How Medallia is Removing Blind Spots from Customer Feedback

January 11, 2017 Nicole Klemp

Most Customer Experience (CX) professionals would agree that customer feedback is only valuable if you have the ability to fully analyze and act on it. Nobody knows this better than the experts at Medallia, who recently beefed-up their already powerful customer feedback analysis capabilities by introducing a new patent-pending text analytics technology. This technology uses machine learning to automate the discovery of customer-feedback topics in real time.

Medallia’s customer experience management system helps organizations manage feedback from end to end: from the creation of well-timed, well-crafted surveys, to timely customer delivery, to response collection and analysis. The data collected is ultimately transformed into actionable items for every employee in real time. These 3 components are key to the customer feedback process:

  1. Capturing real-time customer feedback (from every customer across every channel).
  2. Transforming that feedback into usable insights.
  3. Understanding how to make those insights actionable.

Machine learning eliminates human bias

The company’s new text analysis capabilities make that second step much easier for organizations to accomplish. “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, former VP of Product at Medallia. The element of machine learning in this new technology makes analysis more accurate, removing those blind spots and the bias that human input presents.

Medallia uses Net Promoter Score (NPS) to determine how customers feel about a company. Customers are given the question “How likely is it that you would recommend [Company X] to a friend or colleague?” along with a standard scale that ranges from 0 (not at all likely) to 10 (extremely likely). Based on how they respond, they’re put into one of 3 categories: promoter, passive, or detractor. But why customers feel the way they do is just as important as how they feel about an organization. That’s why the standard NPS question should always be followed by a broad, open-ended question — giving organizations the opportunity to hear very informal comments straight from the hearts of their customers. With their new-and-improved text analysis engine, Medallia can glean the customer sentiments provided in the open-ended question field — blind spot- and bias-free.

Employee feedback

Good feedback analysis can not only help improve the Customer Experience, but the Worker Experience can benefit as well. The Medallia platform uses frequent, anonymous “pulse checks” to give HR and management a better understanding of employee sentiments, and helps to identify areas that may need improvement. Access to bias-free feedback can give leaders a good jumping-off point for creating a dialogue between managers and their direct reports, which can improve employee engagement and morale.

Want to learn more about getting and using customer feedback? Read about customer survey technology, NPS scores, and feedback analysis in our ebook, Creating an Exceptional Customer Experience.

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