Modeling Competition and Its Impact on Paid-Search Advertising
Yang, Sha; Shijie, Lu; and Xianghua, Lu (2013), “Modeling Competition and Its Impact in Paid-Search Advertising,” Marketing Science, Forthcoming.
56 Pages Posted: 5 Jul 2013 Last revised: 1 Jan 2019
As paid search becomes the mainstream platform for online advertising today, competition further intensifies. The main objective of this research is two-fold. On the one hand, we want to understand, in the context of paid-search advertising, the effects of competition (measured by number of ads on the paid-search listings) on click-volume and CPCs 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) We model the realized click-volume of each entrant as a function of the baseline click-volume and the decay factor, ii) We model the vector of realized CPCs of those entrants as a function of the decay factor and the order statistics of the value-per-clicks at an equilibrium condition, and iii) We model number of entrants as the multiplication of the number of potential entrants and the entry probability, and 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 data of 1597 keywords associated with digital camera/video and accessories with full information on competition. Our empirical analysis indicates that the number of competing ads has a significant impact on 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
JEL Classification: B21, B23, C11, D21, D44, M31, M37
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