Google Searches for Ad Dollars in Social Networks

New patents aim to pry profits from patterns

Photo-Illustration: Armand Veneziano; Original photo: Ryan McVay/Getty Images

The U.S. Patent and Trademark Office recently published a series of intriguing patent applications from Google. They raise questions about the search giant’s significance for the profitability of social networks—and whether anyone has figured out how best to translate Web 2.0 hype into bankable income. Dozens of social-networking sites such as MySpace, Facebook, Bebo, and Friendster continue to flourish like Web startâ''ups in the dot-com heyday—consuming engineering talent, computing resources, and thousands of lines of code along the way. But no one has yet found the golden keys to profitability. The three Google patents, which rely on language processing and other technology to search for patterns in data, could ratchet up social networks’ ad revenue by better targeting ads to individuals, experts say.

Most social network sites rely on ads for revenue, but according to New York City research firm eMarketer, those sites account for just one US $1.4 billion slice of the $50 billion online advertising pie. A good click-through rate for advertising on traditional media sites is 2 percent, but ”on Facebook, you’re lucky if you’re going to get 0.3 percent,” says Jaffer Ali, CEO of online advertising agency Vidsense, based in Mokena, Ill.

The patents—Open Profile Content Identification, Custodian Based Content Identification, and Related Entity Content Identification—and the algorithms behind them would let Google find patterns in users’ profiles, pages, and friend lists in order to better target ads to them. Ideally, they would make the users more likely to click through.

Google’s Related Entity patent, for one, involves prying information from a user’s list of friends or user groups. But Google is not alone in this field. In June the social ad firm SocialMedia Networks said it had invented an algorithm called FriendRank that also scours a user’s friendship lists for friends whose names might be dropped in a targeted ad.

The Open Profile and Custodian patents would mine data from, say, a MySpace user’s profile and the profile of the MySpace page the user is visiting. The Open Profile patent, for instance, would consider a user profile like ”I really enjoy hiking, especially long hikes when you can camp out for a few days. Indoor activities don’t interest me at all, and I really don’t like boring outdoor activities like gardening.”

Using smart language-processing algorithms to detect the user’s sentiments (”enjoy” or ”don’t like” near ”hiking” or ”gardening”) and other linguistic cues, the system would then potentially serve up active outdoor sports-related ads to this user but avoid ads about more hobbyist-oriented activities.

While none of Google’s proposed patents look into business strategies that social networking ad agencies haven’t tried already, says Hussein Fazal, CEO of Toronto-based agency AdParlor, its language-processing and pattern-recognizing algorithms are probably key to the whole enterprise. However, Google did not disclose its particular pattern-searching algorithms, and a Google spokesperson declined an interview.

AdParlor’s ad targeting, Fazal says, typically examines four or five factors, such as a social-network user’s gender, age, and location. But Google’s computing resources, he says, ”might be able to analyze everything about that user.”

Is there a patent fight brewing in all this algorithm activity? Jeremy Pinkham, chief technical officer of social-media advertising company Lotame Solutions, based in Elkridge, Md., doesn’t think so.

”There’s a lot of room for different folks to try different approaches,” he says. Google’s new patents help to ”validate that this industry is worth people’s attention.”

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