*This is although I’ve spoken at four prior versions of the event, and responded to their request for free consulting as recently as this year.

OK, that might have been personal in some way — but Nick Patience tweets a very similar story. Even Seth himself tweets that

They have a business model that does not apply well to the IT conference space.

The Text Analytics Summit has been troubled for years, but evidently things have gotten worse.

This is more than an incidental problem. Interest in text data is exploding, and marketplace confusing about text analytic technology abounds. More clarity is needed, but too few folks have found an economic model for providing it. (The industry shares some of the blame for that.) I’m glad Seth is doing other conference work — notably on sentiment analysis — but yet more is needed.

If I get into the conference business — and it seems natural that I would — I’ll try to help fill the gap. But if somebody else beats me to the punch, more power to you, and please let me know how I can help.

1. Web search

2. Public-facing site search

3. Enterprise search and knowledge management

4. Custom publishing

5. Text mining and extraction

Three are more standalone:

6. Spam filtering

7. Voice recognition

8. Machine translation

This list comes from a talk I gave Monday at the Text Analytics Summit called The Text Analytics Marketplace: Competitive landscape and trends. In half an hour, I covered the first five areas (in Sue Feldman’s word, at a “gallop”). The slide deck has been uploaded to the link below. I plan to break out the material from the talk into a series of blog posts over the next few (or perhaps not-so-few) weeks.

Slides:

• The Text Analytics Marketplace: Competitive landscape and trends

Other posts based on those slides:

• Three specialized markets for text analytics (based on Slide 2)
• 6 trends that could shake up the text analytics market (based on Slide 19)
• Why search technologies are going to recombine (in A World of Bytes, based on Slide 19)
  

That is, of course, hugely more than any of the independents (e.g. Attensity and Clarabridge) have. And it’s focused on marketing-oriented apps — especially Voice of the Customer — just as those vendors are. Even so, they report rarely seeing SPSS, and SPSS agrees with that assessment.

The obvious explanation — which Olivier does not dispute — is that Text Mining For Clementine sales are focused on Clementine data mining users. But that raises an interesting follow-up — how much data mining are these users really doing on text data? Attensity and Clarabridge customers do little true data mining, but Olivier asserts that SPSS customers do quite a bit — predictive modeling, real-time scoring, and the whole enchilada.

By the way, Olivier actually no longer runs SPSS’ text mining business. He’s moved to Chicago as VP of Corporate Development, focused on acquisitions. Coincidentally, he has a glum view of the prospects for independent text analytics companies, and believes the best course for them is to be acquired.

Beyond that, Alessandro denies all the rumors that have grown out of TEMIS being hard to reach recently. He reports that pharma is still TEMIS’s big market, but stresses that this covers a range of apps, from research to Voice of the Market. I do get the sense that TEMIS’s sentiment extraction capabilities are less sophisticated than some of the other vendors’ — but the other vendors I’m thinking of are pretty focused on English, SPSS aside. If you need sentiment analysis in non-English languages — e.g., French or Italian — TEMIS should definitely be on your vendor shortlist.

Lexalytics’ main business is OEMing sentiment extraction, e.g. to the many blog-analysis/reputation-management (i.e., Voice of the Market) companies that recently started up and in some cases have been bought by big market analysis firms. Lexalytics can and sometimes does extract the more basic stuff as well, but sentiment analysis is the heart of its business. A partial customer list can be found on the Lexalytics site. Lexalytics extracts in the English language only.

One feature Lexalytics is proud of is that it doesn’t just assess sentiment from a phrase; it also gives a confidence (“evidence”) weighting. In such a fuzzy area as sentiment, I think that’s a good idea.

Lexalytics has a demo site, PoliticalTrends.info. The links on the left show some of the charts and reports they offer. But the bar charts in the middle inadvertently show the limitations of an approach that overweights some kinds of linguistic analysis at the expense of others. As I write this, the top 5 “Breaking themes in the last 3 days” are

• last week
• court decision
• web site
• nuclear program
• front page

I think that particular part of the app might work better if a little more restriction were placed on what is or isn’t counted as a “theme.”

*In reality, the bar opened early, and I took a Sam Adams into the roundtable room.

Now, it’s possible this reflected a certain vendor bias. Most of the show’s attendees are either vendors or users whose attendance the vendors pay for, and many of the rest are prospects the vendors encourage to come. The show’s program is also heavily influenced by what the vendors think is important. Still, this is confirming evidence that the text mining industry’s center of gravity has shifted emphatically to the CRM area.

Text Analytics News exclusive white paper, “Text Technologies in the Mainstream” by Seth Grimes, President, Alta Plana Corp.

As Text Analytics truly comes of age, we are witnessing the transition of text technologies from the established and still hugely successful life-sciences research and intelligence analysts into the IT mainstream in business applications such as CRM, voice of the customer, social media analysis, competitive intelligence, E-discovery and financial analysis, transforming business intelligence across a diverse range of industries.

