Most social media strategies are today confined around the quantitative measures of fans and followers and fan engagement. Often getting engagement of fans is a hit and miss exercise and social media strategy is a lot of trial and error even today. However, by following an approach that looks only at the bilateral conversations between brands and fans, we are selling our social media strategy way too short. The question arises then is what can we do better and how can we look beyond the obvious to generate insights that are based on reliable and actionable data?

Another version of marketing myopia, or rather social marketing myopia, is the reluctance to look at our fans and followers outside the context of our brand and category. We often forget that our fans are constantly interacting with their connections outside of the context of our brand. How often do we analyse the conversations our fans are having on social media? What gets my fans talking? What incites passion? What trends work for them and what trends leave them cold? Can we listen to the overall social conversations of our fans and form sub-groups of fans within our follower base based on their psychographics and attitude? This requires sophisticated listening and multivariate analysis tools. However this investment can yield invaluable socio-cultural insights into our fan following – their interests, behaviour, spending patterns, popular subjects and conversations (trends) and also the sort of keywords that trigger responses.

Another source of valuable insight is the ability to analyse not just our fans but also their networks. This gives us the ability to generate data around cohort groups and build even more sophisticated profiles. Looking at networks can also lead to a deeper understanding of when conversations ‘spike’ or peak and what triggers these peaks. This also gives a great insight into what terminology – phrases or words – elicit a response and of what intensity? All of this obviously means that one is analysing large quantities of largely unstructured data from a plethora of social sources. This is ‘big data’ in the true sense of the word – massive, unstructured and heuristic. Making sense of this data requires advanced analytical tools.

The last leg of data driven social media strategy is to create the stimulus – based on the insights that one has got from the first two pieces of analysis. Different groups can be sent different stimuli and the response can be monitored and calibrated in real time. Keywords that trigger sub-optimal responses can be changed and the stimulus can be repackaged with keywords that are likely to get a response from the recipients. The critical thing is that one is not shooting in the dark but basing the stimulus based on fairly robust data driven customer profiles.

There is obviously some way to go before these sophisticated analytics become common currency in devising social media strategies that are based on data and that really work. However the best time to start with this approach is now in order to steal a social media edge over competition.

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