Thanks to ad:tech for publishing this first
I first learned about Mixtent in mid February, and was fascinated by both the notion of collective reputation measurement and the role it could play in making better hiring decisions. Let’s face it, making the decision to hire people is always a bit of a crap shoot. You can check references but rare is the person that cannot find three schmucks to vouch for them. Further, the fluid nature of job roles in the modern organization means that the same job title can require one set of skills in one company, and quite a different set in another.
We all know that hiring and retaining great staff are huge challenges on both the agency and brand sides. I am going to use the role of Media Supervisor as an example of why deep reputation information can be essential to making better choices. One assignment might require intimate knowledge of the bleeding edge, another an extraordinary mentoring ability, and the third the ability to build a stronger relationship with a client. We none of us are strong at everything.
What Mixtent does is uses your personal Linked In network, and a binary either or rating system to provide a picture of an individual based upon the opinions of people that they are connected to.
You join Mixtent by connecting it to your LinkedIn profile. From there, the platform defines a range of skills connected to your experience, and has the community rate you versus other connections on those skills.
In turn, you get to rate people you know on their experience sets. As I mentioned earlier, the ratings system is binary. Would you rather work with person A or person B on a project requiring the given skill set?
The platform gathers all of the ratings of all of the people and gives you a percentile rank versus others with the same skill sets. Your percentile rank is only calculated AFTER you have received 20 ratings, which is designed to limit the impact of being flamed by an individual you are connected to. And to give the data genuine validity.
How will this be useful in hiring and management decisions? Well, for a start, it gives you a more quantitatively valid view of an individual’s strengths. It’ll help you decide whether candidate A or candidate B might be more appropriate for that Media Supe assignment that requires strong managerial skills. Because you won’t be relying on a few interviews and self-selected references.
BTW, your ratings of individuals are kept private – that’s another inherent strength of the system requiring more than 20 votes before it calculates your percentile rank. That way you can be honest without fear of repercussions.
This is a new service, and for now only your connections can see your rankings. Additionally, if you see your ratings and dislike the answers, you can opt right out. Tech Crunch said that this is important to building a successful professional reputation platform. In their words:
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.
I can only guess where Mixtent is going. But I think the model is well designed, and the information very valuable. It’ll become even more valuable as the ranking algorithms get more and more accurate. Keep an eye out for this team – I think they are on to something very valuable.