Peer39 Wins Support From Venture Community for Non-Cookie-Based Ad Platform

Privacy advocates have long been up in arms about cookies—those data packets that store information about you in your browser, and that have become the basis of some technologies that allow companies to market directly to you. So a couple of years back, the venture community began looking for technology developers who had new approaches to helping advertisers find their target audiences on the Web, and who weren’t using cookies or anything else that might smell like an invasion of privacy.

Among the companies that caught the attention of VCs was Peer 39, a New York-based startup that uses semantic analysis—not cookies—to find the most appropriate settings for marketers on the Web. In late May, Peer39 raised $5.2 million in a Series D, bringing its total venture haul to $27 million. “What they offer is precise targeting, without raising concerns about privacy and safety,” says Warren Lee, a venture partner with Canaan Partners, which first invested in Peer39 in 2007 and was part of the recent round.

Peer39 was founded in Israel in 2006. The company started as an ad network, but shifted its model in 2009 to focus entirely on selling the technology it had developed to help advertisers optimize their ad placements by quickly scrutinizing the words on every Web page. The U.S. headquarters, where the executive team is based, opened three years ago. The R&D office remains in Petach Tikva, Israel.

Peer39’s technology is based on three key capabilities. First, it can distinguish between a content-rich page—such as a reported story on Xconomy (excuse the plug)—vs. something boring, like a login page for a password-restricted site.

Then it provides advertisers the ability to target categories of content, such as personal finance, parenting, or autos. “We’re able to look at billions of page impressions in any given day and say, ‘This page is about this particular class of cars and trucks,'” says Peer39’s CEO Andy Ellenthal, who was a veteran of DoubleClick and several ad-tech startups before he joined the company in 2010. “That’s fundamentally interesting to a lot of buyers.”

Finally, Peer39 can layer in “safety” criteria. “Some advertisers want to stay away from hard news about catastrophes,” Ellenthal says, “but other buyers could care less. Different brands have different thresholds for what’s appropriate.” Disney, for example, probably wouldn’t want to be seen on a page containing a story about alcoholic beverages. Budweiser, on the other hand, might covet that spot.

Peer39’s semantic technology can also rapidly detect changes in the sentiment behind certain words. For example, prior to the recent Missouri tornadoes, the term “Joplin” only appeared on .16 percent of pages, and 95 percent of those were music sites related to the legendary Janis Joplin. After the tornadoes, “Joplin” showed up on 2 percent of all Web pages, more than 90 percent of which Peer39 identified as part of a category it calls “Death/Disasters”—a negative environment for ad placements in Peer39’s vernacular. That made it easier for advertisers averse to negative content to steer clear of the disaster coverage.

Ellenthal says the secret to Peer39’s platform rests in its ability to use both natural language processing and machine learning. “They balance each other out,” he says. “Natural language processing looks at relationships between words. It’s very accurate, but not very fast. Machine learning understands how content changes over time, and it’s very fast.”

Peer39’s customers are ad networks and exchanges, agencies, and publishers. But Ellenthal believes the company’s biggest growth opportunity lies in real-time ad bidding platforms such as AdMeld, which was recently bought by Google (NASDAQ: GOOG) for $400 million. AdMeld is one of Peer39’s customers. “They use our service to provide buyers with more information about quality, safety, and the topic of pages,” Ellenthal says.

Canaan’s Lee adds that the popularity of real-time ad bidding has exploded in the last year, creating an opportunity for all ad-tech companies. But what he particularly likes about Peer39’s platform is that it’s both fast and scalable. “A lot of companies have developed technologies that are useful on a small scale, but when you get to a billion impressions a day, they break,” he says.

Ellenthal says that scaling up Peer39’s platform to meet the demand from AdMeld and other real-time players hasn’t been difficult. In January of 2010, Peer39’s technology was processing about 30 million page impressions a month, he says. “Right now we’re looking at 3 billion a day,” he says. “We’ll be close to 10 billion by the end of this month.”

Other ad-tech companies are starting to raise the interest of the venture community. On June 9, New York-based Taykey—another company founded in Israel—raised a $9 million Series B, led by Sequoia Capital, Softbank Capital, and Crescent Point. Co-founder Amit Avner says Taykey’s technology is also non-cookie-based, but that’s where its similarities to Peer39 end. Taykey’s algorithm uses real-time data and trend analysis to predict where an advertiser’s audience is likely to go next on the Web. The platform is most useful for companies that want to advertise on social-media sites or search engines, Avner says.

In a beta test, Pepsi used Taykey for two Facebook campaigns. Pepsi’s goal was to get 20,000 “likes,” and it ended up with 46,000, Avner says. One of Taykey’s goals is to improve the technology so the company can also participate in the real-time ad bidding boom, Avner says.

Ellenthal is encouraged by the venture community’s support for companies in his space, but he knows that Peer39 will have to do plenty of evangelizing to get stalwart brands to embrace newfangled ad technologies. “For us to continue to grow we’ll need to see more brand dollars flowing into these exchanges, and much bigger campaigns,” he says. “We need to make those brands comfortable leveraging these new technologies. They need to know their ads won’t end up on pages that are inappropriate, but rather in environments that are relevant to what they’re trying to do.”

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