Dynamic Catalog Mailing Policies

Duncan I. Simester (), Peng Sun () and John N. Tsitsiklis ()
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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

Management Science, 2006, vol. 52, issue 5, 683-696

Abstract: 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.

Keywords: dynamic optimization; catalog mailing; field test; Markov decision process (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (39)

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