Measuring Community Velocity

When you are involved in a community you can really get a sense of its health. You know when it is active and you know when it is in decline. Think about the social networks that you use, think through the amount of time that you spend using the site/application. Multiply that out by the number of friends or colleagues that you engage with using it … and then think about the number of circular, “viral” type elements that feed, sustain and grow the membership. How many are you involved with, and how active?

Now, it is easy to sense a velocity of engagement, but what is the evidence for this “sense” — after all, one of the challenges of social media is measurement. Where and how do we start?

Well, it seems that Rachel Happe has given this a great deal of thought and come up with a metric that, on the surface, looks pretty good. Here is what Rachel suggests as input and outcome:

The inputs:

  • Total members for a given month
  • Total active members for a month
  • Total posts (this can be a blog post, a wiki post, a discussion item, a link) for a month
  • Total addressable market (how many members would you have if everyone was in the community – this will be a rough estimate)

The Community Velocity Metric:

  • ((% of active members * # posts/per member/period) + total members ) / TAM

Now, Rachel freely admits that the total addressable market may be very large (in the case of a brand community), but a good guess will yield a CVM of around 0.01 for new communities and 0.03-0.04 for the more mature community.

But think about this in action. What would happen if we applied this to Twitter or some of its new competitors like Plurk or even older stalwarts like Pownce. I whether the CVM can help us predict a community (or an application) with a growth trajectory — or one experiencing the first pangs of disaster. Perhaps we may know sooner rather than later!

One thought on “Measuring Community Velocity

  1. Hi Gavin –
    Thanks for the post – this is exactly the intent of this metric…to track health over time and compare against other communities of similar types/sizes.
    It’s not perfect…but to be widely usable it also has to be fairly simple so that does leave out a lot but hopefully provides a baseline index.
    Cheers –

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