Sponsored Search Auctions Research Articles

Research Note—Quality Uncertainty and the Performance of Online Sponsored Search Markets: An Empirical Investigation

Online sponsored search advertising has emerged as the dominant online advertising format largely because of their pay-for-performance nature, wherein advertising expenditures are closely tied to outcomes. While the pay-for-performance format substantially reduces the wastage incurred by advertisers compared to traditional pay-per-exposure advertising formats, the reduction of such wastage also carries the risk of reducing the signaling properties of advertising. Lacking a separating equilibrium, low-quality firms in these markets may be able to mimic the advertising strategies of high-quality firms. This study examines this issue in the context of online sponsored search markets. Using data gathered from sponsored search auctions for keywords in a market without intervention by the intermediary, we find evidence of adverse selection for products/services characterized by high uncertainty. On the other hand, there is no evidence of adverse selection for similar products in a regulated sponsored search market, suggesting that intervention by the search intermediary can have a significant impact on market outcomes and consumer welfare.

Multi-bidding strategy in sponsored search auctions

The generalized second price auction has recently become a much studied model for sponsored search auctions for Internet advertisement. Though it is known not to be incentive compatible, properties of its pure Nash equilibria have been well characterized under the single bidding strategy of each bidder. In this paper, we study the properties of pure Nash equilibria of the generalized second price auction when each bidder is allowed to submit more than one bid. This multi-bidding strategy is noted to have been adopted by companies for keyword advertisements on search engines. In consideration of the pure Nash equilibria, we completely characterize conditions on the number of selling slots for a pure Nash equilibrium to exist, assuming all the advertisers are allowed to use multi-bidding strategies or only one advertiser will use a multi-bidding strategy. Our findings reveal interesting properties of limitations and potentials of the generalized second price auction for the sponsored search market.

Optimal Auction Design and Equilibrium Selection in Sponsored Search Auctions

In analyses of sponsored search auctions for online advertising, it is customary to model the dynamic game of incomplete information by considering a static game of complete infor mation. This approach is used in Benjamin Edelman, Michael Ostrovsky and Michael Schwarz (2007) (EOS), Hal R. Varian (2007), and the subsequent literature. Modeling complex interactions in uncertain environments as games of complete information has a long history. For example, the Bertrand model of oligopolistic competition posits that companies know their competitors' costs based on their experience from prior interactions. The use of a static game of complete infor mation often offers important benefits. For one, it is tractable?avoiding complex multi period information sets in a dynamic game. Furthermore, a suitably chosen static game can capture important characteristics of the under lying dynamic game. When a game is repeated over an extended period, there is good reason to think participants will learn many characteris tics of their counterparts?supporting the use of a complete information model. Yet the use of a static game of complete information is also unsatisfying. There is no clear way to identify which (if any) equilibria of the static game of complete information are a relevant approximation of the equilibria of the dynamic game of incomplete information.

Optimal Bidding in Multi-Item Multi-Slot Sponsored Search Auctions

We study optimal bidding strategies for advertisers in sponsored search auctions. In general, these auctions are run as variants of second-price auctions but have been shown to be incentive incompatible. Thus, advertisers have to be strategic about bidding. Uncertainty in the decision- making environment, budget constraints and the presence of a large portfolio of keywords makes the bid optimization problem non-trivial. We present an analytical model to compute the optimal bids for keywords in an advertiser’s portfolio. To validate our approach, we estimate the parameters of the model using data from an advertiser’s sponsored search campaign and use the bids proposed by the model in a field experiment. The results of the field implementation show that the proposed bidding technique is very effective in practice. We extend our model to account for interactions between keywords, in the form of positive spillovers from generic keywords into branded keywords. The spillovers are estimated using a dynamic linear model framework and used to jointly optimize the bids of the keywords using an approximate dynamic programming approach. Accounting for the interaction between keywords leads to an additional improvement in the campaign performance.

An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms

In this paper, we first describe a framework to model the sponsored search auction on the Web as a mechanism design problem. Using this framework, we describe two well-known mechanisms for sponsored search auction - generalized second price (GSP) and Vickrey-Clarke-Groves (VCG). We then derive a new mechanism for sponsored search auction which we call optimal (OPT) mechanism. The OPT mechanism maximizes the search engine's expected revenue, while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We then undertake a detailed comparative study of the mechanisms GSP, VCG, and OPT. We compute and compare the expected revenue earned by the search engine under the three mechanisms when the advertisers are symmetric and some special conditions are satisfied. We also compare the three mechanisms in terms of incentive compatibility, individual rationality, and computational complexity.

A 'Position Paradox' in Sponsored Search Auctions

We study the bidding strategies of vertically differentiated firms that bid for sponsored search advertisement positions for a keyword at a search engine. We explicitly model how consumers navigate and click on sponsored links based on their knowledge and beliefs about firm qualities. Our model yields several interesting insights and a main counter-intuitive result we focus on is the position paradox. The paradox is that a superior firm may bid lower than an inferior firm and obtain a position below it, yet still obtain more clicks than the inferior firm. Under a pay-per- impression mechanism, the inferior firm wants to be at the top where more consumers click on its link, while the superior firm is better off by placing its link at a lower position as it pays a smaller advertising fee but some consumers will still reach it in the search of a higher-quality firm. Under a pay-per-click mechanism, the inferior firm has an even stronger incentive to be at the top since now it only has to pay for the consumers who do not know the firms' reputations and, therefore, can bid more aggressively. Interestingly, as the quality premium for the superior firm increases, and/or if more consumers know the identity of the superior firm, the incentive for the inferior firm to be at the top may increase. Contrary to conventional belief, we find that the search engine may have the incentive to over-weight the inferior firm's bid and strategically create the position paradox to increase overall clicks by consumers. To validate our model, we analyze a dataset from a popular Korean search engine firm and find that: (i) a large proportion of auction outcomes in the data show the position paradox, and (ii) sharp predictions from our model are validated in the data.

