Modeling Competition and its Impact on Paid-Search Advertising

Posted: 28 Feb 2014

See all articles by Sha Yang

Sha Yang

University of Southern California - Marshall School of Business

Shijie Lu

University of Houston - C.T. Bauer College of Business

Xianghua Lu

Fudan University - School of Management

Date Written: 2014

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.

Keywords: paid-search advertising, competition, Internet marketing, Bayesian estimation

Suggested Citation

Yang, Sha and Lu, Shijie and Lu, Xianghua, Modeling Competition and its Impact on Paid-Search Advertising (2014). Marketing Science, Vol. 33, No. 1, 2014; pp. 134-153; DOI: 10.1287/mksc.2013.0812. Available at SSRN: https://ssrn.com/abstract=2397614

Sha Yang (Contact Author)

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA 90089
United States

Shijie Lu

University of Houston - C.T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

Xianghua Lu

Fudan University - School of Management ( email )

670 Handan Road
Shanghai
China

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