel R. Bitran & Susana V. Mondschein, 1996. "Mailing Decisions in the Catalog Sales Industry," Management Science, INFORMS, vol. 42(9), pages 1364-1381, September.
    3. Ronald A. Howard, 2002. "Comments on the Origin and Application of Markov Decision Processes," Operations Research, INFORMS, vol. 50(1), pages 100-102, February.
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    Cited by:

    1. Giuliano Tirenni & Abderrahim Labbi & Cesar Berrospi & André Elisseeff & Timir Bhose & Kari Pauro & Seppo Pöyhönen, 2007. "—Customer Equity and Lifetime Management (CELM) Finnair Case Study," Marketing Science, INFORMS, vol. 26(4), pages 553-565, 07-08.
    2. Ricardo Montoya & Oded Netzer & Kamel Jedidi, 2010. "Dynamic Allocation of Pharmaceutical Detailing and Sampling for Long-Term Profitability," Marketing Science, INFORMS, vol. 29(5), pages 909-924, 09-10.
    3. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean, 2011. "Adaptive Experimental Design Using the Propensity Score," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 96-108.
    4. Eric T. Anderson & Gavan J. Fitzsimons & Duncan Simester, 2006. "Measuring and Mitigating the Costs of Stockouts," Management Science, INFORMS, vol. 52(11), pages 1751-1763, November.
    5. Oliver J. Rutz & Michael Trusov & Randolph E. Bucklin, 2011. "Modeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?," Marketing Science, INFORMS, vol. 30(4), pages 646-665, July.
    6. repec:eee:joinma:v:23:y:2009:i:2:p:157-168 is not listed on IDEAS
    7. repec:eee:joinma:v:28:y:2014:i:4:p:271-284 is not listed on IDEAS
    8. 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.
    9. repec:eee:jouret:v:89:y:2013:i:3:p:263-280 is not listed on IDEAS
    10. Klein, Robert & Kolb, Johannes, 2015. "Maximizing customer equity subject to capacity constraints," Omega, Elsevier, vol. 55(C), pages 111-125.
    11. Damgaard, Mette Trier & Gravert, Christina, 2018. "The hidden costs of nudging: Experimental evidence from reminders in fundraising," Journal of Public Economics, Elsevier, vol. 157(C), pages 15-26.
    12. 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.
    13. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    14. Romana Khan & Michael Lewis & Vishal Singh, 2009. "Dynamic Customer Management and the Value of One-to-One Marketing," Marketing Science, INFORMS, vol. 28(6), pages 1063-1079, 11-12.
    15. Jonathan Z. Zhang & Oded Netzer & Asim Ansari, 2014. "Dynamic Targeted Pricing in B2B Relationships," Marketing Science, INFORMS, vol. 33(3), pages 317-337, May.
    16. repec:eee:jouret:v:89:y:2013:i:4:p:374-396 is not listed on IDEAS
    17. Shie Mannor & Duncan Simester & Peng Sun & John N. Tsitsiklis, 2007. "Bias and Variance Approximation in Value Function Estimates," Management Science, INFORMS, vol. 53(2), pages 308-322, February.
    18. Scott A. Neslin & Thomas P. Novak & Kenneth R. Baker & Donna L. Hoffman, 2009. "An Optimal Contact Model for Maximizing Online Panel Response Rates," Management Science, INFORMS, vol. 55(5), pages 727-737, May.
    19. Dimitris Bertsimas & Adam J. Mersereau, 2007. "A Learning Approach for Interactive Marketing to a Customer Segment," Operations Research, INFORMS, vol. 55(6), pages 1120-1135, December.
    20. repec:eee:joinma:v:27:y:2013:i:3:p:172-184 is not listed on IDEAS
    21. repec:eee:joinma:v:24:y:2010:i:2:p:121-137 is not listed on IDEAS
    22. Daniel Adelman & Adam J. Mersereau, 2013. "Dynamic Capacity Allocation to Customers Who Remember Past Service," Management Science, INFORMS, vol. 59(3), pages 592-612, January.


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