Now, we have received confirmation that the social media monitoring and analytics industry is heading rapidly toward maturity because IBM is getting into the game as well. We say this because IBM isn’t exactly on the leading edge of this type of service. As a result, if there is an official IBM product entry into the space then we are well beyond the “Do you think we should have this at our company?” phase.
IBM is introducing a new social media monitoring tool, one that it says will measure consumer sentiment from data gathered on Twitter, blogs and other web services and networks.
The software, called the SPSS Modeler data mining and text analytics workbench, will use natural language processing (NLP) to analyze everything from product names and industry jargon to slang and emoticons, and it’s already being used by some pretty big businesses.
Uh oh, geek alert! Anytime the term NLP (natural language processing) is used we know we have stepped into the land of engineers, scientists, academics and good ol’ fashioned ‘smarty pants’ types. We also know that there is a great likelihood that the tool itself may be a little, well, technical in its delivery. Take a look at the screen shot below and get an idea. If you can’t read it, there are terms like distribution, churn and predictor importance. Sounds important.
Mashable’s description captures this as well.
SPSS Modeler data mining and text analytics workbench is a high-grade product and might be both too sophisticated and too expensive for the average small business. The interface itself is hardly what we’d call intuitive or user-friendly. But for larger enterprises that need robust technologies and can’t risk entrusting data collection to a startup web app, IBM’s software might very well provide the features they need.
So the online monitoring industry moves on into maturity. IBM’s entry into this space evokes the same feeling one gets when they discover that their grandparents started Facebook pages. It’s at that point that you figure everyone knows about it now.
All kidding aside though, most attempts at any type of automated sentiment analysis in monitoring tools is more marketing hype than product reality. If IBM could prove that their tool does something to move the needle in this area then maybe there is something to this. In the area of automated sentiment analysis I still think that all claims to that effect should be viewed as guilty of over-hyped ‘til proven otherwise.