HASUG Meeting Notes: November 2011 (Social Media)

The 4th quarter 2011 HASUG meeting took place at Bristol-Myers Squibb in Wallingford, CT, on November 10th. Speakers included John Adams of Boehringer Ingelheim and David Kelly from Customer Intelligence at SAS Institute.

David Kelly presented SAS Institute’s Social Media Analytics software platform designed to enable companies to process large volumes of unstructured data from internal and external social media and to base business decisions on that data. His presentation, “The Power of Social Media Listening,” introduced the SAS Customer Intelligence organization at SAS, provided an engaging narrative of social media statistics (about 70% of YouTube and FaceBook activity come from outside the US, for example), portrayed the potential and the landscape of social media and outlined the data challenges (punctuation, spelling, segmentation, acronyms, industry and social media jargon) associated with analyzing the unstructured text data which comprises over 70% of social media data.

Kelly cited the infamous viral YouTube video posted by a previously obscure singer-songwriter who watched United Airlines cargo handlers break his expensive Taylor guitar as a social media example of negative PR which led to a loss of $180 million for United Airlines. Clearly, how corporations react to social media in real-time can have serious financial implications. Kelly also discussed the “4 Cs” of social media: Content, Context, Connections, and Conversations, and noted the importance of being able to identify key “influencers” (a concept which will be of interest to those acquainted with Malcolm Gladwell’s “Tipping Point”) and the origins of negative PR stories.

SAS’s solution for businesses looking to monitor and respond quickly to information about their brand floating around on social media sites is the SAS Social Media Analytics software platform. This platform crawls the web for industry or company-specific information (largely in the form of unstructured text data), capturing, cleaning, organizing, and analyzing that data as part of a customizable self-service application that allows your organization to generate real-time reports, including comparison reports (vs. competition), analysis of historical data and trend identification, “sentiment analysis” currently supported in 13 languages, and much more. See my conference paper for an example of the kind of text analysis you can do using Base SAS.