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Consumer Search: Evidence from Path-tracking Data

Author

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  • Fabio Pinna
  • Stephan Seiler

Abstract

We estimate the effect of consumer search on the price of the purchased product in a physical store environment. We implement the analysis using a unique data set obtained from radio frequency identification tags, which are attached to supermarket shopping carts. This technology allows us to record consumers' purchases as well as the time they spent in front of the shelf when contemplating which product to buy, giving us a direct measure of search effort. Controlling for a host of confounding factors, we estimate that an additional minute spent searching lowers price paid by $2.10 which represents 8 percent of average trip-level expenditure.

Suggested Citation

  • Fabio Pinna & Stephan Seiler, 2014. "Consumer Search: Evidence from Path-tracking Data," CEP Discussion Papers dp1296, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp1296
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    References listed on IDEAS

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    1. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
    2. Elisabeth Honka, 2014. "Quantifying search and switching costs in the US auto insurance industry," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 847-884, December.
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    4. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-2980, October.
    5. Nitin Mehta & Surendra Rajiv & Kannan Srinivasan, 2003. "Price Uncertainty and Consumer Search: A Structural Model of Consideration Set Formation," Marketing Science, INFORMS, vol. 22(1), pages 58-84, June.
    6. Hoyer, Wayne D, 1984. "An Examination of Consumer Decision Making for a Common Repeat Purchase Product," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(3), pages 822-829, December.
    7. Draganska, Michaela & Klapper, Daniel, 2010. "Choice Set Heterogeneity and the Role of Advertising: An Analysis with Micro and Macro Data," Research Papers 2063, Stanford University, Graduate School of Business.
    8. Stephan Seiler, 2013. "The impact of search costs on consumer behavior: A dynamic approach," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 155-203, June.
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    Cited by:

    1. Petrikaitė, Vaiva, 2016. "Collusion with costly consumer search," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 1-10.

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    More about this item

    Keywords

    Consumer search; in-store marketing; path data;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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