Stop Calling Social Analytics Intelligence

March 27, 2013
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Everyone is saying social analytics and monitoring tools are social intelligence, and this needs to stop in order for the social media industry to progress. But before we put this common misconception to bed, we need to understand the difference between social analytics and social intelligence, and where future value lies.


Social Media Analytics. 

Everyone is saying social analytics and monitoring tools are social intelligence, and this needs to stop in order for the social media industry to progress. But before we put this common misconception to bed, we need to understand the difference between social analytics and social intelligence, and where future value lies.


Social Media Analytics. 

Hootsuite, Visible Technology, Radian6, and other platforms are great providers of social media analytics and monitoring. They provide simple and effective ways of slicing and dicing the social firehose through search configurations. This is great if all you want to do is follow your company, competitors, and industries on social media– then gather sentiment, share of voice, and mention analysis. But what if you want to mine larger sets of social data in order to drive intelligence that can help shape your business, product development, or launch plans by taking into account data outside of your search? That is where social media intelligence comes into play. 

Social Media Intelligence.

This is not a new idea. It was first defined by Sir David Omand, Jamie Bartlett, and Carl Miller in a paper published in 2012 based off of the 2011 England riots. During the riot, police officers were able to analyze social media data sets in it’s entirety, including meta data associated with posts to better position and utilize their resources. So why can’t an everyday organization leverage social media to this degree? Well this was a fairy tale idea and didn’t exist until recent developments in the Big Data world with the introduction of Topological Data Analysis (TDA). The reason TDA was a breakthrough was because it allows for automatic discovery of insights, unlike other search or query-based models.

Ayasdi is an example of a platform that uses TDA and machine-learning algorithms to analyze large, high dimensional data sets. They have already driven breakthroughs in cancer research by analyzing a 12 year old data set and uncovering unseen connections that lead to a more effective cancer treatment. Now Ayasdi has been experimenting with inputting high dimensional social data into its system and seeing what connections can be found, and the results have been fantastic (click here to watch a TDA platform analyze Twitter social data). 

Imagine downloading mass amounts of public Twitter data from around the world, or purchasing it off of Gnip, and being able to automatically mine it to find consumer behaviors, population trends, economic indicators, and more. 
That is real social media intelligence. This has nothing to do with social analytics, but more about how you can use Ayasdi Iris Analysismass quantities of social data to drive business results. These patterns that are discovered through TDA have the ability to make your business smarter. Without seeing it first hand I would never believed it either, but this has the power to change the world as we know it by placing social media in the center.

The Future.

I too have been drinking the kool aid and thinking that social analytics is the best we can get, but it’s time we take the next step and demand more. Social tools today don’t offer this type of analysis, they are just serving you the same data in a different form. By using Big Data tools to analyze your social data at a deeper level you will be leading the industry and expanding how social is used within your organization.

So stop looking for intelligence through social analytics, and let the social data speak for itself. Let it take shape and create true social intelligence for your organization instead of you just sifting through social analytics on a hunch.