Recovering Sku-Level Preferences and Response Sensitivities from Market Share Models Estimated on Item Aggregates

41 Pages Posted: 22 Aug 2004

See all articles by David R. Bell

David R. Bell

University of Pennsylvania - Marketing Department

Andre Bonfrer

Deakin University; Australian National University (ANU)

Pradeep K. Chintagunta

University of Chicago

Date Written: June 17, 2004

Abstract

We propose an alternative approach to obtaining SKU-level preferences and response sensitivities. An attribute-level model in which the unit of analysis is the market share for an alternative created by aggregation e.g., Colgate toothpaste) is distinguished from a truly disaggregate SKU-level model and develop an analytical relationship between parameters obtained from these two models is established. We show that the researcher can recover SKU-level parameters via calculation from estimated attribute-level parameters, circumventing the need for direct estimation of the more complex true SKU-level model.

Our market share model is calibrated using 98 weeks of data for 10 brands and 168 SKUs in the toothpaste category. We show that instead of estimating 168 preference parameters (when we have an outside alternative in addition to the 168 inside ones), one need only estimate 10 brand preference parameters from which the 168 parameters can be computed as long as share and marketing mix data are available at the SKU level. Marketing mix response parameters can be recovered in a similar fashion. Estimation on holdout samples demonstrates superior predictive performance compared with other available methods. Implications for the derivation of SKU-level elasticities and forecasts of market share and response sensitivity for new items introduced to the category are discussed.

Keywords: Discrete Choice, Market Share Models, Marketing Mix, Product Attributes, SKU

Suggested Citation

Bell, David R. and Bonfrer, Andre and Chintagunta, Pradeep K., Recovering Sku-Level Preferences and Response Sensitivities from Market Share Models Estimated on Item Aggregates (June 17, 2004). Available at SSRN: https://ssrn.com/abstract=579562 or http://dx.doi.org/10.2139/ssrn.579562

David R. Bell (Contact Author)

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

Andre Bonfrer

Deakin University ( email )

Australia

Australian National University (ANU) ( email )

Canberra, Australian Capital Territory 2601
Australia

Pradeep K. Chintagunta

University of Chicago ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States
773-702-8015 (Phone)
773-702-0458 (Fax)

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