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The latest insights on community strategy, technology, and value by FeverBee’s founder, Richard Millington

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The Thermostat

Richard Millington
Richard Millington

Founder of FeverBee

The thermostat here in our room checks that the temperature stays below 21’c.

If it rises above 21’c, a signal is sent to the air conditioning unit which kicks in to life. 

The thermostat’s wax pellet is a simple device, the air conditioning unit is much more complex. 

Every discussion of community metrics focuses on the thermostat. We debate what to measure to see if the community is going well. We endlessly try to make a better thermostat when we need an air conditioner. 

We never talk about how we use those signals. If the community is doing better/worse than last month, what will you do differently? Do you just panic more? Or put in place a plan of action?

e.g. Should you invest more in staff if the community is doing well or if the community is doing badly? 

Most metrics, I suspect, are simply collected for our own vanity – or to show our bosses that we’re successful. If that’s the case, cherry pick the metrics that best support your case. 

In fact, the typical metrics we collect (number of members, amount of activity, cases resolved etc…) are only good as vanity metrics. They tell you if something is going right/wrong, but not why. You might get fired, you might get promoted, but you can’t use them to improve the community. 

That requires understanding the antecedent of those problems.

Is activity declining because less members are visiting, registering, or posting than before? Has the sense of community declined or have discussions become less relevant? Once you have these metrics you can allocate your time accordingly. 

Imagine if your thermostat told you the number of new visitors to your community was declining. That’s a signal to allocate more time to promotion. You can create entertaining stories and persuade bloggers/journalists to cover that – for example. There’s a clearly link between the signal and the action. 

There’s a very efficient decision tree you can create and that’s what we need here. We need far less discussion on the thermostat and far more discussion on how we use that data to help us build better communities. 

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