Article ID: | iaor20081223 |
Country: | United States |
Volume: | 52 |
Issue: | 5 |
Start Page Number: | 683 |
End Page Number: | 696 |
Publication Date: | May 2006 |
Journal: | Management Science |
Authors: | Tsitsiklis John N., Simester Duncan I., Sun Peng |
Keywords: | distribution, advertising |
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.