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A Dynamic Model of Sponsored Search Advertising

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Abstract

Sponsored search advertising is ascendant---Jupiter Research reports expenditures rose 28% in 2007 to $8.9B and will continue to rise at a 15% CAGR, making it one of the major trends to affect the marketing landscape. Yet little, if any empirical research focuses upon search engine marketing strategy by integrating the behavior of various agents in sponsored search advertising (i.e., searchers, advertisers, and the search engine platform). The dynamic structural model we propose serves as a foundation to explore these and other sponsored search advertising phenomena. Fitting the model to a proprietary data set provided by an anonymous search engine, we conduct several policy simulations to illustrate the benefits of our approach. First, we explore how information asymmetries between search engines and advertisers can be exploited to enhance platform revenues. This has consequences for the pricing of market intelligence. Second, we assess the effect of allowing advertisers to bid not only on key words, but also by consumers searching histories and demographics thereby creating a more targeted model of advertising. Third, we explore several different auction pricing mechanisms and assess the role of each on engine and advertiser profits and revenues. Finally, we consider the role of consumer search tools such as sorting on consumer and advertiser behavior and engine revenues. One key finding is that the estimated advertiser value for a click on its sponsored link averages about 24 cents. Given the typical $22 retail price of the software products advertised on the considered search engine, this implies a conversion rate (sales per click) of about 1.1%, well within common estimates of 1-2% (gamedaily.com). Hence our approach appears to yield valid estimates of advertiser click valuations. Another finding is that customers appear to be segmented by their clicking frequency, with frequent clickers placing a greater emphasis on the position of the sponsored advertising link. Estimation of the policy simulations is in progress.

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  • Song Yao & Carl F. Mela, 2008. "A Dynamic Model of Sponsored Search Advertising," Working Papers 08-16, NET Institute, revised Sep 2008.
    • Handle: RePEc:net:wpaper:0816
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    Cited by:

    1. Zsolt Katona & Miklos Sarvary, 2010. "The Race for Sponsored Links: Bidding Patterns for Search Advertising," Marketing Science, INFORMS, vol. 29(2), pages 199-215, 03-04.
    2. Cédric Argenton & Jens Prüfer, 2012. "Search Engine Competition With Network Externalities," Journal of Competition Law and Economics, Oxford University Press, vol. 8(1), pages 73-105.
    3. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    4. Winer, Russell S., 2009. "New Communications Approaches in Marketing: Issues and Research Directions," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 108-117.
    5. Weijia Dai & Hyunjin Kim & Michael Luca, 2016. "Which Firms Gain from Digital Advertising? Evidence from a Field Experiment," Harvard Business School Working Papers 17-025, Harvard Business School, revised Jan 2023.

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    More about this item

    Keywords

    Sponsored Search Advertising; Two-sided Market; Dynamic Game; Structural Models; Empirical IO; Customization; Auctions;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

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