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This paper describes a new data set available to academic researchers (at the following website: http://mktsci.pubs.informs.org). These data are comprised of store sales and consumer panel data for 30 product categories. The store sales data contain 5 years of product sales, pricing, and promotion data for all items sold in 47 U.S. markets. In two U.S. markets, the store level data are supplemented with panel-level purchase data and cover the entire population of stores. Further information is available regarding store characteristics in these markets. We address several potential applications of these data, as well as the access protocol.
Key words : price; promotion; product; distribution; sales
History: Received: June 6, 2007; accepted: June 9, 2008; processed by John Hauser.
Introduction
This document outlines a broad, new consumer packaged goods data set available for distribution to academics in 2008. These data are intended to enable academic researchers to study important research topics in marketing and economics that are of concern to practitioners, policy makers, and scholars. In the following paper we detail the broad class of studies the data set was intended to facilitate, the structure of the data, and the process for disseminating data and topics to the academic community. More specific information on the variables and data can be found in the Technical Appendix at http://mktsci.pubs.informs.org.
Research Issues
IRI convened an assembly of industry practitioners from leading retailers and manufacturers and a number of academics to overview issues of potential interest that would guide the construction of these data. The result of this process was a list of relevant domains of interest to IRI, its clients, and academics. Table 1 overviews the research domains raised by these participants during the construction of the marketing data set.
One dimension in which these issues are categorized in Table 1 is by retailer/manufacturer. It is worth noting that Ataman et al. (2007) find that there is considerable variation in market shares over regions that can be ascribed to retailer behavior, and they call for more work in this area. By conglomerating data that span a plenitude of product categories across multiple retailers and regions, researchers will be able to explore the factors underlying variation in retailer shares over time and space. Prior data sets, because they...