Data-Driven Community Management
A well-managed community has the power to drive business growth but there are a lot of strategic and tactical decisions to make when building and managing a community. If you’re a “people person” your intuition has probably served you well in guiding many of those decisions. However, if you are not using data-driven techniques to back up your instincts, can you prove you are making good decisions for your community?
Data-driven means guiding decisions using the good old-fashioned scientific method we learned in the fifth grade:
Ask a question.
Collect relevant data.
Turn the data into knowledge.
Revise your plan incorporating your new knowledge.
Repeat.
We all know marketing is very data-driven and there are dozens of data collection and analysis tools available for social media marketing (SMM) managers. Using these tools, SMM managers can track the outcome of specific actions. For instance, a marketing team might wonder if they can increase audience engagement by scheduling posts. Using a service like Buffer to manage delivery of posts across the course of a day, they can use basic SMM tools to analyze the collected click data after running a test. Iterating on this simple, data-driven technique allows them to develop an optimized schedule for posts and reap the rewards of being “data-driven”.
This simple example is just SMM 101, right? And we understand community building is much more than counting clicks and page views. After all, unlike social media marketing, community management is about:
Knowing individuals in a ‘community’ not the aggregated responses of an SMM ‘audience’
Understanding ‘relationships’ between community members rather than just collecting shallow statistics about audience ‘reach’
Fostering ‘mutual engagement’ instead of blasting ‘one-way’ messages to people
Building community through ‘interactions’ versus monitoring audiences by ‘observing’ actions
Can we apply data-driven methodologies to community management to supplement our instincts? Do you have the tools you need? As Ligaya Tichy points out:
… with certain terminology come expectations and with expectations come metrics, and we need to be sure we’re measuring against the right things… or you might as well just empty out your desk.
Follower counts, keywords, and page views may be necessary, but not sufficient, to understanding community behaviors. We are social creatures, so when dealing with people we rely on our instincts. You spend lots of time with your community so you know the players and the ebbs and flows of conversations. Our “gut” is a powerful thing, especially in understanding people and relationships, but there are two big pitfalls.
The first pitfall is not recognizing that the size of our online communities often exceeds our ability to intuitively process information from a community. Robin Dunbar, a social scientist, theorized the maximum size of a physical world community we can comprehend is between 100-230 people. When our online communities grow into the thousands, even tens of thousands of members, we lose the ability to manage our communities using just our instincts.
The second pitfall to relying on our “gut feel” is our brains specialize in pattern recognition and event processing. We make amazing intuitive leaps given little information because that’s what kept our ancestors from being eaten by tigers. The problem is that we can make amazing intuitive leaps given very little information… and often these “epiphanies” wrong! Apophenia is when our brain creates non-existent patterns, correlations, and causation. Even in smaller online communities, the deluge of information we must cope with can easily let us fall into the the trap of incorrectly interpreting data into false patterns.
Making data-driven decisions about your community doesn’t mean being less human or authentic. Indeed, integrating data-driven tools designed specifically for community managers into your decision-making processes means you can back up your “gut feel” with solid information. These specialized tools will allow you to track important metrics like member tie strength and lifetime, analyze conversations and provide novel insights about larger communities. And, just as important, a data-driven community manager is now able to quantify and communicate their achievements to the rest of the team.
