Clarabridge Hones Focus on Social Media as Text Analytics Demand Grows

By   /  May 16, 2011  /  No Comments

Alta Plana Corp.’s Seth Grimes last week pinpointed text analytics market demand as closing in on the $1 billion mark globally, with growth in particular among apps that use NLP to derive business insight (from facts to relationships to sentiment) via social networks, online media, and/or surveys. Among such applications are Clarabridge’s Enterprise and Professional sentiment and text analytics software, which now include features such as embedded connections to some major social media monitoring sources with today’s release of its Tower version 4.5 edition.

On the social media source front, Clarabridge says that users now can directly access data pulled from Lithium, NM Incite Buzzmetrics and Radian6 without leaving its interface, for faster access to conversations and insights. Its new Voice of the Customer (VOC) source framework accomplishes this and is designed to easily adapt to additional sources in the future, as well. Companies could previously add this data to their Clarabridge solutions but not seamlessly, as they can for accommodating social media data from sources like Twitter and Facebook.

Among companies that are looking to create a multichannel Voice-of-the-Customer solution, as Clarabridge brands it, “the majority are using multiple listening platforms today, including Lithium for forums, Bazaarvoice for ratings and reviews, a wide variety of EFM platforms, and social media aggregators like Radian6 and/or Nielsen Buzzmetrics,” CEO Sid Banerjee told the Semantic Web Blog in an email conversation. In addition, companies also often integrate CRM data, email, live chat, and even news data, he says, so they need a single platform to integrate, commonly categorize and quantify sentiment across these sources.

“If you use multiple tools, you get different outputs, and you can’t compare the insights in an apples-to-apples manner,” he says. “Point solutions also don’t easily deploy across an enterprise.”

With the VOC source framework, Clarabridge can take content from many discrete sources,  integrate and quantify the text, and distribute the insights in a secure, scalable manner across sales, marketing, operations, and customer insights teams in a way that single platforms cannot, Banerjee says. The VOC source framework over time can support not only more social media aggregators but potentially CRM or even SFA vendors.

The company also is adding native language parsing for French and Portuguese, including advanced sentiment analytics, to its existing English and Spanish language support. “You can build native language categories, see the sentiment of all text, aggregated against all documents of a particular language. So you can have an application that is “single language,” Banerjee says. Or, Clarabridge can create an aggregated application that allows an analyst to see feedback from multiple languages in a single dashboard that displays categories, subcategories, sentiment scores, and structured data elements in the desired language.

The way it do this, he explains, is that the software first parses all languages natively, and scores sentiment for all languages natively. But it can create common categories that categorize text into a category like ‘bedroom’ regardless of whether the sentence contains mentions of ‘chambre’ or ‘bedroom.’  “Our category models are able to work in multiple languages because we can recognize key words and linguistically connected concepts in multiple languages, and group them together into a common category model regardless of the original language,” Banerjee explains.

Other new features in the Tower edition are first-time support for word clouds, serving as a quick reports window for executives or high-level decision makers about what’s trending among customers, including color-coding for sentiment and the ability to quickly drill down to see verbatim responses themselves with one click.  “We not only do this for single words, but we also do it for word groups that are linguistically connected, which is a competitive differentiator, since linguistically connected words in word clouds provide more conceptual understanding than just words,” he says.

The update also includes giving access to insights to more people who can do something about what they learn. This required building into the software better security and administration of who can see what, and what they can modify or just view. The vendor has seen that as its customers begin to realize the value of listening to the voice of the customer through their implementation of a customer experience management program, “it’s equally important to insure that those actionable insights get promoted across their companies,” Banerjee says.

From Traction to Next Actions

So, what’s behind the traction the market is seeing in the text and sentiment analytics space, and where does the energy go next? “Text and sentiment analytics are just enabling technologies, and what we’ve believed all along is that the key business problem is, how do we listen to the voice of our customer, when we’re inundated with so much of it, coming from so many places. The problem hasn’t changed, but we’ve seen the technologies mature, and frankly, the recession has pushed companies to really focus on retaining their customers, which has created a perfect storm of sorts.” Banerjee says.

Banerjee says he envisions a world where every customer touch-point is interconnected, no matter whether it’s physical or virtual, and every employee is empowered to access customer insights to make more informed and highly personalized decisions anytime. The next phase of that world, in the coming year or two, will revolve around solutions that can “predict” problems before they occur, with text and sentiment analytics being used to drive more efficient and personalized support, marketing, and even campaign management processes, he says. “Many existing processes in the CRM, E-commerce, F (Facebook)-commerce, and support spaces will be enhanced and expanded as text and sentiment algorithms and content is merged with those solution areas.”

Speaking of merging, Banerjee does foresee consolidation in what has been a fast-evolving and increasingly crowded space. Point solutions will either have to grow beyond their current capacity or get acquired, he says, noting that Clarabridge itself began that way, but has focused on continually adding more functionality and value.

“As we’ve evolved into this space, we’ve naturally partnered with both information providers like Lithium, Radian6, etc, as well as information consumers like the market research firms, systems integrators, platform companies that have an interest in creating consolidated data sets. Consolidation is likely to occur as providers, analyzers (like us) and consumers of insight are brought together,” he says. “But there is also value to staying independent and continuing to work with a wide range of content providers and consumers. A company like Clarabridge needn’t be part of a consolidation play to remain viable and valuable.”







About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.

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