Thursday, January 13, 2011

How To Make $20,000 By Finding Your Friend A Job

Your brilliant programmer friend is looking for a high tech job. You consult a Web site and find the perfect fit. He gets hired. The Web site pays you between $10,000 and $20,000.

This sounds too good to be true, but San Francisco startup Top Prospect is doing it right now for Silicon Valley tech jobs. The site opened to the public this week after a couple months of private beta testing, and right now there are more than 140 jobs with 47 companies available through the site, with total available recommendation fees of $1.5 million.

How can Top Prospect afford to pay such high fees? Despite high general unemployment, certain tech jobs are still very hard to fill. Top Prospect CEO Rotem Perelmuter explains that these are the kinds of fees companies pay contingency recruiters to fill these jobs today -- usually about 20% to 25% of the recruit's first year salary.

Top Prospect believes that friends and colleagues know more about who might be qualified for a particular position than some of these recruiters.

So how does Top Prospect prevent people from gaming the system or spamming it with unqualified friends?
  • To recommend somebody for a job, users have to sign in with a LinkedIn or Facebook profile. Once signed up, Top Prospect looks at information about the recommender -- particularly their job history and how many other "important" people they're connected to. Importance is measured by job title, number of connections, and other factors.
  • Top Prospect uses this information and machine learning technology to figure out whether a recommender knows what he's talking about, and whether a specific recommendation makes sense. If a prospect is obviously unqualified, Top Prospect rejects it immediately nad the hiring company never sees it.
  • Prospects are double-checked by an in-house recruiter to make sure they're qualified. Eventually, the company hopes the machine learning gets good enough so that the recruiter will only be called in for a few borderline cases.
  • Recommenders are weighted based on past performance. If a person recommends a bunch of unqualified friends who are rejected by Top Prospect or employers, future recommendations are discounted, and eventually ignored.

  • To protect privacy, only the recommender, the prospect, and the hiring company know about each recommendation.
Top Prospect has only been testing its service since November, but has already received high praise for its recommendations by collaboration software startup Asana, which was founded by a couple of ex-Facebookers. A number of interesting Bay Area startups and VCs are now advertising jobs on the site, including (anti)social picture-sharing service Path, online movie community and recommendation service Flixster, digital music marketing company TopSpin, and VC Andreessen Horowitz, which provided funding to Top Prospect. The most prominent company advertising on Top Prospect is Nielsen, but Top Prospect hopes that other big tech companies will come aboard.

Right now, the site is focused on the Bay Area and tech jobs, but if the concept proves itself, Top Prospect plans to expand quickly to other areas -- New York is an obvious second market -- and other industries like health care, finance, and energy. Executive recruiting is not likely -- Perelmuter admits that Top Prospect can't compete with personal networks of CEOs and high-end recruiters -- but just about any other sector with more job openings than qualified employees is open.

If the entire concept of paying cash for recommendations sounds a little bit familiar, it is: early last decade, H3.com tried something similar. But the company had a tough time providing qualified leads because social networks barely existed, so it couldn't tap into the massive wealth of available information about prospects' job histories and connections. H3.com is gone, but Top Prospect has acquired some of its patents -- good ammunition against imitators.

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