Dynamic catalog mailing policies
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. © 2006 INFORMS.
Duke Scholars
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Operations Research
- 46 Information and computing sciences
- 38 Economics
- 35 Commerce, management, tourism and services
- 15 Commerce, Management, Tourism and Services
- 08 Information and Computing Sciences
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Operations Research
- 46 Information and computing sciences
- 38 Economics
- 35 Commerce, management, tourism and services
- 15 Commerce, Management, Tourism and Services
- 08 Information and Computing Sciences