As someone who used to crunch numbers for a living, I know how much data and information matter. So at this time of the year, it's interesting to reflect on the content we produce to discover what's working and where. To that end, I've compiled a few stats that provide a degree of insight into the impact our content has inside social channels.
For the purposes of this exercise, I was less concerned with volume as in broad page view numbers. Instead, I concentrated on engagement-related metrics. There are many ways to think about this but I wanted to get a sense of social interactions outside of diginomica. We use Parse.ly as an analytics engine because it produces useful ways to slice and dice our data.
The subset I examined allows us to see not only the numbers related to social referrals but also those related to social interactions. This is what I discovered when viewing the figures from the point of view of broad categories we use.
This is kind of arbitrary in one sense because stories can easily span half a dozen categories. Nevertheless, the analysis provides us with insights into the content with which people are prepared to interact. So - without further ado, here's what I discovered regarding the top 10 categories. Inevitably, the categories end up as self-selecting to a degree on the basis of volume produced but that's not really the case. If anything, I'd argue that these tables provide an indication of what readers find most valuable.
As (I hope) you can see, and despite the fact, we see plenty of action on Twitter, LinkedIn was consistently our best referrer. Facebook? Often negligible. This confirms our theory that contrary to received wisdom, B2B people don't find a great of value on Facebook. That's not universally true but is the case most of the time.
Turning to interactions, we see a different pattern:
Our best guess at understanding this is to say the relatively small character limit on Twitter, combined with a much larger overall reach in that channel works to ensuring we achieve much better interactions relatively speaking.
When we dive deeper we find other things emerging. So for instance, this story, which was primarily categorized as an IoT related story drew the most referrals: Can IBM and Cisco make Rotterdam the smartest, IoT connected port in the world? Should we have done more in that topic area? Perhaps. On the other hand, this story, SAP extends HCM on premise support to 2030 – smart move or major mistake? drew the most interactions. In fairness, we know that most of the time, when we write about SAP we will see plenty of traffic, in part because we know at least some of that content is widely circulated inside SAP but also because we have a significant number of social connections to people with SAP experience.
Here's another wee snippet of information for you. When we consider the degree to which we achieve any level of either social referral or engagement, the numbers work out at the equivalent of roughly 10% of our overall traffic. That's not a huge number but it provides an insight into the impact of social channels that's worth exploring further. I've not bottomed out my thinking here so won't add any more commentary at this point.
My questions to readers are these: do you see similar patterns emerging in your chosen topic area(s)? How do you use insights of this kind to help deliver better content?