One of the burning questions that keeps us awake at night, is “why does one campaign or one piece of content actually work, and another does not, when the intent and concept were very similar?” As strategists, analysts or community managers, we often think we know the answer, but it is mostly just guess work. We don’t have the technology or timely data, or perhaps even skills, to really dive into the detail. So the scrmhub.com team have been focusing on how could we actually track the data, interpret it, and visualise it, so our users can truly understand the answer, and then obviously replicate the success. The key is that the solution has to be powerful, easy to understand as we are all time poor, and quick to turn actions into an incremental improvement.
In researching the topic, and thinking about our own solution, we discovered that the clever folks at BuzzFeed have been thinking the same way. They have been working on doing deep data modelling to understand “virality”.
With over 200M monthly users, they have been focusing on the tree structure of network diffusion across social. Not just big numbers, but actual insight into who does what, to generate the results around amplification. The reality is that most amplification ends in a single transaction, but a small percentage of the initial engagement is by users, who truly have an impact. Someone injects the content into a network which is positive about the topic, and a whole branch grows and drives real buzz. If you take it one step further, you may discover that this single engagement into a network, drove all conversion and all the ROI. The extension of this thinking is that if you could replicate that one single connection with a user, then you would achieve the same real outcome, as the result of the last activity item, without all the other amplification.
If you could replicate the same single transaction with similar multiple individuals, because you know what they look like, then you could exponentially improve the result of the last activity item. The answer is in the data, but the tools we use must make it easy for the user to understand and put into action.
I know that sounds pretty geeky, but it is actually a burning question. It also goes to the heart of the objective. Is lots of engagement really valuable, in and of itself. Generally no, but engagement that delivers conversion and ROI, now that is a different matter. If we can track that down and replicate it, and bring more of these real conversion driving individuals into our initial or extended audience, then we can exponentially increase our outcomes.
This has lead us to find solutions to accurate on-scale machine based sentiment measurement, differentiation of sponsored vs organic amplification and influencer effectiveness measurement, which have had positive spins offs for other areas of our product, and the whole team is excited to share some of these with our users, as we move towards solving the burning question I posed earlier.