CallMiner: Revolutionising Emotion in the Contact Centre

Company's bespoke AI underpins empathy in CX, driving business success

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Callminer Emotion in the Contact Centre
Contact CentreInsights

Published: September 24, 2021

Maya Middlemiss

Maya Middlemiss

Customer experience has always been about levelling up happiness and satisfaction – but these emotions are often difficult to measure and model at scale. Today’s customers have high expectations of the brands they engage with and buy from, including the ways they connect and communicate with customer service and contact centre agents. 

To meet those expectations, brands are embracing artificial intelligence (AI) to gain deeper insights into customer conversations and to support agents in how they engage with customers. 

To better understand the role of AI in supporting more empathetic customer experiences and better contact centre outcomes, I spoke to CallMiner’s VP of AI, Rick Britt. He explained the challenges brands and agents face when managing and engaging with emotional customers. 

“You’ve got a lot of information coming at you, and you have to deal with the actual issue the customer has… You need to fix the problem, and while you’re doing that it’s difficult to get involved in how they’re feeling,” he explained.

Real-time AI augmentation can support that. By discreetly flagging escalating tensions or delivering actionable guidance for how to defuse the situation, agents can more effectively respond to the human side of the interaction, while offering a practical resolution, without having to evaluate that emotion in the first place.

What gets measured gets managed – including feelings

To achieve this, AI continually listens and scores in complex ways.

“We listen to the words they’re using first,” Britt explained, “and then the acoustics. Is the pitch going up or down?

“But I have friends, who when they get angry, they get quiet,” he pointed out. “So we use pseudo-acoustics as well, to assess things like pauses, or patterns of general behaviour in a conversation.”

Being able to indicate to the agent when emotions are changing during a call is a powerful way to deepen the emotional connection with the customer. At scale, brands can draw out tangible metrics for actionable insights, such as the most common reasons why customers show different emotions and how effectively agents respond. These insights can be used to improve individual agent performance, deepen the understanding of the voice of the customer, and deliver better CX – ultimately improving competitiveness and the bottom line.

The power of CallMiner’s AI, in live voice and text-based interactions, can help brands better understand and respond to their customers, while helping inform strategic business decisions.

Continually learning and improving

AI gets more effective as more data is ingested, generating increasingly valuable and relevant insights.

“The most exciting benefits right now are in unsupervised learning,” Britt continued, “where we know the answer is in the data…a very common question that a brand might have, why are my customers calling me?”  

AI can identify, isolate and analyse all the relevant points of every call in a vast dataset to provide a clear answer to that kind of question. “The algorithm can cluster the content by words, but also by emotions and contexts – giving the brand the ability to understand their callers better, and then predict their future behaviour.”

Meanwhile, when it comes to retaining the best and most skilled agents, CallMiner’s AI capabilities do more than provide perfectly timed intelligent support and identify the traits that make agents most successful to improve training. It also builds predictive models to help organisations understand agent attrition, an issue affecting even the best brands in every market right now.

“It’s not only customers. Can you predict when an agent is going to leave a company, can you invest in addressing that cause that might lead other agents to quit? 

“As the AI deepens its understanding and modelling of empathy, it can better support ALL the humans involved in the conversation.”

 

 

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