IBM’s Watson Enlisted for B2B Sentiment Analysis

B2B customer support firm TeamSupport on Tuesday announced the addition of sentiment analysis technology, powered by IBM’s Watson, to its customer relationship platform.

The new tech provides automatic text analysis of email or chat responses to assess how a customer feels, so customer support teams can prioritize and personalize their outreach efforts. It includes predefined categories such as “satisfied” and “frustrated.”

The sentiment analysis capability is an addition to TeamSupport’s Customer Distress Index, which analyzes ticket and response data to categorize levels of customer satisfaction at a company level.

IBM Watson data will be used to score response data at both the ticket and overall customer level to help inform customer strategy and provide a framework for customer success, TeamSupport said.

The company also plans to use data from IBM Watson to expand other areas of its service, noted TeamSupport CEO Robert Johnson.

Customer Support Table Stakes

“Sentiment analysis for chat and text has been around for a long time,” observed Rebecca Wettemann, VP of research at Nucleus Research.

“RightNow had it before the Oracle acquisition. IBM had it long before Watson was its marketing albatross,” she told CRM Buyer.

Sentiment analysis “has evolved to be more sophisticated and cost-effective, and there are varying levels of effectiveness of such solutions,” Wettemann pointed out. “It’s really table stakes by now.”

The technology’s long history in customer support has revealed many uses, noted Ray Wang, principal analyst at Constellation Research.

“Many pioneers of this technology have shown how it could — in customer support — change prioritization of issues [and] response time to cases,” he told CRM Buyer.

More importantly, it enables reps to know the customer interaction history before responding, Wang said.

Outdoing IBM

What is interesting about TeamSupport’s approach is that it “has made the investment to operationalize Watson in a way IBM has — so far — been unable to do,” Nucleus’ Wettemann noted. “This may make it accessible to smaller teams without the resources to build out their own sentiment model.”

However, “there are plenty of in-app options available at multiple price points today,” she remarked.

Other companies that offer sentiment analysis to help customer support efforts include Medallia and Clarabridge, Wang said, “but they have traditionally been more focused on B2C than B2B.”

Help Desk on Steroids

TeamSupport’s tools were designed from the ground up by B2B support professionals for organizations providing external customer support. The company compares its offerings to help desk software from Zendesk, Freshdesk, Service Cloud, Parature, Intercom, Kayako and HappyFox.

Customers include the American Lung Association, the United States National Basketball Association, Agilent Technologies and Comcast.

“If the training programs for TeamSupport improve the accuracy of existing capabilities in the market, they have a good shot at gaining market share,” Wang observed.

Resolving the Growing B2B Buyer-Seller Divide

There’s a growing divide between B2B buyers and sellers, according to the Miller Heiman Group, with buyers seeing sales teams as product representatives and engaging them later in the purchasing process.

Sentiment analysis may help breach that divide.

For example, Insights, a feedback analysis solution Yotpo announced at Shoptalk in March, uses natural language processing (NLP), artificial intelligence and machine learning technology to analyze reviews and their related opinions.

Retail brands can use Insights to analyze customer feedback at scale to identify trends or untapped markets, receive alerts about new issues, and gain instant feedback on new product releases.

Sentiment analysis “uses NLP to identify, prioritize and suggest responses to de-escalate customer issues,” said Constellations’ Wang, “and, more importantly, proactively resolve issues before they become a problem.”

Richard Adhikari has been an ECT News Network reporter since 2008. His areas of focus include cybersecurity, mobile technologies, CRM, databases, software development, mainframe and mid-range computing, and application development. He has written and edited for numerous publications, including Information Week and Computerworld. He is the author of two books on client/server technology.
Email Richard.

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