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Price customization and within-chain data do not mix!

Rakesh Niraj (Marketing and Policy Studies, Case Western Reserve University, Cleveland, Ohio, USA)
S. Siddarth (Marketing, Marshall School of Business, University of Southern California, Los Angeles, California, USA)

European Journal of Marketing

ISSN: 0309-0566

Article publication date: 4 February 2014

599

Abstract

Purpose

Grocery retailers have access to detailed data on consumer purchases within their own chains. Previous research has used across-chain scanner panel data to develop optimal price cuts targeted to individual households but whether such a targeting strategy will work with only within-chain data is unknown. The purpose of this research is to address this specific question.

Design/methodology/approach

The authors use scanner panel data from multiple categories to create across-chain and within-chain purchase histories for the same consumers. They then estimate models of purchase decisions on the two datasets and compare their performance.

Findings

Within-chain data fares significantly worse on both fit and prediction criteria. Retailers' upside to customizing is minimal compared to those reported for manufacturers. Finally, customized prices based on the within-chain model significantly underperform the promise of across-chain data.

Research limitations/implications

Store choice is not modelled. Research also needs to be replicated in other contexts. The authors conclude that limited purchase histories may not yield accurate enough estimates of marketing mix responsiveness, and that across-chain purchase histories are essential for effective targeted price cuts.

Practical implications

Loyalty card data may be useful for other purposes, like experimenting with segment-specific discounts, but its value in customizing prices at individual level is limited without adding other sources of information.

Originality/value

Previous research on price customization has been based almost exclusively on across-store data. However, retailers only have access to their own chain-specific data. This is the first study to comprehensively compare price customization based on within- and across-chain purchase data and show that the upside potential for price customization based on the former information set is quite limited.

Keywords

Acknowledgements

The authors are grateful to Information Resources, Inc. (IRI) and A. C. Nielsen for providing the data used in the study. They appreciate the comments and suggestions made by seminar participants at USC, UC-Irvine, University of Virginia, University of British Columbia, Texas Christian University, Arizona State University, Case Western Reserve University, University of Oklahoma, Supermarket Retailing Conference at SUNY-Buffalo, and the Return on Marketing Investment Conference at IIM-Ahmedabad. The authors thank Joffre Swait for helpful discussions during the course of this research and acknowledge the financial support provided by the Marshall School Summer Research fund. Information Resources, Inc. (IRI) has changed its name to SymphonyIRI Group, Inc. All estimates and analyses in this paper based on SymphonyIRI Group, Inc. data are by the author(s) and not by SymphonyIRI Group, Inc.

Citation

Niraj, R. and Siddarth, S. (2014), "Price customization and within-chain data do not mix!", European Journal of Marketing, Vol. 48 No. 1/2, pp. 360-379. https://doi.org/10.1108/EJM-01-2012-0032

Publisher

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Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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