Posts tagged Attensity
Attensity Sells IP to InContact: What Does it Mean?

Goodbye to Attensity, an early text analytics pioneer Attensity

Fellow text analytics colleagues,

I wanted to direct your attention to some industry news that broke today. It appears that Attensity—an OdinText competitor and a long time name in the text analytics software space—is selling its IP assets to InContact, a provider of call center solutions. (Read about it here.)

For people who’ve been watching the text analytics sector, this probably comes as no big surprise. It is well known that Attensity has been in the throes of some financial difficulty for a while. And just last month they sold their European business to an investment consortium. (Read about it here.)

It is my guess that Attensity’s text analysis software will be bundled into InContact’s portfolio as a value add for call center customers—essentially using the former’s basic NLP for a voice-to-text application and then to code results.

Whether or not Attensity’s product continues to exist in a standalone capacity, too, or what this means for their existing customers remains to be seen.

I think this development is noteworthy in part because Attensity was one of the earliest players in the text analytics space. In fact, even Claraview—the company from which Clarabridge was later spun off in 2006—initially licensed Attensity’s technology, before developing their own very similar tool.

As I noted in a very recent blog post, Attensity and Clarabridge both adhere to a rules-based approach that requires costly and time-consuming customization.

At the risk of being self-serving, it seems to me that as the text analytics market continues to mature and buyers become better informed, we’ll see increasing demand for more flexible solutions that are faster to get up and running and easier to use with a better total cost of ownership.

That’s good news for OdinText, but as the situation with Attensity suggests it doesn’t bode well for competitors with eight figure debt selling dated approaches.

That said, it is an extremely exciting time for industry as a whole with adoption continuing to increase as more and more use cases now move to clients ‘must have’ lists.

@TomHCAnderson

 

[NOTE: Tom is Founder and CEO of OdinText Inc.. A long time champion of text mining, in 2005 he founded Anderson Analytics LLC, the first consumer insights/marketing research consultancy focused on text analytics. In 2015 he founded OdinText SaaS which take a new, Next Generation approach to text analytics. He is a frequent speaker and data science guest lecturer at university and research industry events.]

Attensity, Clarabridge vs. OdinText: What’s the Difference?

Attensity Clarabridge Text Analytics Software Comparison - The Printing Press Still Prints, But Who Would Want To? I’m always a bit reluctant to talk about competitors because I don’t want to disparage anyone, but people often ask me: what differentiates OdinText from your two big, well-known text analytics software competitors, Attensity and Clarabridge?

A RULE-BASED APPROACH

Attensity and Clarabridge are traditional text analytics tools, but they adhere to an outmoded, rules-based approach. This means they require costly and time-consuming expert customization before they can be useful to a client.

Furthermore, once these rules-based dictionaries are created, they only apply to the data used to create the rules. So, if you attempt to use the tool in another industry, category or company or for a different data set, critical exceptions to these rules creep up that render them useless.

Attensiity Clarabridge Text Analytics Software Comparison

ODINTEXT - LESS SETUP, FASTER INSIGHT

In contrast, we built OdinText from an analyst’s perspective—not a developer’s—so that it’s intuitive, adaptive, data agnostic and fast. It doesn’t need all of this extensive priming and it works great right out of the box, which cuts the speed to insight dramatically.

The platform is easy to use, trainable to everyone and flexible in order to provide long-term value across an organization. This is part of the reason why we refer to our solution as Next Generation Text AnalyticsTM.

BUILT BY ANALYSTS, FOR ANALYSTS

OdinText is the culmination of more than a decade of applied text analytics experience as a user of multiple text mining software platforms for large clients, including social media giants like Facebook and LinkedIn.

We realized that all of these platforms were built on an approach that required custom dictionaries and linguistic rules—they are more similar than different—and on the analytics side they all lacked fundamental capabilities to perform the tasks for which researchers like us needed them.

CLEANER DATA, BETTER INSIGHT

The exclusive advantages to OdinText’s empirically-based, patented approach include what we refer to as Contextual Sentiment and ESC (Noise Reduction). Put simply, OdinText automatically filters out noise and brings important verbatim issues and relationships in the data to the user’s attention, allowing them to easily discover what they may not otherwise even have known to look for.

[Contact us for additional information on OdinText Contextual Sentiment/Noise Reduction]

Attensity Clarabridge Text Analytics Softwaer Comparison

The real innovation in word processing was not the technology, but its impact: Word processing simplified and democratized publishing.

OdinText doesn’t require a team of linguists, data scientists or expert consultants to set up before you can use it or reuse it. OdinText enables anyone in your organization to quickly, easily conduct sophisticated analyses of any unstructured text data—survey open-ends, call center transcripts, email, social media, discussion boards—to deliver immediate insights.

IN SUMMARY

In short, OdinText is built for the Analyst in mind - faster setup, cleaner data, better insight, all within a simple interface everyone -- especially Analysts -- can use.

Find out for yourself. Contact us for a demo.

