The explosion of social media like blogs, Twitter and Facebook has made it tough for enterprises to keep track of all the data floating around on the Web that could provide valuable business insights. But IBM thinks it has an answer with its SPSS predictive analytics software. Big Blue has just released an update to its SPSS product, promising businesses better insights into things like customer and employee sentiment. The new version comes equipped with 180 different vertical taxonomies to ensure that businesses in various sectors are getting an accurate picture of what people are saying about them around the Web. Datamation takes a look at IBM’s update to the SPSS predictive analytics software.
IBM this week unveiled the latest update to its SPSS predictive analytics software, giving enterprise customers the ability to monitor and analyze social media data that’s constantly being updated and shared via Facebook, Twitter, RSS feeds, blogs and wikis.
IBM SPSS Modeler promises to monitor changes in customer and employee sentiments, uncover deeper insights and predict the key factors that businesses need to grow their sales, retain top performers and quickly react to subtle changes in their industries or product categories.
The software’s text analytics component identifies emoticons that are often included in a blog entry or tweet and can discern between different meanings or references for the same word. It also understands slang terminology and abbreviations so users get an accurate understanding of what people are saying about their companies and products in the vernacular that tweeters and bloggers use.
