Tackling the Retailer Decision Maze: Which Brands to Discount, How Much, When and Why?

Gerard J. Tellis and Fred S. Zufryden
Additional contact information
Gerard J. Tellis: University of Southern California
Fred S. Zufryden: University of Southern California

Marketing Science, 1995, vol. 14, issue 3, 271-299

Abstract: We propose a model that seeks the optimal timing and depth of retail discounts with the optimal timing and quantity of the retailer's order over multiple brands and time periods. The model is based on an integration of consumer decisions in purchase incidence, brand choice and quantity with the dynamics of household and retail inventory. The major contribution of the model is that it shows how the optimum depth and timing of discount varies with key demand characteristics such as consumer stockpiling, loyalty, response to the marketing mix, and segmentation. In addition, the optima also vary with key supply characteristics such as retail margins, depth and frequency of manufacturer deals, retail inventory, and retagging costs. The most valuable contribution of the model is that it can provide an optimal discount strategy for multiple brands over multiple time periods. The optimization model runs on a user-friendly personal computer program. An application based on UPC scanner data illustrates the model's uses. Sensitivity analyses of the optimization model under alternative scenarios reveal novel insights as to how optimal discounts vary as a function of the key demand and supply characteristics.

Keywords: optimal promotions; retailing; consumer response; discount timing; mathematical programming (search for similar items in EconPapers)
Date: 1995
References: Add references at CitEc
Citations: View citations in EconPapers (42)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.14.3.271 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:14:y:1995:i:3:p:271-299

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().