Medallia Launches Text Analytics

Medallia yesterday launched machine learning Text Analytics technology that automates the discovery of customer-feedback topics. This real-time solution is capable of processing and analyzing billions of customer comments at the click of a button.

Medallia's machine learning approach automatically clusters and classifies conceptually related expressions and sentences, enabling its customers to anticipate and respond to changes in customer feedback and sentiment.

"Companies today are faced with vast amounts of solicited and unsolicited customer feedback. Text analytics offerings have come a long way but are still only as good as the people behind them, which can lead to inherent bias and blindspots," said Ken Fine, head of worldwide product at Medallia, in a statement. "What Medallia's new text analytics engine does is turn this problem on its head by allowing machine learning to identify topics that could have been missed. We can do this on the fly and with any amount of data."

Sage Software, a provider of accounting, ERP, and payroll solutions, was one of the companies to pilot Medallia's Text Analytics product.

"Hard data only tells part of the customer story. Listening to what customers are saying is what brings that data to life and gives my CX team the insight they need to take action that's focused on the highest-priority friction areas across our customer lifecycle," said Jim Pendergast, senior vice president of global customer experience at Sage, in a statement. "We receive thousands of customer comments daily. Each one of those comments is a learning opportunity for us. It would be impossible to extract tangible meaning out of this data without Medallia."

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Customer experience management company Medallia acquired customer feedback capturing technology Kampyle earlier this week and rolled it into Medallia Digital—a combined feedback management and data analytics solution. Together, the two solutions will deliver more omnichannel insight into the customer experience because it will take both offline and online data into account.

Posted October 21, 2016