For decades, the call center industry has struggled to address issues like low customer satisfaction and high turnover among agents. As simple as it might seem, providing better quality service and ensuring customers do not have to call in multiple times has been a major barrier to improved performance. 

In an age of increased efficiency, customers are demanding more. Nearly 75% of customers say their loyalty hinges on the speed and quality of service they receive, and yet 78% of agents cite the disconnect between speed and quality in their jobs. How do you increase customer service, make the process faster, and keep agents happy at the same time? 

Artificial intelligence is addressing this by systematizing and improving the ways in which customers are routed, agents engage with their problems, and conversations are mediated. Historically, nearly 30% of all calls made to call centers are from customers with problems previously unresolved. With a full third of calls being repeat calls, it’s no wonder turnover rates sit between 19-35%.  Advanced AI solutions are enabling these call centers to not only improve the quality of initial calls but also to provide agents with a set of nimble tools that allow them to respond with greater insight to complaints and concerns, and these tools are more accessible and powerful than ever before. 

AI-Mediated Conversations

More than half of call centers in the United States handle direct customer interaction by phone, but many of them report recurring issues with low employee morale, slow pickup rates, and dissatisfied customers. 

For this reason, nearly half of those call centers are planning to invest in AI in the next five years. Today’s AI systems are more powerful than ever, with models designed specifically for use in call centers. Emotional cognitive AI, in particular, provides a wealth of benefits that can lead to a 12-17% revenue improvement and a 10% or higher customer satisfaction rate increase.

AI-Mediated Conversations (AI-MC) are designed to analyze speech, understand emotions, assess behaviors, and predict intent from vocal cues. The solution can subsequently build complex agent and customer profiles, evaluate calls in real time to determine the best course of action in responding to customer concerns, and provide recommendations for agents. AI-MC with multi-task learning can analyze the emotional states of both the customer and the call center agent to make recommendations on how the interaction should proceed, from routing the customer to the best available agent based on both individuals’ profiles to intervening if a call is predicted to escalate. 

Behavioral Signals’ award-winning technology utilizes 75-dimension profiling to support this approach to call center support. By analyzing elements such as the energy and prosody of speech, general politeness, speaking rate, intonation, and talkativeness, among dozens of other elements, AI-MC provides a near-human quality of emotion recognition. In a number of tests, the system was able to identify anger with higher than 80% accuracy, allowing for more accurate matching and subsequent response from call center agents. 

Call Center Benefits of AI-MC

Many organizations are integrating AI-MC into their call center workflow, which allows them to realize several tangible benefits. 

Among the most substantial improvements is the customer experience. Behavioral Signals’ customers have seen CSAT scores increase by 10%, with a 5% reduction in AHT and a 7% reduction in repeat call rates. As a result, the overall rate of positive call outcomes has increased by 8%, with some organizations realizing even higher gains. Shorter call times, reduced waits, smarter routing, and real-time recommendations to resolve issues ensure customers are getting the highest-quality service. 

At the same time, call centers that have historically struggled with low agent morale and high turnover rates are able to better support agents in their roles. By optimizing agent workflow, AI-MC helps improve agent productivity by 20%, distributes calls more equally among agents, and reduces tension from high-stress calls that can be intercepted more proactively. 

Finally, organizations implementing AI-MC are realizing direct financial benefits in the form of revenue recovery and increased conversion rates. AI-MC helps identify customers with a higher propensity to buy or upgrade (or, in the case of collections, to pay outstanding bills). The result is an 8% increase in upsells and cross-sells and a broader 12-17% increase in revenue for these call centers. Recently, a European Financial Group implemented AI-Mediated Conversations from Behavioral Signals to improve customer-agent matching and address low call success rates. As a result, 95% of their agents saw an increase in call success rates, and they realized a 10.9% increase in positive debt payments. 

The Future of Emotional Intelligent AI for Customer Support

A recent IBM IBV study shows that 63% of executives expect to be using generative AI to support customer service agents and improve retention rates across their businesses. Similarly, IBM predicts that AI will become a crucial component of talent development, empowering agents with tools that improve personalization, producing real-time call scripts to respond to specific customer needs, and leveraging speech analysis to better engage with and respond to customer needs. 

Artificial intelligence is advancing rapidly, enabling sweeping improvements across a range of industries. Customer support in call centers will continue to improve as AI-MC provides a layer of real-time support that improves agent productivity, matching between agents and customers, and overall positive outcome rates. 
For organizations seeking the next wave of technology to support better customer support at scale, Behavioral Signals is at the cutting edge of AI-mediated conversation technology. Through better customer-agent matching, deep AI analysis of conversation and speech data, and optimization of existing workflows to improve productivity and morale, Behavioral Signals’ AI-MC is a crucial resource for broader improvements to contact center performance.

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