According to Frost & Sullivan's recent survey, 2012 IT Decision Makers' View of the Enterprise Communications Evolution, almost half of respondents place high importance on having some type of social media strategy. And higher adoption levels among those placing greater importance on such strategies indicate that adoption can likely be driven by a better understanding of how social media information can be harnessed for specific business purposes.
Early enterprise efforts around social media have been focused on leveraging a brand's Twitter feeds and Facebook pages to increase customer engagement. Social media analytics tools can, for example, identify a business' most active and ardent followers or provide customer service and suggest opportunities for cross-selling and up-selling. But while most of the tools focused on engagement provide ways to increase outreach, they do little to deliver actionable business intelligence from the social media stream.
Now, businesses are looking for ways to leverage that collective intelligence to make better decisions and drive their products and services to market. At the same time, new technologies are changing how vendors and their customers approach Big Data, which defies the efficient data processing and management of relational databases--and which, when tapped, has the potential to radically alter how business gets done.
But the growing popularity of social media--and the user-created content that is constantly published in an online social environment--is creating the next Big Data challenge for enterprises. Social media contains useful information about customers, prospects and competitors, but surfacing that intelligence out of the millions of daily interactions requires a focused approach. The challenge is to find effective ways to tap into these massive unstructured data streams and leverage the information within them for tactical and strategic decision making--and not just one-off customer engagements.
Applying data mining to social media requires a new tactic: casting a very wide net while pulling out only the information relevant to the business or a specific user group. Social media data mining does not require that a particular user follow your company on Twitter or like it on Facebook to be relevant; if he is talking about the things that matter to your organization, his data stream matters. Deriving business and market intelligence requires that enterprises understand not just what their customers are saying about the organization, but also what non-customers are saying about the market in general--or the company and its competition.
For a closer look at what technology vendors are offering in this space--and what customers are doing with it--check out my colleague Michael Brandenburg's newly published Market Insight.
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