FTSE100 and social media

I was reading Sociagility report ‘Social Media in The City’ and I couldn’t help it: I needed to get the data and perform the analysis they suggest have been done.

Let me summarise it. Basically, by means of a proprietary methodology called PRINT™, a series of social media performance indicators are calculated for the FTSE 100 companies (the report refers to year 2012). Then, linkages between the social KPIs and the financial indicators are statistically assessed.

Five attributes contribute towards each organization’s PRINT Index™. They are:

Popularity – the extent to which each brand is attracting attention

Receptiveness – the extent to which each brand is seen to be actively listening to relevant comments or conversations

Interaction – the extent to which each brand is interacting with its communities

Network reach – the extent to which each brand’s community is being built using social media, beyond it’s immediate network

Trust – the extent to which the content and interaction of a brand is liked and recommended within its network

For a first approach I have used market capitalisation as at December 10th 2012, measuring the strength of the link between this financial fundamental and the different indicators Sociagility provides:

Sociagility scattergrams


The agency suggests that the best social indicator in terms of correlation is the Awareness Quotient (QA), so lets see:

Sociagility AQ vs Market Capitalisation

An OLS regression would indicate us that AQ explains 18.85% of the Market Capitalisation (beware!, as well indicated in the report, correlation doesn’t imply causality), with a positive relationship that tells us that for every point of AQ we should expect a market cap of between 7.59 and 106.77 millions (95% confidence interval), with an average effect of 57.18 millions per AQ point (p=2.43%).

Obviously, there is more in the report to be digested (recommended read!), and more interesting results that go in line with my research on social media ROI. It is not perfect information, since aggregated data loses valuable variation, but it is something to start with. Let’s have fun!