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Text Analytics – An Ingredient, not a Solution

July 27, 2011 1 comment

Wikipedia has a short entry on “text analytics” http://en.wikipedia.org/wiki/Text_analytics where the length of the concept definition is eclipsed by the list of vendors selling products / solutions / tools that claim some type of text analytics capabilities.

After reading far too many vendor data sheets and whitepapers and reviewing all the fun #textanalytics twitter posts, it really boils down to “deep inspection of content” for some tuned business purpose.

There are those who claim to have broad platforms for text analytics and cast a (very) wide net across the multitude of potential business use-cases – threat and fraud to better search to clinical trials – but without a real “solution.”  (I define a “solution” as a product or platform with domain specific IP to address a business problem).

Truly the text analytics marketplace is nascent.  We’re seeing huge growth in content related to the topic, and searches about the topic.  You can see for yourself with Google Insights:   http://www.google.com/insights/search/#q=text%20analytics&cmpt=q

There are some vendors who are positioning their technologies as platforms for text analytics, however I expect they’ll struggle as customers try and understand if they’re selling a “dessert topping or floor wax.”

The true power, and value, of text analytics comes from leveraging the capabilities as ingredients in broader business solutions.  Text analytics alone won’t reduce insurance fraud, but it can be an extremely powerful addition to an insurance fraud solution which includes ECM, BPM and BI.

I expect over the next 2 years we’ll see a decline in the positioning of platforms and a marked increase in the positioning (and vendor success) of leveraging text analytics in real business solutions and enterprise applications.  The power of text analytics is real – but that power only becomes truly useful when delivered in context of a business problem with definable ROI.
This is, I believe, why “consumer insight” is so popular in the text analytics field.

It’s intuitively obvious that happy customers are better than unhappy.  What keeps me so interested in text analytics is the ingredient opportunities beyond consumer sentiment analytics.

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