Internet advertising is perhaps the number one current application (revenue-wise) for algorithmic game theory, and is paying the salaries of many AGT researchers in Microsoft, Yahoo, Google, and elsewhere. Beyond the basic “generalized second price auction” used for ad-auctions, there are many other issues and questions involved.
About a week ago, Google annouced a new beta program for interest-based targeting (a form of behavioral targeting). The basic idea is very simple: allow advertisers to target ads to segments of people according to their previous Internet behavior and not just the current web-page that they are on. E.g. if you visit many sports web-sites, the it makes sense to show you sports-related ads even on a general news page rather than, say, detergent ads. In general, this should result in less annoying (or even actually useful) ads for the viewer, higher effectiveness for the advertiser, and higher revenue for the web-site “publisher” (and of course, for my own current employer, Google).
Technically, this is quite easy to do using browser cookies, and is already heavily used by most advertising middlemen on the web. The catch is of course in the privacy issues. It seems that the main innovation here was in how Google managed to handle the privacy issues, as explained on it’s public policy blog. The main technical ingredient here is the ads preferences manager that gives viewers full control of their data.
Turing's Invisible Hand 
What exactly do all those AGT researchers do to increase profitability?
Yahoo has a fantastic labs program but is a total laggard.
Shouldn’t we stop pretending that AGT has any relation to the real world?
[…] but also various characteristics of the user such as his geographic location (and sometimes much more). While much of the early work on ad auctions focused on the single auction, much of the current […]