Now that I’ve managed a few different communities, I’m beginning to see a divide between two kinds of work that I do. One one hand, the individual tweets, updates, blogs and content-based work that I do ends up being a bit more creative – and definitely a lot harder to pin down rules for. I’m supposed to make great content, and reply sensitively to customers, and to sound authentic. To do this, I rely on a lot of common sense, with a few pretty well-established rules about what not to do.
On the other hand, I’m engaged in a data-driven project. I keep track of a handful of metrics that let me quantify causal and personal relationships, and I get a sense of what I’m doing well and not-so-well. It happens after I’ve already got an account and interactions. I have to start somewhere, and then I find out where to go next by looking at the metrics.
The difference between the liberal art of social media engagement and the empirical project of measuring what happens on social media is not a new one. TV writers are different from the people who rate at Nielsen. There are entirely different skill sets, but because everyone’s accountable to the bottom line, these two sides have to meet up. The writers must make something that’s more than good: they need to make something that can sell. Someone else is probably responsible for figuring out what that something is.
What has changed is that the person who writes and the person who figures out what to write about are now the same person. I have to manage what happens on twitter, and I have to measure what happens on twitter. I am the link between the data and the content, and that’s both super cool and very easy to forget. If you do remember, then you’ll end up getting feedback from your data that you would have otherwise ignored. Likewise, you’ll have the chance to make much more awesome content, and to see what makes it good. These activities can reinforce one another, so at every opportunity ask yourself: what does the data say? How can my content make a change in the data?