Skewed Bidding in Pay-per-Action Auctions for Online Advertising

Abstract

Online search as well as keyword-based contextual advertising on third-party publishers is primarily priced using pay-per-click (PPC): advertisers pay only when a consumer clicks on the advertisement. Slots for advertisements are auctioned, and per-click bids are weighted by the probability of a click given that the advertisement is displayed (the “click-through rate”) in addition to other factors. The PPC method allows the advertising platform (e.g. Google) to bundle together otherwise heterogeneous items (impressions on different positions on a search page, on different search phrases sharing common “keywords,” and on different publishers) into more homogeneous units, simplifying the advertiser's bidding problem. However, PPC pricing has some drawbacks. First, all clicks are not created equal: clicks on a Paris, France hotel website that is displayed on a search for Paris Hilton may result in lower pro t conditional on the click. Second, for infrequently searched phrases on search engines or small content providers, it is difcult for the advertiser to accurately estimate conversion rates, increasing the risk and monitoring costs for the advertiser and diminishing their incentives to advertise broadly (indeed, on contextual networks, the advertising platform may not even provide the advertiser with suf cient accounting data about where the advertisements were displayed to allow the advertiser to distinguish sources of clicks, and the publisher mix may change on an ongoing basis.) Third, the problem of click fraud is fairly pervasive: when publishers receive a share of advertising revenue, advertisers place a single bid applying to many publishers, and revenue