Mixtent Launches to Crack Reputation with Controlled Anonymous Commentary

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Another Day, Another Desk-Mounted Rocket Launcher

I’ve talked to a dozen startups in the last month who are trying again to crack the tricky problem of reducing who you are personally and professionally to a reputation score that can’t be gamed and isn’t just a outlet for trolls and haters. I’m not convinced it can be done, as I argued with Klout’s Joe Fernandez, and beyond that I’m not convinced it should be done. Social media has already given plenty of people an unhealthy obsession with measuring their self-worth in friends, followers and retweets. Anyone who faces a mob of angry commenters for every word they blog knows the truth: The Internet is too big to take even a large number of haters too seriously. Even hundreds of comments saying “YOUR AN IDITO!” are still just a tiny angry minority, who just wants to be heard.

But there are some instances where getting closer to capturing reputation online could help solve real world problems, and most are in the professional sphere. After all, I don’t have to care what a guy on the street thinks about me, but if that guy on the street is friends with the hiring manager for my dream job, suddenly his opinion becomes hugely relevant to my life. The workplace is the one place where people’s opinions of you actually matter. I’m actually writing about two new companies today that I think get closer to solving this problem than LinkedIn has, and might be worth the foray into the seedy world of inviting your peers to judge you. The first is Mixtent.

Mixtent is founded by a Venezuelan-born entrepreneur named Jonathan Gheller, who relocated to Silicon Valley after selling his second company. His goal is to make the labor market slightly more efficient on a national level, and fully expects it to take a decade or more to get there. This is not a guy out to flip a company, and he’s already spent years honing Mixtent’s reputation algorithms. (The company has allegedly raised money, but Gheller adamantly refused to give me any information on who it was from and how much, saying he thinks there’s too much attention in the Valley paid to who is backing you, not the product itself. I argued not disclosing it only made it more of an issue. Take that bit of weirdness however you wish.)

Here’s how the service works: You sign up for Mixtent, which is an app on top of your LinkedIn profile. Mixtent scrubs your profile to parse all kinds of information about you, such as how well you know certain contacts and who are your most direct peers. Then it polls other Mixtent users you know on specific job-related questions about you and those peers. Your peers can vote on you anonymously, so you don’t have the LinkedIn issue where people glad-hand recommendations for one another, but there is no way to enter text so the site doesn’t evolve in the defamation morass of Honestly either. Also, unlike Honestly (born as Unvarnished), you have to opt-in to Mixtent, and if you don’t like the results, you can opt out. I think that’s essential to any reputation system. If you build a good enough product, people will use it without being bullied or forced into it.

Mixtent gives you your own dashboard that ranks you against all your peers, but also provides some useful information, like whether superiors tend to like you better than peers, or whether people who work for you are the ones who find you insufferable. I find the idea of an absolute professional rank silly, but the latter is potentially constructive criticism that you could act on. The eventual hope is that Mixtent learns enough about you by the way you vote and others vote about you, that it knows what kind of employee you are and can tailor job recommendations for you, not just your resume. For instance, it could know if you are too autonomous to work well under a micro-managing executive or too thin skinned to work at TechCrunch in certain office environments.

Whether Mixtent gets there is a huge unknown but it could represent another leap up in the ability to hire online, the way LinkedIn used real world relationships and links between people to dramatically leapfrog job boards like Monster. Labor is such an inefficient market and a problem companies will pay handsomely to solve, so you only have to make things slightly better to build a decent-sized company.

What concerns me about Mixtent isn’t the gargantuan scope and challenge of the problem it is trying to solve. It’s that it’s designing a solution for a labor market that may be more polarized than ever before. On one hand there’s Silicon Valley– where an intense war on talent is the single biggest challenge every tech company faces whether its Google, Facebook or a no-name startup. There are simply not enough people to fill certain jobs in the Valley, and salaries and golden-handcuffs are getting to insane levels. Then you have the real America, where a large number of out-of-work people just can’t find jobs anywhere. Those are two wildly different problems of supply and demand. The former, could be helped by a site like Mixtent, especially since programmer jobs are more quantifiable. You can’t fake an ability to code.

But the latter isn’t a problem of inefficiency– it’s a deeper problem of a disconnect between the jobs that are empty and the skills people have. Mixtent isn’t going to solve that. My advice for Mixtent would be to focus on the problem it can solve, that it deeply understands as a startup based in Silicon Valley first, and then try to broaden to other industries.

And even in the Valley, I’m not sure all professions lend themselves to this kind of comparable voting method. For instance, only an entrepreneur whose business has hit the fan can truly judge how good a venture capitalist on his board is at his or her job, and that’s not a big enough sample size for most VCs. Ditto personal assistants– one of the hardest positions to hire for. Similarly, I’d never sign up for Mixtent, because I’d argue sources are the better barometer for how well I do my job, not reporters at other publications who have no idea how hard I may work to break a story, or other times when a scoop just falls in my lap. And even with sources, if a reporter is doing their job well, there should be a healthy amount of hate for them. Ditto anyone in sales. I’m not convinced the algorithms can parse nuances like that.

Still, I think people are hungry enough for self-metrics, they’ll flock to the site, and Mixtent’s future will be interesting to watch. It may come one step closer to solving reputation online and applying it to an actual problem, without giving another megaphone to haters.

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