Behavioral Research Using Scanner Data

Citation:

Amitava Chattopadhyay, Stephen J. Hoch, and Glen Mayhew (1994) ,"Behavioral Research Using Scanner Data", in NA - Advances in Consumer Research Volume 21, eds. Chris T. Allen and Deborah Roedder John, Provo, UT : Association for Consumer Research, Pages: 224.

Advances in Consumer Research Volume 21, 1994      Page 224

BEHAVIORAL RESEARCH USING SCANNER DATA

Amitava Chattopadhyay, McGill University

Stephen J. Hoch, University of Chicago

Glen Mayhew, Washington University

Scott A. Neslin, Dartmouth College

Emine Sarigollu, McGill University

Russell S. Winer, University of California-Berkeley

Behavioral research on consumer purchase/choice behavior has often relied on small samples, artificial settings, and measures of behavioral intent rather than actual behavior. Quantitative research on these topics have been criticized for not adequately incorporating behavioral constructs. The purpose of this session was to explore how scanner panel data provides a unique opportunity for consumer behavior researchers to examine a variety of questions in a context that, on the one hand, allows the use of actual field purchase data from a large sample and, on the other, enables the researcher to incorporate behavioral constructs of theoretical and practical importance.

The session consisted of three speakers followed by a discussant. The three speakers focused on very different topics. This is deliberate as our objective was to show the wide range of consumer behavior questions that can be addressed using scanner panel data. The discussant not only critiqued the research presented but built on this diverse range of topics and suggested broad directions for future research.

While the presentations dealt with widely divergent topics, it was clear from the presentations that research based on scanner panel data can contribute to consumer research in three ways: (1) focus on actual behavior rather than surrogate measures such as behavioral intent, (2) enhance external validity and (3) change the conversation.

Though each of the papers presented in the session contribute in all three ways, each paper contributes most strongly on a subset of the three dimensions. Hoch discusses a three-year project focusing on real-time, in-store pricing experiments. His discussion of six experiments that examine consumer's purchase behavior in response to several types of promotions as a function of the consumer characteristics of a store's trading area contribute towards enhancing the external validity of consumer promotion research on the one hand and, on the other, changing the conversation in research on consumer promotions.

The work of Mayhew and Winer focuses on the use of scanner panel data to determine how much consumers are willing to pay for an innovation in the category of frequently purchased nondurables. Their method provides an alternative to survey based methods currently used as inputs to pricing decisions. Thus this paper contributes most significantly in changing the conversation in the domain of research on pricing decisions.

Chattopadhyay, Sarigollu and Gorn focus on the relationship between advertising and sales. Their work extends traditional research in this area which models the link between ad exposure and sales with no regard for the nature of the advertising, by introducing characteristics of the ad in terms of both the mechanical aspects of the ad (e.g., did it involve a direct comparison) as well as consumers' evaluations of the ad (e.g., how persuasive was it considered). Their presentation described some initial findings from a programme of research designed to examine the relationship between the characteristics of advertisements and sales as a function of a variety of market and customer considerations. Thus this research contributes most significantly to a better understanding of advertising effects by focusing on behavior.

To summarize, the presentations provided some insights not only on specific issues in consumer behavior but, more importantly, showed the potential for using scanner data in examining diverse aspects of consumer behavior and contributing to traditional consumer research by enhancing external validity, focusing on behavior, and changing the conversation in specific research domains.

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