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Observed and Unobserved Preference Heterogeneity in Brand-Choice Models

Author

Listed:
  • Dan Horsky

    (William E. Simon Graduate School of Business Administration, University of Rochester, Rochester, New York 14627)

  • Sanjog Misra

    (William E. Simon Graduate School of Business Administration, University of Rochester, Rochester, New York 14627)

  • Paul Nelson

    (William E. Simon Graduate School of Business Administration, University of Rochester, Rochester, New York 14627)

Abstract

This paper extends the scanner-based choice literature by explicitly incorporating individual-level brand-preference data. We illustrate our model using a unique data set that combines survey and scanner data collected from the same individuals. The addition of individual-specific brand-preference information significantly improves fit and prediction. Furthermore, this “observed” heterogeneity better explains choice than does “unobserved” heterogeneity in the standard scanner model's parameters. More importantly, we find that the standard model underestimates the importance of consumers' brand preferences and overestimates both brand loyalties and price sensitivities. Brand loyalty is overestimated because models without preference information confound state dependence, heterogeneity, and preference effects. Price sensitivities are inflated because the “average” preference-based consumer is implicitly assumed to be more willing to switch from his preferred brand than is the “real” preference-based consumer. Further, standard models overestimate the heterogeneity in price and loyalty sensitivities and misidentify both price- and loyalty-sensitive consumers. The managerial implications of our findings and the applicability of our methodology when survey data are collected infrequently and for only a subsample of consumers are pursued. We demonstrate that even under these circumstances better populationwide pricing and promotion decisions are identified and more accurate targeting results.

Suggested Citation

  • Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
  • Handle: RePEc:inm:ormksc:v:25:y:2006:i:4:p:322-335
    DOI: 10.1287/mksc.1050.0192
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    References listed on IDEAS

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    1. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    2. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    3. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    4. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    5. Füsun Gönül & Kannan Srinivasan, 1993. "Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues," Marketing Science, INFORMS, vol. 12(3), pages 213-229.
    6. Pradeep Chintagunta & Jean-Pierre Dubé & Khim Yong Goh, 2005. "Beyond the Endogeneity Bias: The Effect of Unmeasured Brand Characteristics on Household-Level Brand Choice Models," Management Science, INFORMS, vol. 51(5), pages 832-849, May.
    7. Hausman, Jerry A. & Ruud, Paul A., 1987. "Specifying and testing econometric models for rank-ordered data," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 83-104.
    8. Pradeep K. Chintagunta & Ramarao Desiraju, 2005. "Strategic Pricing and Detailing Behavior in International Markets," Marketing Science, INFORMS, vol. 24(1), pages 67-80, June.
    9. Tülin Erdem, 1996. "A Dynamic Analysis of Market Structure Based on Panel Data," Marketing Science, INFORMS, vol. 15(4), pages 359-378.
    10. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    11. Jie Zhang & Lakshman Krishnamurthi, 2004. "Customizing Promotions in Online Stores," Marketing Science, INFORMS, vol. 23(4), pages 561-578, June.
    12. Keane, Michael P, 1997. "Modeling Heterogeneity and State Dependence in Consumer Choice Behavior," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 310-327, July.
    13. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    14. John C. Liechty & Duncan K. H. Fong & Wayne S. DeSarbo, 2005. "Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(2), pages 285-293, November.
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