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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)

Registered author(s):

    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.

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    File URL: http://dx.doi.org/10.1287/mnsc.1050.0504
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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 52 (2006)
    Issue (Month): 5 (May)
    Pages: 683-696

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    Handle: RePEc:inm:ormnsc:v:52:y:2006:i:5:p:683-696
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