How can data interpretation fuel storytelling?

As a community manager I get to see the back and front end of a lot of audience platforms. Seeing the content that resonates on a community feed and then ‘popping the hood’ to see how the content actually measures up against other posts and types of interactions. Simply gaining ‘likes’ is one thing but receiving comparable measures of ‘comments’ and ‘shares’ can potentially tell us that the community is not only responding to the post but also provoking a response from their friends too. Essentially different aspects of insight across audience awareness and content interaction can help anyone, be it brand manager, marketer or simple data analyst. I like to break these aspects into story-forming interpretations.

Essentially;

  • Pattern forms narrative
  • Behaviour forms character
  • Measure forms personality

https://twitter.com/jacqui/status/676339199994384384

Pattern forms narrative.

Finding patterns in behaviour that relate to other patterns (being a pattern in itself) can help us structure an idea of narrative. If we see that, at a basic level, people visit your website after a specifically popular social post we can attribute a level of value to that post. But not only the post itself was a influencing factor; what else was happening in your community, what time of hour/day/week did the post go out? Who were the interactions made by? All these factors could hold pivotal insight into why how we can begin to see nuances in narrative within a community.

Behaviour forms character

When looking at how specific communities and audiences behave we must consider not only motivations but also habitual activity. These may be one and the same but in the case of certain habitual engagers for example social ‘gamers’ (as in individuals on social media who only interact with competitions to win a prize). This kind of habitual behaviour might be disregarded. However, in the case of, say, how Facebook categorises behaviour activity, we can consider behaviours like posting activity; photo sharing or event page creation. In this way behaviour can be truly quantified by habitual activity. In retrospect, knowing how your community has behaved in past interactions and cross referencing that with your knowledge of demographic segments your community is made up of can result in another dimension of character. For example one of the communities we manage is made up of a combination of UK-wide large and small retailers combined with end consumers of more specific services like online gaming, parcel delivery and general utility customers. We can assume that each segment will not necessarily behave and interact with content the same way as each other. Even the smaller and larger retailers behave differently according to different subject matter.

Measure forms personality

Essentially the measuring of these behaviour levels and narrative forming patterns can form a solid understanding of the personality of your community. This, of course, can be a constantly evolving aspect of any digital community which requires regular snapshots of the metrics and changes over time to properly understand where your community ‘is at’ in terms of profile character at any one point in time. From this we can trace the levels of behaviour, preferential data, popular content or subject matter and profile statistics i.e. follower level, influence, activity rate, active channels. All this can form batched averages of the personality of your community.

The story of the connected network

Being able to trace a path between interactions and community relationships has been one of the most revealing forms of narrative in our experience of community management. Knowing who knows who and why, has been crucial to informing all the above aspects of storytelling. Having previously managed a global community of music fans which comprised of event creators, volunteers, musicians, artists and music professionals; we saw vast insight into how this global network of people with a common interest can interact. Being able to trace success stories of (now) major label musicians from small ‘cutting teeth’ gigs, through to how their biggest fans (not just friends and family) helped champion their popular demand (via social sharing) and expose them to incrementally better management and label opportunities (evident via private Facebook groups). To an eventual discovery via a viral audio post from a major label boss and hence a signing and resulting album release and world tour. All these factors are all, measurable on social networks, either public or private, direct or indirect, but all attribute to the narrative of their success. All evident through the digital patterns in behaviour and personality of their community.

In a nutshell, know your community through measurable behaviour and identifying narrative through insight and pattern has been key to telling the story. See what people are saying about the emerging trend of data storytelling and how this is useful for modern journalists and marketers.

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