Customizing Promotions in Online Stores

Jie Zhang () and Lakshman Krishnamurthi ()
Additional contact information
Jie Zhang: Stephen M. Ross School of Business, University of Michigan, 701 Tappan Street, Ann Arbor, Michigan 48109-1234
Lakshman Krishnamurthi: Kellogg Graduate School of Management, Northwestern University, 2001 Sheridan Road, Evanston, Illinois 60208

Marketing Science, 2004, vol. 23, issue 4, 561-578

Abstract: The main objective of this paper is to provide a decision-support system of micro-level customized promotions, primarily for use in online stores. Our proposed approach utilizes the one-on-one and interactive nature of the Internet shopping environment and provides recommendations on . We address the issue by first constructing a joint purchase incidence-brand choice-purchase quantity model that incorporates how variety-seeking/inertia tendency differs among households and change over time for the same household. Based on the model, we develop an optimization procedure to derive the optimal amount of price discount for each household on each shopping trip. We demonstrate that the proposed customization method could greatly improve the effectiveness of current promotion practices, and discuss the implications for retailers and consumer packaged goods companies in the age of Internet technology.

Keywords: customized promotions; profit optimization; Internet marketing; decision support system; personalized marketing; econometric models; purchase incidence; brand choice; purchase quantity; variety-seeking; inertia (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (67)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.1040.0055 (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:23:y:2004:i:4:p:561-578

Access Statistics for this article

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