One of the really innovative things that the team has been working on, and that we showed at the in.Telligent conference, is something we’re calling Social Fingerprints. This is included in Harvest 2.0 which we’ll release in the next few weeks.
The concept is that each person in a community has their own unique contribution style or fingerprint that they they leave on a community. While finger prints from a variety of individuals may be similar they will almost always be unique. For example, here is mine:
I tend to skew heavily towards “Asker” meaning that I ask lots of questions or start lots of discussions.
Now compare this to Joe who is the program manager for Evolution who tends to skew more towards the contributor/answers side:
The fingerprint is built around how the user contributes in the community and their profile changes over time.
We think this is a pretty interesting way to think about how to categorize and classify groups of people too. Depending upon the type of community you are creating you would expect to have a fingerprint for the overall community type too. That is, a support community should look different than an enthusiast community. We’ll eventually tie this data into predictive profiling of users – so you know what types of users turn into high contributors, etc.
While this is only version 1.0 of our work in this area we’re going to be investing a lot of time and energy into helping customers use this kind of information to improve and measure.