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Personalized Discounts and Consumer Search

Author

Listed:
  • Zikun Liu

    (Yale University)

  • Jiwoong Shin

    (Yale University)

  • Jidong Zhou

    (Yale University)

Abstract

The growing availability of big data enables firms to predict consumer search outcomes and outside options more accurately than consumers themselves. This paper examines how a firm can utilize such superior information to offer personalized buy-now discounts intended to deter consumer search. However, discounts can also serve as signals of attractive outside options, potentially encouraging rather than discouraging consumer search. We show that, despite the firmÕs ability to tailor discounts across a continuum of consumer valuations, the firm-optimal equilibrium features a simple two-tier discount scheme, comprising a uniform positive discount when the consumer outside option is intermediate and no discount when the outside option is low or high. Furthermore, compared to a scenario where the firm lacks superior information, we find that the firm earns lower profits, consumers search more while their welfare remains unchanged, and total welfare declines.

Suggested Citation

  • Zikun Liu & Jiwoong Shin & Jidong Zhou, 2025. "Personalized Discounts and Consumer Search," Cowles Foundation Discussion Papers 2440, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2440
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    File URL: https://cowles.yale.edu/sites/default/files/2025-04/d2440.pdf
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    References listed on IDEAS

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    Cited by:

    1. Kun Zhang, 2025. "Uncharted Waters: Selling a New Product Robustly," Papers 2508.04134, arXiv.org.

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