Executive Summary
Entering consumers’ consideration set is one of the top priorities in marketing strategy, and the implementation of such strategies is contingent on knowledge of individual consumers’ consideration sets. Such knowledge has been obtained by either asking respondents to state their considered set of brands or inferring those sets from their revealed choices. The authors propose, operationalize, and estimate a new model to capture unobserved consideration from discrete choice data. This model accommodates different sets of marketing-mix variables and heterogeneity in both consideration and choice stages, is computationally feasible for large numbers of alternatives, and bridges the stated and revealed approaches, enabling the analysis of either one or both sources of data to infer sets of brands considered for purchase.
An important goal of this study is to establish the validity of the existing practice to infer consideration sets from observed choices in panel data. The authors show with experimental data that underlying consideration sets can be reliably retrieved from choice data alone. Their model does so better than methods previously documented in the literature. The authors also show that consideration is positively affected by display and shelf space. The analysis is the first to provide support for the convergence of the stated and revealed consideration approaches.
The authors then apply the model to Information Resources Inc. panel data. The findings suggest that promotion effects are larger when they are included in the consideration stage of the two-stage model than in a single-stage model. The authors also find that consideration covaries across brands and that this covariation is mainly driven by unobserved consumer heterogeneity. Using a simulation experiment, the authors also show the implications of the model for price cut and featuring planning relative to a more standard model of choice. The results show that their model gives markedly different results from the single-stage model. Notably, when the authors use the optimum that results from the single-stage model in a world in which two stages is the reality, profits are relatively low. This shows that using a two-stage model is crucial for improving the effectiveness of such marketing decisions.
Biography
Erjen van Nierop is Assistant Professor of Marketing in the Department of Marketing, Faculty of Economics and Business, at the University of Groningen. He has an MSc and PhD in Econometrics from Erasmus University Rotterdam. He worked for two years as a visiting assistant professor in the Tepper School of Business at Carnegie Mellon University in Pittsburgh. He has taught courses on pricing, marketing research, and marketing model building. His research interests are marketing research and econometric modeling of marketing phenomena in general and choice, sales, and product diffusion models in particular.
Bart Bronnenberg is Professor of Marketing and CentER fellow in the School of Business and Economics at Tilburg University, the Netherlands. He holds a PhD and MSc in Management from INSEAD and an MS. in Industrial Engineering from Twente University (the Netherlands). At Tilburg University, Professor Bronnenberg teaches Masters and MPhil courses on Market Assessment and Statistics. In 2003, he received the Citibank Award for the most outstanding MBA teacher at University of California, Los Angeles. Bart Bronnenberg has completed consulting assignments for various consumer goods firms and corporations in the medical field. Professor Bronnenberg does research in marketing strategy, geographic organizations of markets, and local branding. He continues to work on empirical analyses of new product growth and consumer choice behavior. His articles have appeared in Journal of Marketing Research, Marketing Science, Marketing Letters, Journal of the Academy of Marketing Science, and other journals. Professor Bronnenberg was named the recipient of the 2003 and 2008 Paul Green Award, the 2003 International Journal of Research in Marketing Best Paper Award, and the 2004 John D.C. Little Best Paper Award.
Richard Paap is Professor of Econometrics and Marketing in the Econometric Institute at Erasmus University Rotterdam. His research topics include discrete choice modeling, duration analysis, Bayesian econometrics, and time-series analysis.
Michel Wedel is PepsiCo Professor of Consumer Research in the Robert H. Smith School of Business at the University of Maryland and holds an honorary chair at the University of Groningen. Michel has taught various courses for BBA, MBA, and PhD students on marketing research, marketing analysis, and marketing decision making. His main research interests are in the application of statistical and econometric methods to problems in marketing and marketing research. Much of his recent work addresses issues in visual marketing using eye-tracking technology. He serves on the editorial boards of several journals and is area editor of Marketing Science and Journal of Marketing Research. His work has been awarded with several prizes, such as the O’Dell best-paper award from Journal of Marketing Research, the Hendrik Muller award for outstanding contributions to the social sciences from the Royal Dutch Academy of the Sciences, and the Gilbert A Churchill award for lifetime achievement in the academic study of marketing research from the American Marketing Association.
Philip Hans Franses is Professor of Applied Econometrics and Professor of Marketing Research, both at the Erasmus University Rotterdam. His research interests are econometrics, time-series analysis, forecasting, marketing, and empirical finance. He publishes on these topics in international journals and in books. He currently serves as the dean of the Erasmus School of Economics.
Journal of Marketing Research, Volume 47, Number 1, February 2010
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