Services & Software

The Portable Personalization Project: Matchmine

Matchmine attempts to give you control of your own preferences data.

We gave Matchmine a small writeup from the DemoFall conference yesterday, but I wanted to dive into the concept here a little more. What Matchmine is trying to do is create a universal preferences system. The pitch is that instead of rating the movies and music and blogs you like on each site you go to that has ratings, you rate your preferences once, and then any future sites you go to can grab those prefs immediately to serve you recommendations that will be good for you.

By telling Matchmine what you like, you create a key that can be used by other sites.

The recommendations are created independently of any site's users, and thus can't be based on collaborative filtering, where you're matched with items based on what other users are buying or rating. Instead, Matchmine finds items for you based on a database of attributes attached to each property in its database. If you rate Western movies highly, it will find more of them for you. If you're partial to Oscar winners, it knows that, too. Of course, the more items you rate, the better your results should be.

The company plans to make money be selling its technology to content marketplaces, and it already has deals with some second-tier music and film sites like Fuzz, FilmCrave, and Peerflix.

There's a standalone recommendation application that connects you to Amazon and other stores to buy things.

These sites, though, already have their own databases of media as well as their own rating systems. Sites that support Matchmine will let their users import their preferences, but they don't, yet, export. So any work you've done on Peerflix, for example, to rate your favorite movies won't get exported to your Matchmine preferences set. And it's unlikely that the major commerce/rating sites, like Amazon and Netflix, will adopt technology that commoditizes what for them is a key service. I really don't think Amazon sees its recommendation engine as something it can outsource.

On the other hand, Matchmine can send transactions to any store it wants, including Amazon and Netflix, and pocket affiliate fees for doing so. The service's standalone recommendation engine does just that.

One of the things I don't get about Matchmine is that it stores all its preference data locally, on users' machines, in a background executable file that the user then authorizes applications to access. This lets users control their information, but it's a very un-Web concept: It's not portable and it sucks up resources on the PC. The service also makes a big deal about privacy, since it doesn't store any personal information with your preferences. But as soon as you import prefs into a commerce site, you'll be matched up. So I don't quite get that.

Matchmine is a noble experiment. The company is trying to take very personal information about users--their likes and dislikes--and give that data back to us for us to use and control as we wish. That's fantastic. It looks like it's going to be difficult to make it work as a business, though.