Decomposing the Sales Promotion Bump with Store Data

Harald J. van Heerde (), Peter S. H. Leeflang () and Dick R. Wittink ()
Additional contact information
Harald J. van Heerde: Faculty of Economics and Business Administration, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands
Peter S. H. Leeflang: Faculty of Economics, Department of Marketing and Marketing Research, University of Groningen, P.O. Box 800, 9700 AV, Groningen, The Netherlands
Dick R. Wittink: Yale School of Management, Yale University, P.O. Box 208200, New Haven, Connecticut 06520-8200, and Faculty of Economics, University of Groningen, Groningen, The Netherlands

Marketing Science, 2004, vol. 23, issue 3, 317-334

Abstract: Sales promotions generate substantial short-term sales increases. To determine whether the sales promotion bump is truly beneficial from a managerial perspective, we propose a system of store-level regression models that decomposes the sales promotion bump into three parts: cross-brand effects (secondary demand), cross-period effects (primary demand borrowed from other time periods), and category-expansion effects (remaining primary demand). Across four store-level scanner datasets, we find that each of these three parts contribute about one third on average. One extension we propose is the separation of the category-expansion effect into cross-store and market-expansion effects. Another one is to split the cross-item effect (total across all other items) into cannibalization and between-brand effects. We also allow for a flexible decomposition by allowing all effects to depend on the feature/display support condition and on the magnitude of the price discount. The latter dependence is achieved by local polynomial regression. We find that feature-supported price discounts are strongly associated with cross-period effects while display-only supported price discounts have especially strong category-expansion effects. While the role of the category-expansion effect tends to increase with higher price discounts, the roles of cross-brand and cross-period effects both tend to decrease.

Keywords: econometric models; market response models; sales promotion; regression and other statistical techniques (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (70)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:23:y:2004:i:3:p:317-334

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