David’s thoughts as to why the SaaS share isn’t even higher – as it seems to be for Clarabridge* – centered on the point that some customers want to blend internal and external data, and may not want to ship the internal part out to a SaaS provider. Besides, if it’s tabular data, I suspect Attensity isn’t the right place to ship it anyway.

*Speaking of Clarabridge, CEO Sid Banerjee recently posted a thoughtful company update in this comment thread.

When I challenged him on ease of use, David said that Attensity is readying a Microstrategy-based offering, which is obviously meant to compete with Clarabridge and any of its perceived advantages head-on.

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.”

• Voice of the Customer/Voice of the Market (Attensity pretty much conflates the two) applications are going really well. David kept repeating that prospects were actually calling Attensity, rather than Attensity having to go out on sales calls and find them. (Of course, that’s what’s supposed to happen when you have good marketing, including but not limited to lead generation.) Phil said that the quarter is going extremely well, including with some big-name customers.
• Attensity’s new favorite buzzword for these applications is “First-person intelligence.”
• About 50% of Attensity’s commercial customers take the technology on a SaaS basis, including some of the biggest ones. I didn’t know that, but thought I’d ask after discovering how important SaaS is to Clarabridge. While Attensity apparently introduced a “new” SaaS offering earlier this year, in fact some of Attensity’s largest customers have always been on SaaS.  Edit:  Actually, that 50% figure is overstated.
• Clarabridge is Attensity’s only significant commercial competitor, at least to the extent David or Phil is aware.
• Government is a strong market for Attensity too. (Recall that Attensity was funded by In-Q-Tel.)
• In particular, Attensity has expanded from intelligence to civilian law enforcement, via something called LEADS (Law Enforcement Analysis Desktop Solution). LEADS extracts relationship information from case notes and the like and dumps it into the I2 link analysis tool (OEMed). I’m aware of only one actual LEADS customer (Chesterfield County, VA). But Attensity is talking with other jurisdictions, plus (an obvious group of prospects) “fusion centers” that combine case information across jurisdictions.

• Clarabridge’s favorite buzzphrase is Customer Experience Management (CEM). That’s how they define their category.
• Clarabridge’s second-favorite buzzphrase is Voice of the Customer.
• Clarabridge is active in a variety of all vertical markets, with the common characteristic being the overall richness of customer interaction (based on some combination of frequency and complexity).
  • Travel/lodging/hospitality continues to be important.
  • Retail has come on strong the past 2-3 quarters.
  • The telecom and internet sectors are going well; neither was big a year ago.
  • High-tech consumer electronics is an active sector.
• Much of the value users derive from Clarabridge is early warning, such as of trends in customer sentiment or loyalty.
• Sometimes, this warning can be same-day, for example of technical malfunctions. Sid told one story of a hotel that was wrongly locking guests of its rooms, and another of a website that didn’t live up at ordering time to the offer it had just promoted. In both cases, the problem was detected and fixed immediately. Sid believes this wouldn’t have happened without Clarabridge technology.
• Examples of applications and benefits not closely tied to early warning include:
  • Scorecarding/benchmarking – all doubts about legitimate statistical significance notwithstanding, some enterprises are including text mining results in their self-measurement.
  • Correlation of trends to specific events – text mining can help figure out whether a specific marketing campaign or seasonal variation is getting results. For example, if you run a marketing campaign calling people’s attention to a specific product feature, and your support calls in connection with that feature spike, chances are that the campaign is working.
• Sid cited one example of a household-name Clarabridge customer using more open-ended survey forms than before. Good idea. Lots more enterprises should follow suit.

• SaaS represents over half of Clarabridge’s revenue. Please note that this surely means well over half of Clarabridge’s new sales are in SaaS, because of how revenue is recognized. And these fractions are still growing.

• Clarabridge is making 10-15 sales transactions/quarter.

• Clarabridge reports 500%+ sales and revenue growth in 2007. (Note that Clarabridge was only recently founded and spun out of Claraview, unlike a number of competitors.)

• Over half of Clarabridge’s customers are already on SaaS. Given the other figures already cited, that’s unsurprising.

• Clarabridge is selling to business departments, in customer-oriented areas (marketing, support, product management, etc.). IT hasn’t embraced text mining technology yet.

• A large customer may get up to 1-3 terabytes of content into Clarabridge over the course of a year. (Obviously, the sample size here is small.)

• Clarabridge says that customers quickly expand their usage to multiple corpuses of data, and multiple business departments. (But then, I’m trying to think of an analytic technology vendor who doesn’t say that, and I’m drawing a blank.)

• In particular, Clarabridge thinks it’s important that its customers can and do fuse internal and external text data. Internal text might be email, survey forms, or call center verbatims. External text might be blog or forum postings.

• Clarabridge has developed a Web services API to bring data back to customer sites, for integration with other data — but few customers care yet. Mainly, they’re operating on a pure outsourced basis.

I’ll post about Clarabridge’s actual applications and customer segments separately.

The most interesting point was text mining SaaS (Software as a Service). When Clarabridge first put out its “We offer SaaS now!” announcement, I yawned. But Sid tells me that about half of Clarabridge’s deals now are actually SaaS. The way the SaaS technology works is pretty simple. The customer gathers together text into a staging database – typically daily or weekly – and it gets sucked into a Clarabridge-managed Clarabridge installation in some high-end SaaS data center. If there’s a desire to join the results of the text analysis with some tabular data from the client’s data warehouse, the needed columns get sent over as well. And then Clarabridge does its thing.

It has always been the case that business intelligence was an IT systems software technology that often wound up being sold on an application basis to end-user departments. Clarabridge very much fits that model. And while it used to be the case that BI adoption was pretty simple, that’s increasingly not the case, which is one reason SaaS is appealing. So this all makes a lot of sense.

Even so, I was surprised to hear that SaaS had so quickly become half of Clarabridge’s business. Wow.

Since Clarabridge touts Cognos as an important partner, and Cognos is being bought by IBM, I also asked Sid about UIMA. He basically responded that UIMA was unlikely to become relevant to Clarabridge any time soon, because the way Clarabridge interfaces with other software is SQL. Up to a point, that makes great sense to me. But if we buy into the comprehensive/exhaustive extraction story — as Clarabridge does — then the day should and will come when serious linguistic processing gets done on text after it is extracted into a relational database. And if that happens, then all of a sudden SQL won’t be the only interface integrating text analytics with BI.

*Note: Umbria has a non-obvious URL.

I haven’t actually spoken with Umbria — uh, guys, why not? — but they seem to have a reputation tracking service. Their niche is apparently to quantify/measure by a variety of metrics, and that’s supposedly what makes their service (and their competitors’) worthwhile.

I certainly believe that automated clustering of web commentary is worthwhile for many companies, even if with no more precision than via some kind of tag-cloud visualization. (And I’ve been skeptical of tag clouds and the like ever since I was first pitched by Semio.) But I’m curious as to whether there’s sufficient and sufficiently precise data to deliver real value along the lines of what Umbria offers.

That there’s enough for at least a superficial demo I have no doubt. Dashboards look great when there are maps involved, and I imagine Umbria’s offering is full of map. Not to mention pie charts, bar charts, layer cake graphs, and all that other good stuff …

So what do you think, folks? How finely can one slice the reputation tracking salami with today’s technology and data, before things just get silly?