Analysis of text mining vendor Clarabridge and its products. Related subjects include:
I had a brief chat with the Attensity guys at their Teradata Partners Conference booth – mainly CTO David Bean, although he did buck one question to sales chief Jeff Johnson. The business trends story remained the same as it was in June: The sweet spot for new sales remains Voice of the Customer/Voice of the Market, while on-premise/SaaS new-name accounts are split around 50-50 (by number, not revenue).
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.
|Categories: Application areas, Attensity, Clarabridge, Competitive intelligence, Software as a Service (SaaS), Text mining, Text mining SaaS, Voice of the Customer||1 Comment|
Jim D. of UPS asked in the comment thread to the recent Attensity update post how one should decide between Attensity and Clarabridge. I wrote an answer, and then decided to just split it out in a separate post. Here are five ideas about how to pick between Attensity and Clarabridge for the kind of Voice of the Customer/Market application both companies are focusing on.
1. Attensity is the older company than Clarabridge, and is good at more things. Is Clarabridge really good at everything you want them to be?
2. In particular, Attensity has more overall sophistication at linguistic extraction. Do any of the differences matter to you?
3. Both companies are working hard on ease of use, for multiple kinds of user (business user tweaking linguistic rules, IT user, etc.). Whose approach and feature set do you like better?
4. Usually, buying one of these products involves some professional services. Whose organization do you like better?
5. Attensity’s default database schema for its exhaustive extraction is pretty flat and normalized, as befits a happy Teradata partner. Clarabridge’s is more of a star schema, as befits a bunch of ex-Microstrategy guys. Either can be straightforwardly translated into the other, so you may not care — but do you?
|Categories: Attensity, Clarabridge, Competitive intelligence, Comprehensive or exhaustive extraction, Text mining, Voice of the Customer||4 Comments|
One of the major dilemmas facing a group of people we all know is: How can humanities majors make money? Sure, they can become lawyers. And they can join the tech industry and write documentation. But what else?
Well, what about text analytics? Much of what I know about natural language processing (NLP) I learned from my friend Sharon Flank, who I met when she was a Slavic Linguistics PhD student at Harvard. My partner in first figuring out search engines — and later in running Elucidate — was my wife Linda Barlow, a 15-times-published novelist who’s also taught English at the college level. And Olivier Jouve’s education is in paleontology, although whether or not that’s a humanity is a sort of borderline definitional issue.
So I ask you all: Is text analytics a fruitful area for humanities majors to find lucrative careers? All insight would be appreciated. If the news is good enough, I’ll do my part in publicizing it to university placement offices and the like. Read more
I chatted recently with David Bean, Attensity’s CTO, and then with marketing exec Phil Talsky. Highlights included: Read more
|Categories: Application areas, Attensity, Clarabridge, Competitive intelligence, Software as a Service (SaaS), Text mining, Text mining SaaS, Voice of the Customer||6 Comments|
I talked with text mining SaaS vendor Clarabridge’s CEO Sid Banerjee today. Part of the call covered applications and markets for Clarabridge’s technology. Highlights included: Read more
|Categories: Application areas, Clarabridge, Software as a Service (SaaS), Text mining, Text mining SaaS, Voice of the Customer||Leave a Comment|
Clarabridge CEO Sid Banerjee called with some product news that is embargoed until the Text Analytics Summit, and which I hence won’t write about at this time. But during the call, I discovered something interesting – Clarabridge’s hosted/SaaS (Software as a Service) text mining offering has taken over its business. Highlights of the call included: Read more
I just had a quick chat with text mining vendor Clarabridge’s CEO Sid Banerjee. Naturally, I asked the standard “So who are you seeing in the marketplace the most?” question. Attensity is unsurprisingly #1. What’s new, however, is that Inxight – heretofore not a text mining presence vs. commercially-focused Clarabridge – has begun to show up a bit this quarter, via the Business Objects sales force. Sid was of course dismissive of their current level of technological readiness and integration – but at least BOBJ/Inxight is showing up now.
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. Read more
|Categories: BI integration, Clarabridge, Comprehensive or exhaustive extraction, IBM and UIMA, Software as a Service (SaaS), Text mining, Text mining SaaS||1 Comment|
And for my sixth text mining post this weekend, here are some highlights of the Clarabridge technology story. (Sorry if it sounds clipped, but I’m a bit burned out …)
- Like Attensity, Clarabridge practices exhaustive extraction.* That is, they do linguistics against documents, extract all sorts of entities and relationships among the entities from each document, and dump the results into a relational database.
- Unlike Attensity, which uses a simple normalized relational schema, Clarabridge dumps the extracted data into a star schema. (The Clarabridge folks are from Microstrategy, which – surely not coincidentally – also favors star schemas.) Read more
|Categories: BI integration, Clarabridge, Comprehensive or exhaustive extraction, Ontologies, Text mining||2 Comments|
Besides asking them technical questions, I surveyed Attensity and Clarabridge last week about text mining application trends, getting generously detailed answers from Michelle De Haaff of Attensity and Justin Langseth of Clarabridge. Perhaps the most important point to emerge was that it’s not just about particular apps. Enterprises are doing text mining POCs (Proofs of Concept) around specific apps, commonly in the CRM area, but immediately structuring the buying process in anticipation of a rollout across multiple departments in the enterprise.
Other highlights of what they said included: Read more
|Categories: Application areas, Attensity, Clarabridge, ClearForest/Reuters, Competitive intelligence, Factiva/Dow Jones, Investment research and trading, Text mining, Voice of the Customer||3 Comments|
I’ve been emailing and/or talking with both Clarabridge and Attensity this week. Since they’re the two big proponents of exhaustive extraction, I naturally asked whether there are any cases exhaustive extraction should not be used. In Clarabridge’s case, it turns out exhaustive extraction is the default, and no customer has ever turned this default off. However, their current high end is several million documents* per year. They suspect that in some current projects with much higher volumes the default may finally be turned off. Read more