In our 2014 report on the state of social business, the single biggest factor associated with a company’s social business maturity was whether and how they collected and used data from and about their social business efforts. Yet I suspect that many companies’ approaches to measuring their social media efforts are wrong.
Standard data analysis techniques are often based in linear methods. These methods essentially try to determine whether a change in one variable is associated with a change in another — whether more of X leads to more of Y. For example, a company might seek to identify whether increased mentions of its brand in social media leads to higher sales or greater brand awareness. Managers are comfortable and familiar with this simple, direct line of thinking.
Social media environments, however, can be far more complex than these simple, linear relationships. Interactions on social media perhaps best understood as a complex adaptive system. These types of systems are often difficult to measure using traditional data analysis techniques, and exhibit four distinctive characteristics.
Social media may exhibit a “Goldilocks effect,” where more of X leads to more of Y up to a point — but when X is “just right”, adding more of it stops having an effect or begins to have a detrimental one.
For example, we studied retention rates in an online community and found that the community operated best when there were moderate levels of people joining and leaving. Too much turnover meant that the community never developed an identity or direction, but too little turnover meant that the community became too rigid and insulated from new ways of thinking. A moderate amount of turnover was “just right,” leading to the best outcomes.
The takeaway: It’s never as simple as you think it is. Managers must be wary of oversimplifying the effects in social media environments. More complex relationships may exist, which require more sophisticated thinking and measurement.
The impact of small changes on larger systems is often illustrated by the so-called Butterfly Effect, in which a butterfly flapping its wings in one part of the world sets a sequence of events in motion that leads to a hurricane in another via incremental effects.