As so often happens in life, I have gotten the job of fixing something that I was complaining about. Specifically, I’ve been asked to run the Marketing panel at the Text Analytics Summit in Newton, MA, June 12-13. In connection with this, organizer Ravi Virpal has asked me to come up with three major points or themes I feel we should address.
I hope to be proved wrong, but I think the Text Analytics Summits going forward will be a waste of time and money. The model the first two years was the same, with key features being:
Most of the attendees are vendors, and the ones I talk with almost uniformly agree they didn’t learn much, and they didn’t meet many prospects either.
If you’re a user or prospect, you can do as well inviting vendors to make sales pitches to you, and eventually calling references. If you’re a vendor, it’s a great place to socialize with your buddies from other firms, but that’s about it. If you’re press or analyst — well, it’s an easy drive for me in Boston, and I’m really focused on this subject area, so I’ve been attending. But almost no other press or analysts went, and I honestly can’t blame them for staying away.
Could this change? Yes. But in my discussions with the organizers, I’ve gotten zero reason to think that it will.
Another Text Analytics/Mining Summit, another occasion to discuss text mining market numbers. Except — it’s really hard to get any specifics. Before writing this post, I decided to web search on text mining market to see if anybody had posted anything about its size or growth. The first and pretty much only relevant hit I could find was my own blog post of a year ago, reproduced below. Oh dear.
While at the Text Analystics Summit, I came increasingly to suspect that two technologies – both of which I’ve put considerable research into recently — are very synergistic with each other:
One noteworthy aspect of the Text Analytics Summit is the French presence. France is generally inept in the software industry, but the text mining business is a clear exception. Temis is a French company. SPSS’s text mining operation (which was Lexiquest), is part French, part English, and run by a Frenchman. Teragram was founded by French guys. For variety, clustering company Semio was founded by a French semiotics professor, and nStein’s managers are a bunch of Quebecois.
Two of the clearest and most charismatic speakers in the text mining business are Attensity cofounders Todd Wakefield and David Bean. Last year, Todd’s Text Mining Summit speech gave an excellent overview of the various application areas in which text mining was being adopted; vestiges of that material may be found in a blog post I made at the time, and on Attensity’s web site. This time, David’s Text Analytics Summit speech was basically a pitch for Attensity’s latest product release – and it was a pitch well worth hearing.
Terry McFadden of Procter & Gamble made a number of interesting points in his Text Analytics Summit talk, in the area of how to build and “amass” (his word) lexicons. Above all, I’m thrilled that he recognized the necessity of amassing lexicography that can be reused from one app to the next. Beyond that, specific comments and tips included:
One thing that didn’t go so well at the Text Analytics Summit was the marketing panel. Indeed, when we wracked our brains afterward, Mary Crissey (who was on the panel) and I could only think of a single observation that was actually made about marketing. Namely, she referred to a core truth of marketing: Just selling features doesn’t work (nobody cares). Just selling benefits doesn’t work (you’re not differentiated). What you have to do is sell the connection between your features and desirable benefits.
So I’m going to try to gather some useful observations on marketing here, filling the gap that the panel left. Key questions I’d love input on include:
1. Which feature-benefit connections do you see customers easily accepting?
2. Which feature-benefit connections is it harder to get them to believe?
3. How are customers defining text analytics market segments?
4. What do they see as the key issues in each segement?
5. Which application areas are showing growth even beyond that of the market overall?
I’m particularly interested in comments from the larger vendors that are selling into multiple parts of the text mining and text analytics market. But everybody else’s input would be warmly appreciated too.
The comment thread to this post is open for business!
Thursday morning at the Text Analytics Summit featured, among other things, one excellent panel, a couple of lively and interesting presentations, and the usual tedious discussion of “What do we call this technology area anyway?” Lots of airtime went to industry stars such as Olivier Jouve (SPSS), Todd Wakefield (Attensity), Ramana Rao (Inxight), and Mary Crissey (SAS). There also was a gratifying repetition from the front of the room of the statement “Curt is right”, so as of when I’m writing these notes (midday) I’m happy, even if Ramana somehow neglected to join that chorus …
Repeated themes and messages included:
I’ve only slept one night in the past three, so I’ll stop here and blog more about the conference later.
The Text Analytics Summit folks have created a page where you can download a bunch of whitepapers. Most of those are tripe, of course, but I’m finding some of them interesting. The first few Megaputer ones I looked at seemed to have non-obvious application stories. The two SPSS ones actually called “Case Study” are worth a quick glance. And the ones from Lexalytics and Intellisophic definitely seem worthy of more thought and/or research.
Edit: Also possibly worth a look on that page is a Henry Morris opus for ClearForest called “Putting the Why in BI.”
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