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Modeling Competition and Its Impact on Paid-Search Advertising

Author

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  • Sha Yang

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Shijie Lu

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

  • Xianghua Lu

    (School of Management, Fudan University, Shanghai, China 200433)

Abstract

Paid search has become the mainstream platform for online advertising, further intensifying competition between advertisers. The main objective of this research is twofold. On the one hand, we want to understand, in the context of paid-search advertising, the effects of competition (measured by the number of ads on the paid-search listings) on click volume and the cost per click (CPC) of paid-search ads. On the other hand, we are interested in understanding the determinants of competition, that is, how various demand and supply factors affect the entry probability of firms and, consequently, the total number of entrants for a keyword. We regard each keyword as a market and build an integrative model consisting of three key components: (i) the realized click volume of each entrant as a function of the baseline click volume and the decay factor; (ii) the vector of realized CPCs of those entrants as a function of the decay factor and the order statistics of the value per click at an equilibrium condition; and (iii) the number of entrants, the product of the number of potential entrants multiplied by the entry probability; the entry probability is determined by the expected revenue (a function of expected click volume, CPC, and value per click) and the entry cost at the equilibrium condition of an incomplete information game. The proposed modeling framework entails several econometric challenges. To cope with these challenges, we develop a Bayesian estimation approach to make model inferences. Our proposed model is applied to a data set of 1,597 keywords associated with digital camera/video and their accessories with full information on competition. Our empirical analysis indicates that the number of competing ads has a significant impact on the baseline click volume, decay factor, and value per click. These findings help paid-search advertisers assess the impact of competition on their entry decisions and advertising profitability. In the counterfactual analysis, we investigate the profit implication of two polices for the paid-search host: raising the decay factor by encouraging consumers to engage in more in-depth search/click-through and providing coupons to advertisers.

Suggested Citation

  • Sha Yang & Shijie Lu & Xianghua Lu, 2014. "Modeling Competition and Its Impact on Paid-Search Advertising," Marketing Science, INFORMS, vol. 33(1), pages 134-153, January.
    • Handle: RePEc:inm:ormksc:v:33:y:2014:i:1:p:134-153
    DOI: 10.1287/mksc.2013.0812
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