Bayesian Applications in Marketing

70 Pages Posted: 10 Mar 2009 Last revised: 19 May 2010

See all articles by Greg M. Allenby

Greg M. Allenby

Ohio State University (OSU) - Department of Marketing and Logistics

Peter E. Rossi

University of California, Los Angeles (UCLA) - Anderson School of Management

Date Written: March 9, 2009

Abstract

We review applications of Bayesian methods to marketing problems. Key aspects of marketing applications include the discreteness of response or outcome data and relatively large numbers of cross-sectional units, each with possibly low information content. The use of informative priors including hierarchical models is essential for successful Bayesian applications in marketing. Given the importance of the prior, it is important to assure flexibility in the prior specification. Non-standard likelihoods and flexible priors make marketing a very challenging area for Bayesian applications.

Keywords: bayesian inference, marketing, econometrics

JEL Classification: C5, D1, M3

Suggested Citation

Allenby, Greg M. and Rossi, Peter E., Bayesian Applications in Marketing (March 9, 2009). Chicago Booth Research Paper No. 09-15. Available at SSRN: https://ssrn.com/abstract=1356062 or http://dx.doi.org/10.2139/ssrn.1356062

Greg M. Allenby

Ohio State University (OSU) - Department of Marketing and Logistics ( email )

Fisher Hall 524
2100 Neil Ave
Columbus, OH 43210
United States

Peter E. Rossi (Contact Author)

University of California, Los Angeles (UCLA) - Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States
773-294-8616 (Phone)

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