 

Yours fondly, @TomHCAnderson

 

[NOTE: Tom is Founder and CEO of OdinText Inc.. A long time champion of text mining, in 2005 he founded Anderson Analytics LLC, the first consumer insights/marketing research consultancy focused on text analytics. He is a frequent speaker and data science guest lecturer at university and research industry events.]

The Text Analytics Opportunity

The Text Analytics Opportunity Text Analytics remains an opportunity for those wishing to gain an information advantage

[Note: This is an ongoing series of interviews on analytics ahead of the Useful Business Analytics Summit. Feel free to check out the rest of the interviews beginning here]

 

My favorite topic of any analytics conference is of course the mining and analysis of unstructured data. Whether you call it Natural Language Processing (NLP), Text Mining, or the more recently popular Text Analytics chances are you’ve heard of it. Since I started Anderson Analytics ten years ago, as the first consumer insights firm to leverage text analytics, the discipline seems to have gone from an unknown to mainstream ubiquitousness.

That said, because it is such a quickly evolving field many of the main players 10 years ago have faded into relative obscurity. Some have been purchased by other companies, many have simply not been able to keep up with advancements or proven adequate value.

Therefore perhaps I shouldn’t have been surprised that this was the one area where our analytics experts were a bit less sure of themselves, and I received relatively few responses to my questions.

That said, consensus is that there certainly are text analytics software options on the market that do provide strong value. Personally I think the main challenge is that there are still too few analysts with experience in text analytics, and too little time allocated to prove just how amazing unstructured data insights can be!

Q. What is your opinion on the current state of the unstructured/text analytics field?

 

JonathanIsernhagenTravelocity

I am the wrong guy to ask, because I was already blown away six years ago when Attensity was boiling down conversations into subject-verb pairs, and things have only gotten better since then. I think there’s a point in the life of each

 

FaroukFerchichiToyota

At this moment, I believe for the kind of experiments that people have started to leverage it for, it is good enough.

 

SofiaFreyderMasterCard

For me personally its more supplemental data. Structured data is easier to utilize, slice and dice.

Unstructured data might be very useful resource of qualitative data and supplemental to quantitative analysis.

Also there are tools that can create structured analytics from unstructured.

 

DeepakTiwariGoogle

A lot of solutions exist in the market place but it is a complex problem and we have a long ways to go.

 

Q. What if anything in text analytics have you found that really works well? What doesn’t?

 

JonathanIsernhagenTravelocity

I don’t have direct experience with text mining beyond what we’ve done with Attensity.

 

FaroukFerchichiToyota

What works well is the flexibility and ability to change and implement once you have the engine built. What doesn’t work well is the overpriced text analytics tools, which makes many, develop their own and miss the opportunity to focus on analytics instead of transforming the unstructured data.

 

SofiaFreyderMasterCard

Works well: Qualitative data, opinion based data.

Doesn’t : Certain KPIs without benchmark

 

DeepakTiwariGoogle

High level sensitivity analysis and high-level signaling works well. But the solutions are not at a place for granular actionable insights. In other words, use them as an indicator and not as an actionable solutions.

 

Stop by for the next blog post as I ask our experts about tips for selecting a software vendor, how much software should cost. I’ll even be asking how our client side speakers like to be sold to…

 

@TomHCAnderson

@OdinText

 

[Full Disclosure: Tom H. C. Anderson is Managing Partner of Anderson Analytics, developers of patented Next Generation Text Analytics™ software platform OdinText. For more information and to inquire about software licensing visit ODINTEXT INFO REQUEST]

OdinText Named Key Challenger to IBM and SAS in Text Analytics Space

Anderson Analytics’ New Text Analytics Platform OdinText Positioned to Challenge Status Quo Anderson Analytics’ OdinText was named as a key challenger to competitors IBM, SAS, Clarabridge and Attensity last week in both the ‘Go to Market Strength’ and ‘Customer Experience Strength’ Quadrants of the 2013 Text Analytics Victory Index Report.

The Customer Experience Strength category is evaluated based on Validity (strength of product) as well as Value (strength in meeting client objectives). Go To Market Strength is based on Viability (stability of company) and Vision (strength of company strategy).

Anderson Analytics CEO and inventor of OdinText, Tom H. C. Anderson, commented

We are pleased to be recognized by industry analysts and customers so early after launch. Clients today recognize that the best innovation typically comes from newer software solutions. The challenge will be never to rest on our reputation, but to continually build it by listening to our customers. Fortunately, this is exactly what our software OdinText is extremely good at. We’re looking forward to a very exciting 2013.

Founded in 2005, Anderson Analytics was the first market research firm to leverage text analytics in consumer insights. The firm has been recognized several times in the past for their innovative methodology and leadership in the text analytics field including awards from industry organizations such as the World Market Research Association (ESOMAR), The Advertising Research Foundation (ARF), and the American Marketing Association (AMA).

The independent study on text analytics software vendors was conducted by Hurwitz & Associates, a strategy consulting, market research and analyst firm that focuses on how technology solutions solve real world customer problems. Hurwitz research concentrates on disruptive technologies, such as Big Data and Analytics, Cloud Computing, Service Management, Information Management, Application Development and Deployment, and Collaborative Computing.