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Contextual Advertising

Author

Listed:
  • Kaifu Zhang

    () (Cheung Kong Graduate School of Business, Beijing 100738, China)

  • Zsolt Katona

    () (Haas School of Business, University of California, Berkeley, Berkeley, California 94720)

Abstract

Contextual advertising entails the display of relevant ads based on the content that consumers view, exploiting the potential that consumers' content preferences are indicative of their product preferences. This paper studies the strategic aspects of such advertising, considering an intermediary who has access to a content base, sells advertising space to advertisers who compete in the product market, and provides the targeting technology. The results show that contextual targeting impacts advertiser profit in two ways: First, advertising through relevant content topics helps advertisers reach consumers with a strong preference for their product. Second, heterogeneity in consumers' content preferences can be leveraged to reduce product market competition, especially when competition is intense. The intermediary has incentives to strategically design its targeting technology, sometimes at the cost of the advertisers. When product market competition is moderate, the intermediary offers accurate targeting such that the consumers see the most relevant ads. When competition is high, the intermediary lowers the targeting accuracy such that the consumers see less relevant ads. Doing so intensifies competition and encourages advertisers to bid for multiple content topics in order to prevent their competitors from reaching consumers. In some cases, this may lead to an asymmetric equilibrium where one advertiser bids high even for the content topic that is more relevant to its competitor.

Suggested Citation

  • Kaifu Zhang & Zsolt Katona, 2012. "Contextual Advertising," Marketing Science, INFORMS, vol. 31(6), pages 980-994, November.
  • Handle: RePEc:inm:ormksc:v:31:y:2012:i:6:p:980-994
    DOI: 10.1287/mksc.1120.0740
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    File URL: http://dx.doi.org/10.1287/mksc.1120.0740
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wilfred Amaldoss & Preyas S. Desai & Woochoel Shin, 2015. "Keyword Search Advertising and First-Page Bid Estimates: A Strategic Analysis," Management Science, INFORMS, vol. 61(3), pages 507-519, March.
    2. Guitart, Ivan A. & Hervet, Guillaume, 2017. "The impact of contextual television ads on online conversions: An application in the insurance industry," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 480-498.
    3. Wang, Wei & Li, Gang & Fung, Richard Y.K. & Cheng, T.C.E., 2019. "Mobile Advertising and Traffic Conversion: The Effects of Front Traffic and Spatial Competition," Journal of Interactive Marketing, Elsevier, vol. 47(C), pages 84-101.
    4. Gong Qiang & Pan Siqi & Yang Huanxing, 2019. "Targeted Advertising on Competing Platforms," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 19(1), pages 1-20, January.
    5. Steven Schmeiser, 2018. "Sharing Audience Data: Strategic Participation in Behavioral Advertising Networks," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 52(3), pages 429-450, May.
    6. Chunhua Wu, 2015. "Matching Value and Market Design in Online Advertising Networks: An Empirical Analysis," Marketing Science, INFORMS, vol. 34(6), pages 906-921, November.
    7. Grewal, Dhruv & Bart, Yakov & Spann, Martin & Zubcsek, Peter Pal, 2016. "Mobile Advertising: A Framework and Research Agenda," Journal of Interactive Marketing, Elsevier, vol. 34(C), pages 3-14.
    8. Zhang, Jianqiang & He, Xiuli, 2019. "Targeted advertising by asymmetric firms," Omega, Elsevier, vol. 89(C), pages 136-150.
    9. Ng, Irene C.L. & Wakenshaw, Susan Y.L., 2017. "The Internet-of-Things: Review and research directions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 3-21.

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