A mediator is a well-known construct in game theory, and is an entity that plays on behalf of some of the agents who choose to use its services, while the rest of the agents participate in the game directly. We initiate a game theoretic study of sponsored search auctions, such as those used by Google and Yahoo!, involving {\em incentive driven} mediators. We refer to such mediators as {\em for-profit} mediators, so as to distinguish them from mediators introduced in prior work, who have no monetary incentives, and are driven by the altruistic goal of implementing certain desired outcomes. We show that in our model, (i) players/advertisers can improve their payoffs by choosing to use the services of the mediator, compared to directly participating in the auction; (ii) the mediator can obtain monetary benefit by managing the advertising burden of its group of advertisers; and (iii) the payoffs of the mediator and the advertisers it plays for are compatible with the incentive constraints from the advertisers who do dot use its services. A simple intuition behind the above result comes from the observation that the mediator has more information about and more control over the bid profile than any individual advertiser, allowing her to reduce the payments made to the auctioneer, while still maintaining incentive constraints. Further, our results indicate that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of agents to coexist.
Deep Dive into For-profit mediators in sponsored search advertising.
A mediator is a well-known construct in game theory, and is an entity that plays on behalf of some of the agents who choose to use its services, while the rest of the agents participate in the game directly. We initiate a game theoretic study of sponsored search auctions, such as those used by Google and Yahoo!, involving {\em incentive driven} mediators. We refer to such mediators as {\em for-profit} mediators, so as to distinguish them from mediators introduced in prior work, who have no monetary incentives, and are driven by the altruistic goal of implementing certain desired outcomes. We show that in our model, (i) players/advertisers can improve their payoffs by choosing to use the services of the mediator, compared to directly participating in the auction; (ii) the mediator can obtain monetary benefit by managing the advertising burden of its group of advertisers; and (iii) the payoffs of the mediator and the advertisers it plays for are compatible with the incentive constraints
With the growing popularity of the Web for obtaining information via search, sponsored search advertising, where advertisers pay to appear alongside the algorithmic results, has become a significant business model and is responsible for the success of internet giants such as Google and Yahoo! The statistics show that the growth of the overall online advertising market has been around 30% every year, as compared to the 1-2% of the traditional media. The first quarter of 2007 also saw a tremendous increase in revenue from online advertising that is 26% over that in 2006. Search remains the largest revenue format, accounting for more than 40% of the 2006 full year revenues of around $17 billion.
In a search-based advertising format, the Search Engine allocates the available advertising space using an auction, where individual advertisers bid upon specific keywords. When a user queries for a keyword, the search engine (the auctioneer) allocates the advertisement space to the bidding merchants based on their bid values and their estimated fitness values. Usually, the ads appear in a separate section of the page designated as “sponsored search results,” which is located above or to the right of the organic/algorithmic results. Each position in such a list of sponsored links is called a slot. Generally, users are more likely to notice and click on a higher ranked slot, leading to more traffic for the corresponding advertisers. Therefore, advertisers prefer to be in higher ranked slots and compete for them. In a popular scheme, known as the Cost-Per-Click (CPC) or the Pay-Per-Click (PPC) model, whenever a user clicks on an ad, the corresponding advertiser pays an amount specified by the auctioneer.
From the above description, we can note that after merchants have bid for a specific keyword, when that keyword is queried, auctioneer follows two steps. First, she allocates the slots to the advertisers. Normally, this allocation is done using some ranking function. Secondly, she decides, through some pricing scheme, how much a merchant should be charged if the user clicks on her ad and in general this depends on which slot she was assigned, on her bid and that of others. In the auction formats for sponsored search, there are two ranking functions, namely rank by bid (RBB) and rank by revenue(RBR) and there are two pricing schemes, namely generalized first pricing(GFP) and generalized second pricing(GSP) which have been used widely. In RBB, bidders are ranked solely according to their bid values. The advertiser with the highest bid gets first slot, that with the second highest bid gets the second slot and so on. In RBR, the bidders are ranked according to the product of their bid value and quality score. The quality score represents the merchant’s relevance to the specific keyword, which can basically be interpreted as the possibility that her ad will be viewed if given a slot irrespective of what slot position she is given. In GFP, the bidders are essentially charged the amount they bid and in GSP they are charged an amount which is enough to ensure their current slot position. For example, under RBB allocation, GSP charges a bidder an amount equal to the bid value of the bidder just below her.
Formal analysis of such sponsored search advertising models has been done extensively in recent years, from algorithmic as well as from game theoretic perspectives [3,7,4,1,9,5,6]. For example, the existence of different types of incentive-driven Nash equilibria has been established. Further, the notion of a mediator in such position auctions has also been discussed [2]. A mediator is a reliable entity, which can play on the behalf of agents in a given game, however it can not enforce the use of its services, and each agent is free to participate in the game directly. In the paper by Ashlagi et al. [2] and the references therein, the motivation for the use of mediator comes from the search of means to implement particular outcomes, such as VCG, in a given mechanism such as RBR with GSP. However, the mediators considered so far are altruistic in nature and have no incentives, and in particular, their only goal is to implement certain outcomes despite the financial cost incurred. As we know, the marketplace is mostly about incentives-a game between selfish agents-and it would be interesting to study mediators which are not altruistic.
In our present work, we initiate a study of mediators in sponsored search auctions, which may not be altruistic in nature. We call such mediators as for-profit mediators and show that advertisers can improve their payoffs by using the services of the mediator compared to directly participating in the auction and mediator can also obtain monetary benefit by managing the advertising burden of its advertisers and in fact at the same time being compatible with incentive constraints from the advertisers who do dot use its service. The simple intuition behind the above result comes from the observation
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