Can Emotional Analytics Help Businesses Get in Tune with How their Customers Are Really Feeling?

 CTO and Founder Jeff Gallino is quoted in CRMXchange’s article on emotional analytics. 

 

Emotion analytics solutions have the capability to extract insights from all customer touchpoints and channels across the organization which include: calls, texts, video, facial, emails, chats, and social media platforms. These products employ historical data and real-time information to identify customer patterns and trends, providing the background for an agent to tweak the dialogue over the course of the call. Data and real-time information help companies to determine the right offers to generate to retain customers, thereby reducing escalations and churn. This makes emotion analytics a weapon of mass instruction for businesses seeking to gain an edge by learning what makes their customers tick.

One technology sector that has a head start in emotion recognition is speech analytics, which introduced speech-to-text transcription. “We’ve done a great deal of research around capturing emotion in conversation,” noted Jeff Gallino, CTO and Founder, of long-time speech analytics leader CallMiner. “We firmly believe that emotional expression goes beyond simply the words being said but is a combination of factors. While there is no good emotional measurement without the underlying context of the words, there is so much more rich communication when you can overlay the tonality that accompanies them. Sentiment …which we’ve been measuring for a pretty long time…. is the verbiage of emotion for us. It helps you to understand how a customer feels about a product, service or interaction. It enables an enterprise company to coach an agent to better respond to those needs.”

“A classic example is if a customer is asking about a product and their description is negative,” continued Gallino.  “He says ‘You know, I really need a phone but while I don’t like those things, I need this functionality.’ The initial part of the statement is a sentiment on top of a product.  The way the customer on the phone benefits is that we can train the agent on how to show empathy, on how to better respond, perhaps by providing education. There are a lot of different kinds of responses that can be used for that statement. The agent could have the same kind of call the very next day where the customer is enthusiastic: “I love those things.’ The agent will treat that caller differently, which has nothing to do with the product. It’s that by measuring the sentiment expressed allows us to better serve that particular customer.”

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