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Business Impact

Popularity Poll Ranks Startups

Measuring online buzz could help investors, a company claims.

The buzz surrounding a startup might not guarantee success, but it can help when it’s time to find funding. Now a company that offers tools for monitoring the startup scene has released a ranking of over 25,000 startup businesses according to their “impact and importance”–in other words, how much buzz they are generating.

Topping the list are familiar companies like the social-networking sites Facebook and LinkedIn, and the video-hosting site Hulu. The other companies in the top 10 are Etsy, Twitter, Yelp, OpenDNS, Mahalo, Kayak, and Blip.tv. Companies that have jumped up the rankings over the past month include Care.com, a source for local caregivers; Reply.com, a place to buy or sell online clicks; and Quantcast.com, a site that generates statistics of websites’ traffic. One of the biggest movers is the PowerPoint-presentation-sharing site SlideShare.

Last year, the company behind the new list, YouNoodle, launched a tool designed to predict how much money a startup would raise, based largely on the background and business connections of its founders. The Startup Predictor tool employs information inputted by users to come up with a three-year value for a startup before it has received significant funding.

However, the idea that a software program could do the same job as an experienced venture capitalist was met with skepticism last year from some observers.

YouNoodle’s new ranking system assigns startups a popularity ranking based on a measure of their media influence and online attention. The company’s software tracks media activity by gathering information from press releases and news outlets. It also measures social traction by monitoring activity on Twitter, blog aggregators like Technorati, and investment-focused sites like AngelSoft and CrunchBase. The approach is more automated than the user-generated market-style prediction systems employed by sites like the Industry Standard and Killer Startups to forecast startups’ success.

“There’s about a hundred billion dollars a year that’s changing hands around investments and startups, [but] there’s no standardized scores for startups, entrepreneurs, VCs, and so on,” says YouNoodle cofounder Bob Goodson.

“It’s a really cool tool,” says Eric Hill, director of product and design for the Industry Standard, which has about 6,000 users participating in its startup prediction market. “Any prediction market is really a barometer of the current news cycle,” he adds.

The company maintains that the tool isn’t meant to take the place of human expertise. “By scoring a startup, we give the first indication of its potential,” says Goodson. “We never expect to completely replace humans.”

Even so, some experts question how useful an automated system like this can truly be.

David Robinson, an associate professor of entrepreneurial finance at Duke University, says that the success of a startup is inherently difficult to predict: “Even if you give me smart people and a good idea and ample funding, there’s still scope for it to fail.”

Others are blunter with their criticism. Entrepreneur and investor Brad Feld says that quantitative predictive models cannot work for innovation or entrepreneurial success because “factors like this dramatically oversimplify the drivers of success (and failure) in entrepreneurial ventures.”

YouNoodle plans to make money by licensing more in-depth information to VCs and other investors. The company also claims to have 150,000 members on its social network.

Josh Lerner, a professor at Harvard Business School, has published research showing that an entrepreneur’s second startup has slightly better odds of succeeding than her first, and that having one successful startup makes a second startup more likely to succeed. “That suggests there are definitely patterns out there that work,” Lerner says. “I’m sure if you were really to punch the data, you’d find there were many other patterns.”

However, Lerner is cautious about relying on prediction tools too much. “So far, it’s hard for me to believe there isn’t an important element of randomness that constitutes a successful entrepreneurial venture,” he says.

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