How Semantic and Social Search Are Evolving: Lessons From the Evri-Twine Merger

bullish on the potential for innovating in the sector. “I believe the opportunities from social-semantic search startups remain as big as ever, but only if the business model makes sense from a very early stage,” he says.

That means getting the model right at a small scale and then increasing the technology investment, Judkins says. The key, he says, is to develop on the cheap and “don’t wave the red flag in front of Google.” In other words, realize that as a startup, you won’t beat the big search engines at most applications, and that you need a clear plan for getting traction with a small number of consumers by focusing on a particular niche area—like social media tracking, contextual discovery, or semantic advertising.

But where semantic and social search are headed still isn’t clear. “Overall it is obviously early days in the space. There is a lot of activity from startups and from Google and Microsoft, but the category hasn’t really been defined,” says Cameron Myhrvold, a founding partner of Ignition Partners, based in Bellevue, WA. Myhrvold leads Ignition’s investment in Topsy, a social search startup in San Francisco focused on Twitter, around which he is seeing a lot of activity. “Growth is immense, and at least at Topsy, user volumes and data volumes are exploding,” he says.

Of course, even if a startup’s business model works and it gains some traction, its product might not be better than what the incumbents will provide. Brian Bershad, Google’s Seattle engineering and site director, said in November at an Xconomy event held at the University of Washington, “I would actually not encourage small companies to go after anything in search having to do with text, because I think we’re going to get there.” Other experts at the event suggested that startups would be smart to pursue search in other niche markets like video or location-based services.

That doesn’t really help Evri, though. For better or worse, the company doesn’t seem to be in a huge rush to get to profitability. “Right now we’re really focused on building out the product and getting the right experience,” Hunsinger says, but he is also “thinking about the core revenue model.” Although he wouldn’t share any details just yet, this is certainly crucial to the near and long-term future of the company—and the semantic search landscape. Paul Allen’s Vulcan Capital may have deep pockets, but it is doubling down on Evri, and it needs to see some results.

And that dovetails with what Evri’s front man said when I asked him about the most challenging aspect of his job. “This is a highly competitive, fast-moving space to be in,” Hunsinger says. “You don’t have the opportunity to noodle too long on where you’re going to stake your claim.”

Author: Gregory T. Huang

Greg is a veteran journalist who has covered a wide range of science, technology, and business. As former editor in chief, he overaw daily news, features, and events across Xconomy's national network. Before joining Xconomy, he was a features editor at New Scientist magazine, where he edited and wrote articles on physics, technology, and neuroscience. Previously he was senior writer at Technology Review, where he reported on emerging technologies, R&D, and advances in computing, robotics, and applied physics. His writing has also appeared in Wired, Nature, and The Atlantic Monthly’s website. He was named a New York Times professional fellow in 2003. Greg is the co-author of Guanxi (Simon & Schuster, 2006), about Microsoft in China and the global competition for talent and technology. Before becoming a journalist, he did research at MIT’s Artificial Intelligence Lab. He has published 20 papers in scientific journals and conferences and spoken on innovation at Adobe, Amazon, eBay, Google, HP, Microsoft, Yahoo, and other organizations. He has a Master’s and Ph.D. in electrical engineering and computer science from MIT, and a B.S. in electrical engineering from the University of Illinois, Urbana-Champaign.