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Tailored Cheap Talk

Author

Listed:
  • Gardete, Pedro M.

    (Stanford University)

  • Bart, Yakov

    (Northeastern University)

Abstract

We consider a persuasion setting in which the sender of a message tries to elicit a desired action from a receiver by means of a compelling argument. In order to understand which arguments may indeed be compelling, the sender can use information about the receiver’s preferences prior to the communication stage. We find that when the sender’s motives are transparent to the receiver, communication can only be influential if the sender is not well informed about the receiver’s preferences. The sender prefers an interior level of information quality, while the receiver prefers complete privacy unless disclosure is necessary to induce communication. We also find that the parties may fail to trade at intermediate communication cost levels. In other cases, the content and cost of communication can affect market outcomes simultaneously. Finally, in general, the sender’s first-best outcome involves pooling with unattractive sender types: he prefers to stay relatively guarded about aspects he is knowledgeable of in order to hinder the receiver’s discernment when topics he does not master are touched upon. Our results are discussed in the contexts of matching markets, including online advertising, sales, expert advice, dating and job search.

Suggested Citation

  • Gardete, Pedro M. & Bart, Yakov, 2018. "Tailored Cheap Talk," Research Papers 3400, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:3400
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    File URL: https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/413996
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    Cited by:

    1. Dmitri Kuksov & J. Miguel Villas-Boas, 2019. "The Performance Measurement Trap," Marketing Science, INFORMS, vol. 38(1), pages 68-87, January.
    2. Ronny Behrens & Natasha Zhang Foutz & Michael Franklin & Jannis Funk & Fernanda Gutierrez-Navratil & Julian Hofmann & Ulrike Leibfried, 2021. "Leveraging analytics to produce compelling and profitable film content," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(2), pages 171-211, June.
    3. T. Tony Ke & Yuting Zhu, 2021. "Cheap Talk on Freelance Platforms," Management Science, INFORMS, vol. 67(9), pages 5901-5920, September.
    4. Tinglong Dai & Shubhranshu Singh, 2020. "Conspicuous by Its Absence: Diagnostic Expert Testing Under Uncertainty," Marketing Science, INFORMS, vol. 39(3), pages 540-563, May.
    5. David A. Schweidel & Yakov Bart & J. Jeffrey Inman & Andrew T. Stephen & Barak Libai & Michelle Andrews & Ana Babić Rosario & Inyoung Chae & Zoey Chen & Daniella Kupor & Chiara Longoni & Felipe Thomaz, 2022. "How consumer digital signals are reshaping the customer journey," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1257-1276, November.
    6. J. Miguel Villas-Boas, 2020. "Repeated Interaction in Teams: Tenure and Performance," Management Science, INFORMS, vol. 66(3), pages 1496-1507, March.
    7. Ham, Sung H. & He, Chuan & Zhang, Dan, 2022. "The promise and peril of dynamic targeted pricing," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1150-1165.
    8. Amir Habibi, 2023. "Communicating Preferences to Improve Recommendations," Rationality and Competition Discussion Paper Series 394, CRC TRR 190 Rationality and Competition.
    9. Jiwoong Shin & Jungju Yu, 2021. "Targeted Advertising and Consumer Inference," Marketing Science, INFORMS, vol. 40(5), pages 900-922, September.
    10. Caldieraro, Fabio & Cunha, Marcus, 2022. "Consumers’ response to weak unique selling propositions: Implications for optimal product recommendation strategy," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 724-744.

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