This is interesting: Earlier this month, Facebook filed for a patent to further hone its ad-targeting technology so that ads can be based on what a user's friends interests may be. The reason for this, it appears, is so that Facebook can better serve ads toward users who have not filled out their profiles with enough information for traditional ad targeting.
Facebook calls this second-degree targeting "inferential."
"Members of social networks often do not populate their profiles to include all of their interests and other personal information," the patent application explains. "As a result, using personal information in ad targeting is typically not available for all members of the social network. Traditional ad targeting techniques are thus limited because they can reach only a subset of the members in the social network for whom the ads are intended."
Obviously, just because you're friends with someone doesn't mean you share the same interests. But if a sizable percentage of your Facebook friends share the same interests, it's pretty safe to assume that you might, too. The patent application suggests that advertisers may be able to select how heavily they want inferential targeting to be weighted.
"For example, an advertiser may determine that an ad may infer an interest for a member if more than 25 percent of the member's connections satisfy the secondary inferential targeting criteria or if at least 3 connections meet the main targeting criteria, or a combination of both," the patent application explained. "The ad targeting method may also weight the member's connections or otherwise take into account the member's affinity or other measure of closeness to the member's connections. Any combination of the above methods may be implemented in the ad targeting method."
It's a fascinating new twist in targeted advertising--and also, we'd theorize, something that may get lawmakers concerned about the scope of information to which third parties have access (again). Facebook would likely retort that such data is safely anonymized.