Facebook, Pinterest, LinkedIn and Twitter are the hottest social media companies on today’s Web – and the data shared and searched on these social networks is highly valuable to organizations. But accumulating social media data presents challenges for marketers unprepared for the difficulties inherent in the process.

Colligent, Inc.,  Redmond, Wash., is a social network data collection, research and analysis company.  Colligent’s MeQ™ (Mutual Engagement Quotient™) system is a predictive audience targeting tool used for analyzing “affinities”—shared likings for comparable consumer items or brands that create a similarity of characteristics suggesting a relationship. These affinities can be revealed in online social network (e.g., Facebook, MySpace, etc.) activity.

Colligent CEO Sree Nagarajan estimates that Colligent is able to produce one trillion+ data points showing how consumers engage with brands.

Colligent’s ability to extract a trillion data points from Facebook to show how consumers engage with brands demonstrates just how complicated is the task of finding meaning in the social data tsunami.  The online community is generating massive amounts of information on a daily basis—according to Facebook, 30 billion pieces of content (Web links, news blogs, photos, etc.) are shared each month on the social network, with no signs of slowing.

While significant, the amount of information created by individuals themselves – writing documents, taking pictures, downloading music, etc. – is modest in comparison to the amount of information being created about them in the digital universe.  In fact, metadata (“data about data”) is growing faster even than the digital universe as a whole.

A person’s “digital shadow” grows continuously—even after, for example, a social network member has deactivated an account (ref. Facebook).

But this data is very difficult for marketing professionals and community managers to quantify in order to justify their often expensive efforts at contributing to company profitability.

Social Media Intelligence

So they turn to Social Media Intelligence—“the management and analysis of customer data from social sources, used to activate and recalibrate marketing or business programs,” according to Forrester Research.

They ask themselves if the insight that social media data analysis provides is generally suitable and reliable for determining and executing viable plans of action?  If not, why not?

While monitoring a company’s online presence in the social sphere is the foundation of real-time intelligence gathering, monitoring in and of itself is not actionable. For a company to realistically gain a competitive advantage in its space, the data must have meaning for decision makers who understand that the actions they’re taking in real-time are based on true and accurate knowledge.

If all the knowledge that’s available isn’t ready be interpreted and immediately put into useful action leveraging the results for competitive advantage and driving essential business decisions, then a company’s Social Intelligence gathering efforts can’t be effective in improving business performance.

Where social intelligence can be most productive and valuable is in helping companies develop the online content that distinguishes their brands and attracts consumers to their Web properties for engagement and conversion.

Part I: Social Intelligence—BI Meets Social Media Data

Part III: Social Intelligence Drives the Shaping of Online Content

Part IV: Social Intelligence—Content Curation a Key Filter