CLARABRIDGE ENTERPRISE 4 SPEEDS DEPLOYMENT OF TEXT MINING FOR CUSTOMER FEEDBACK APPLICATIONS

November 16, 2009 00:00 AM

Clarabridge, the leading provider of text analytics solutions that improve customer experience management (CEM), today announced the general availability of Clarabridge Enterprise 4. This major release adds numerous ease of use and back-end enhancements to support a broadening base of users with individualized needs. It incorporates feedback received from Clarabridge’s Executive Steering Committee as well as improvements from dozens of text analytics deployments at world-leading companies.

Clarabridge Enterprise 4 includes the addition of an Ad-Hoc Uploader, upgrades to the Natural Language Processing (NLP) and Sentiment Engines, new collaboration tools in the Classification Suite and built-in Early Warnings and Alerts. These new and improved features enable any department to make customer experience improvements quicker by including any feedback desired, customizing analytical models, supporting teams of analysts and business users and delivering the insight when and where needed.

“Enterprises collect customer feedback from many sources – social media, surveys, call centers – and in many departments – customer service, product management, operations, and Clarabridge was designed to support these use cases,” said Sid Banerjee, chief executive officer at Clarabridge. “Enterprise 4 represents our commitment on improving the usability of our software for those various audiences and feedback sources. We thank our customers and partners for helping us better our product and our company – many of the features and functions in this version are a direct result of their feedback.”

Specifically, Clarabridge Enterprise 4 enhancements include:

“With this direct upload option, we include all of the ‘long tail’ of ad-hoc and one-off sources in the system alongside the enterprise application sources,” said Justin Langseth, president and chief technical officer at Clarabridge. “Clarabridge 4 is the only enterprise text mining solution for customer experience that has this flexibility.”

Earlier, Clarabridge also announced it will hold its second annual Clarabridge Customer Connections (C3) users conference January 25-27th, 2010 at Disney’s Yacht & Beach Club Resorts, Lake Buena Vista, Fla. The conference brings together Clarabridge’s customers, partners and thought leaders from across the industry to discuss and exchange techniques to using text analytics for customer feedback, varying methodologies and best practices that drive CEM success across their businesses, and to explore new ways to help leverage these practices. The early bird registration ends on November 30th. To register, please visit: www.regonline.com/clarabridge.

About Clarabridge

Clarabridge is the leading provider of text mining software for customer experience management. The Clarabridge Content Mining Platform™ provides Global 1000 enterprises an analytical view of text-based verbatims found in voice of the customer feedback channels such as call center notes, qualitative survey feedback, Web 2.0 content, online forums, reviews, social media sites, and customer warranty forms. As a result, businesses can improve marketing, product/service management and customer service delivery. Clarabridge is privately held with headquarters in Reston, Va. Clarabridge customers include AOL, Capital One, Choice Hotels, Expedia, Inc., Gap, Gaylord Hotels, H&R Block, Intuit, Marriott International, Sage North America, United Airlines, Walmart and Walgreens. For more information, visit www.clarabridge.com.

Contacts

  • NLP & Sentiment Engine Upgrades: Clarabridge’s research and development efforts have resulted in continued improvements in the NLP and sentiment engines. New features include clause-based sentiment and classification, along with a multitude of core engine enhancements. Clarabridge Enterprise 4 also adds support for classifying data in foreign languages. These upgrades improve the sentiment results for clients, but also make it easier to tune sentiment for their particular industry or application needs.
  • Classification Suite Updates: Clarabridge Enterprise 4 offers enhancements that increase the accuracy of categorization and adds workflow tools for improved collaboration during the creation of the category model. Classification Templates, developed from Clarabridge’s experience in multiple industries, provide quick-start templates for analysts developing category models. Collaboration upgrades include the locking of models to prevent changes, rule history and roll back functionality, color-coding as a visual aid for maintaining models, and a preview feature. With these updates, analysts can more easily develop, QA, and maintain models with other team members across their organization. In addition, Clarabridge 4 offers enhancements of the analysis capability in the Clarabridge Navigator interface to allow users to directly run, view, and analyze the classification results to facilitate optimal classification precision and recall.
  • Early Warnings & Alerts: Statistical warning and alert engines help users proactively address customer experience issues by alerting them to anything that exceed defined thresholds. Users can configure the thresholds and delivery methods to suit their needs, and receive real-time notification of any significant event.
  • Ad-Hoc Uploader: The Ad-Hoc Uploader allows business users to upload feedback sources for analysis directly from their own browsers via an easy-to-use wizard. While administrators run and monitor million-plus verbatim enterprise sources, this new feature allows market researchers and business analysts to upload their smaller ad-hoc feedback sources, classify through their standard or custom category models, extract sentiment, and analyze the feedback in a completely self-service mode. With this feature, Clarabridge clients continue to build a 360 degree view of their customer experiences by systematically incorporating large feedback sources as well as the flexibility of quickly and easily adding smaller, diverse data sets.