A “Position Paradox” in Sponsored Search Auctions

We study the bidding strategies of vertically differentiated firms that bid for sponsored search advertisement positions for a keyword at a search engine. We explicitly model how consumers navigate and click on sponsored links based on their knowledge and beliefs about firm qualities. Our model yields several interesting insights; a main counterintuitive result we focus on is the “position paradox.” The paradox is that a superior firm may bid lower than an inferior firm and obtain a position below it, yet it still obtains more clicks than the inferior firm. Under a pay-per-impression mechanism, the inferior firm wants to be at the top where more consumers click on its link, whereas the superior firm is better off by placing its link at a lower position because it pays a smaller advertising fee, but some consumers will still reach it in search of the higher-quality firm. Under a pay-per-click mechanism, the inferior firm has an even stronger incentive to be at the top because now it only has to pay for the consumers who do not know the firms' reputations and, therefore, can bid more aggressively. Interestingly, as the quality premium for the superior firm increases, and/or if more consumers know the identity of the superior firm, the incentive for the inferior firm to be at the top may increase. Contrary to conventional belief, we find that the search engine may have the incentive to overweight the inferior firm's bid and strategically create the position paradox to increase overall clicks by consumers. To validate our model, we analyze a data set from a popular Korean search engine firm and find that (i) a large proportion of auction outcomes in the data show the position paradox, and (ii) sharp predictions from our model are validated in the data.

Maintaining Equilibria During Exploration in Sponsored Search Auctions

We introduce an exploration scheme aimed at learning advertiser click-through rates in sponsored search auctions with minimal effect on advertiser incentives. The scheme preserves both the current ranking and pricing policies of the search engine and only introduces one set of parameters which control the rate of exploration. These parameters can be set so as to allow enough exploration to learn advertiser click-through rates over time, but also eliminate incentives for advertisers to alter their currently submitted bids. When advertisers have much more information than the search engine, we show that although this goal is not achievable, incentives to deviate can be made arbitrarily small by appropriately setting the exploration rate. Given that advertisers do not alter their bids, we bound revenue loss due to exploration.

On Robustness of Forward-looking in Sponsored Search Auction

We analyze the robustness of pure Nash Equilibria of sponsored search auctions, based on the forward-looking response function. To consider the robustness of such refined solution concept, we first study the convergence property of several adjustment schemes. Especially, we prove that under the randomized scheme, the auction always converges to a unique fixed point with probability one, whose revenue is equal to the celebrated VCG mechanism. Additionally, we study the robustness of such forward-looking strategic heuristic against aggressive selfish strategic heuristic called vindictive bidding. We investigate three types of such bidding strategies and substantiate that the pure Nash equilibrium still exists under two types even if there is an arbitrary portion of vindictive bidders.

Equilibrium analysis of dynamic bidding in sponsored search auctions

We analyse symmetric pure strategy equilibria in dynamic sponsored search auction games using simulations, restricting the strategies to several in a class of greedy bidding strategies introduced by Cary et al. We show that a particular convergent strategy, 'balanced bidding', also exhibits high stability to deviations in the dynamic setting. On the other hand, a cooperative strategy which yields high payoffs to all players is not sustainable in equilibrium play. Additionally, we analyse a repeated game in which each stage is a static complete information sponsored search game. In this setting, we demonstrate a collusion strategy which yields high payoffs to all players and empirically show it to be sustainable over a range of settings. Finally, we show how a collusive strategy profile can arise even in the case of incomplete information.

Strategic bidder behavior in sponsored search auctions

We examine sponsored search auctions run by Overture (now part of Yahoo!) and Google and present evidence of strategic bidder behavior in these auctions. Between June 15, 2002, and June 14, 2003, we estimate that Overture's revenue might have been higher if it had been able to prevent this strategic behavior. We present an alternative mechanism that could reduce the amount of strategizing by bidders, raise search engines' revenues, and increase the efficiency of the market. We conclude by showing that strategic behavior has not disappeared over time; it remains present on both search engines.

Quality Uncertainty and the Performance of Online Sponsored Search Markets: An Empirical Investigation

Sponsored search mechanisms, where advertisers bid for better placement in the listing of search results on search services such as Yahoo! and Google integrate the benefits of online search with advertising, and have emerged as the dominant revenue model for online search engines. Interestingly, Yahoo! and Google employ different mechanisms to determine the placement of bidders’ advertisements. This provides an unprecedented opportunity to not only test some of the predictions of earlier research relating advertiser’s quality and their advertising intensity, in the online setting, but to also examine whether intervention by the search intermediary impacts the performance of these markets. Using data from online sponsored search auctions this study examines whether the relationship between advertisers’ quality and their advertising intensity varies across product categories as well as across the different search mechanisms. Our results highlight significant and interesting differences in the quality-advertising relationships across the two market mechanisms as well as across products characterized by differing degrees of quality uncertainty.