Can Emotional Analytics Help Businesses Get in Tune with Customers’ Feelings?
Herb Greenbaum from CRMxchange, a platform focusing on call center software and customer experience, interviewed Behavioral Signals’ CTO, Alexandros Potamianos, Callminer’s CTO, Jeff Galino, and Steve Kraus, VP of Marketing at Cogito, on emotional analytics as a software offering.
He notes how emotional analytics solutions have the capability to extract insights from all customer touchpoints and channels across the organization. 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 offer to generate to retain customers, thereby reducing escalations and churn. This makes emotional analytics a weapon of mass instruction for businesses seeking to gain an edge by learning what makes their customers tick.
The article goes on to explain how a behavioral signals’ process is not unlike that of a traditional speech analytics product…it records audio, breaks it up into chunks to see what is being said when and pass it through a voice activity detector to determine where the voice of the agent and the customer will fit, and then give the chunks of audio to an emotional learning platform that will provide information about the speaking style of both parties as well as emotional behaviors: is the customer angry? Is the agent responding appropriately? Is someone being impolite? Are the customer and agent engaged? According to Alexandros Potamianos, the text outputs will be not just verbatim words, but emotions and behaviors that can be used to shape KPIs that are relevant for contact centers, improve performance and determine how well the agent and the customer are matching. “A big part of it is how you train the model,” he said. “And these models have been trained to be as universal as possible. The big trick is selecting and collecting the most appropriate data, labeling it and using it to train the models.” Behavioral Signals’ main thrust at this point is to integrate with speech analytics solutions. Most of their customer base is what Potamianos describes as “major players” in that space using their API to build alerts for agents to determine how they are doing on a call.
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