Working with Text Analytics News, the folks responsible for the highly successful Text Analytics Summits, industry analyst and summit chair-person Seth Grimes — President of Alta Plana Corp. — has authored a groundbreaking white paper entitled “Text Technologies in the Mainstream”. It provides a comprehensive and up to date look at the industry today, analyzing the transition of text technologies into the IT mainstream and what that means for your business. In particular, it covers:

-VOICE OF THE CUSTOMER

-MEDIA AND PUBLISHING

-E-DISCOVERY AND LEGAL AND FINANCIAL COMPLIANCE

-BI, AND PREDICTIVE ANALYTICS

-HARNESSING NATURAL LANGUAGE

-TEXT ANALYTICS AS A SERVICE

-MARKET OUTLOOK, CONSOLIDATION

-EMERGENCE

This whitepaper is a must read for anyone who’s part of this exciting industry, from end users, to analysts, to solution providers and even to those just starting to look at Text Analytics.

To download your free copy now simply click on this link: http://www.textanalyticsnews.com/4thannual08/whitepapers.shtml

For further information please contact josh@textanalyticsnews.com

That’s pretty typical for First Conferences marketing. (And I hope they’ll edit that page after they read this …)

If the Video Search Summit is anything like the four Text Analytics Summits First Conferences has organized to date, it will be a great venue for technology vendor executives to chat with each other, untroubled by interruptions from customers* or prospects.

*Except for any they bring along themselves to participate in their talks.

*Factiva is the most significant exception. Hint, hint.

If you think about it, text analytics is a “secret ingredient” in search, antispam, and data cleaning,* and this dominates all other uses of the technology. A significant minority of the research effort at companies that do any kind of text filtering is – duh — text analytics. Cold comfort for specialist text analytics vendors, to be sure, but that’s the way it is.

*I.e., part of the “T” in “ETL” (Extract/Transform/Load).

Text-analytics-enhanced custom publishing will surely at some point become a must-have for business and technical publishers. However, it appears that we’re not quite there yet, as large publishers make do with simple-minded search and the like. In what I suspect is a telling market commentary, there’s no headlong rush among vendors to dump text mining for custom publishing, notwithstanding the examples of nStein and (sort of) ClearForest. I don’t want to be overly negative – either my friends at Mark Logic are doing just fine or else they’re putting up a mighty brave front – but I don’t think the nonspecialist publishing market is there yet.

Two business publishers who have made major investments in owning text analytics technology are Dow Jones (now sole owners of Factiva) and Reuters (recent purchaser of ClearForest). Beyond that, however, I don’t yet see a lot of activity in the investor/trading market, although ClearForest reported some activity last year and StreamBase reports that one customer is using them for text filtering, presumably alongside the ticker-munching traders usually use StreamBase for.

Obviously, the intelligence market is what fueled the start of the text analytics business, and still provides the majority of revenue at multiple companies. Certainly it’s still going strong. But it’s tough to gauge the growth potential from here, especially since the details of usage are typically classified.

Similar things could be said about pharmaceutical research. Text analytics is totally accepted in that market, but what’s the growth potential from here? And “here” isn’t actually very big (much smaller than intelligence). The related category of patient records analysis looks very promising, but is basically still at the research-project stage. (In general, an explosion in biological IT can be expected when research methods are adapted for clinical use.)

The warranty analysis market, so promising early on, is not showing a lot of growth and depth. The same thing has happened many times before with innovative technologies sold to manufacturing companies’ engineers. It seems to be happening again now.

Voice of the customer* is pretty much the same thing, but for service industries. And the text analytics market for VotC is evidently stronger right now than that for warranty analysis. This makes sense, because the obvious alternative to text analytics – multiple-choice coded forms – is less appealing, due to two application differences:

• VotC looks for opinion as well as fact.

• VotC looks for input from people under no obligation to share it, and who hence can’t be compelled to play along with a structured form – let alone trained to fill it in accurately.

*Definitional note: Voice of the customer is when customers or prospects communicates with you directly, e.g. via a survey form or an angry email. Reputation management is when you web-scrape and find out what they’re saying to everybody else. At least, I think marketers are still using the terms that way pretty consistently.

Reputation management is surely becoming a standard application for the biggest consumer brands. How deep that market turns out to be, however, remains to be seen.

Text analytics for fraud discovery seems poised to sweep the insurance industry, and then the rest of financial services. Current activity, however, while decent, still seems to consist of more poising than sweeping.

Compliance is a minimum-acceptable-efforts kind of activity in most markets. Accordingly search/clustering seems to be the preferred text-checking approach. Where that’s not the case, the market seems to have gone to specialized products like Assentor (stock brokerage).

Human resources is a good area to sell follow-on applications, at least to enterprises with so many employees that they want to automate the reading of employee feedback. I’m not aware of it being the first-sale app to very many enterprises, however.

SAS used to speak glowingly of text mining used directly for ETL. However, nobody else has talked about this, and even from SAS I get the sense that some of the glow has worn off. As noted above, text analytics is an important ingredient to the transformation part of ETL, but it I think it rarely would be the best option for doing the transformations directly.