Promotion Optimization in Retail

26 Pages Posted: 6 Aug 2018 Last revised: 24 Apr 2020

See all articles by Maxime C. Cohen

Maxime C. Cohen

Desautels Faculty of Management, McGill University

Georgia Perakis

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: May 1, 2018

Abstract

This chapter presents some recent developments in retail promotions. We first discuss the different types of promotion used in retail, and then survey the related literature. We next formulate the promotion optimization problem for multiple items. This formulation is directly motivated from practice, holds for general demand models, and can incorporate the relevant business rules. We discuss how this formulation captures important economic factors in the context of retail. We then present an efficient approximate solution approach by using a discrete linearization method that allows the retailer to solve large-scale instances within seconds. We next report a beginning-to-end application of the entire process of optimizing retail promotions. We divide the process in five steps that the retailer needs to follow; from collecting and aggregating the data to computing future promotion decisions. Finally, we discuss the potential impact of using data analytics and optimization for retail promotions. We convey that in our tested examples (calibrated with real data), using the promotions suggested by our model can yield a 2-9% profit improvement.

Keywords: Retail promotions, Pricing, Optimization

Suggested Citation

Cohen, Maxime C. and Perakis, Georgia, Promotion Optimization in Retail (May 1, 2018). Available at SSRN: https://ssrn.com/abstract=3194640 or http://dx.doi.org/10.2139/ssrn.3194640

Maxime C. Cohen (Contact Author)

Desautels Faculty of Management, McGill University ( email )

1001 Sherbrooke St. W
Montreal, Quebec H3A 1G5
Canada

Georgia Perakis

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-565
Cambridge, MA 02142
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
1,314
Abstract Views
4,199
Rank
28,398
PlumX Metrics