A Cascade Model for Externalities in Sponsored Search

Abstract

Abstract. One of the most important yet insufficiently studied issues in online advertising is the externality effect among ads: the value of an ad impression on a page is affected not just by the location that the ad is placed in, but also by the set of other ads displayed on the page. For instance, a high quality competing ad can detract users from another ad, while a low quality ad could cause the viewer to abandon the page altogether. In this paper, we propose and analyze a model for externalities in sponsored search ads. Our model is based on the assumption that users will visually scan the list of ads from the top to the bottom. After each ad, they make independent random decisions with ad-specific probabilities on whether to continue scanning. We then generalize the model in two ways: allowing for multiple separate blocks of ads, and allowing click probabilities to explicitly depend on ad positions as well. For the most basic model, we present a polynomial-time incentive-compatible auction mechanism for allocating and pricing ad slots. For the generalizations, we give approximation algorithms for the allocation of ads.

Sponsored Search Auctions with Markovian Users

“…They analyze user behavior, advertiser bidding strategies and Bayesian equilibria in their model. Independently of our work (which also appeared in [1,2]), Mahdian and Kempe [13] study the same model we do here. They also provide an O(n log n + nk) dynamic program for allocation; however at that point they generalize to the case of position-dependent continuation probabilities and provide an approximation algorithm for this case, whereas we go on to study deeper structural and incentive properties in the original model.…”

“…One small extension of our model is to make the continuation probability q i a function of location as well, which makes the optimization problem more difficult; Mahdian and Kempe [13] have given an approximation algorithm for this case, and so it is natural to ask if position monotonicity is preserved in their algorithm. One can also generalize the Markov model to handle arbitrary configurations of ads on a web page (not necessarily a search results page), or to allow various other user states (such as navigating a landing page).…”

Comparing predicted prices in auctions for online advertising

“…(See Varian (2006), Blumrosen et al (2008), Kempe and Mahdian (2008);and Gomes et al (2008) for more detail.) For simplicity, we ignore this effect in our simulations.…”

An Incentive–Compatible Revenue–Sharing Mechanism for the Economic Sustainability of Multi–domain Search Based on Advertising

“…There are several models correlating the click probabilities to these parameters. Of these, the cascade model, which assumes that the user scans the links from the top to the bottom in a Markovian way [14,15], is the most commonly used. These models introduce so-called externalities in the auction whereby the click probability, and therefore an advertiser's profit depends on which other ads are shown in conjunction.…”