Insights | Artificial Intelligence

How AI-Driven Coaching Can Transform Call Centers

Traditional quantitative metrics and coaching techniques are evolving as AI-driven coaching increases both efficiency and personalization of training.

Call center worker accompanied by her team. Smiling customer support operator at work. Young employee working with a headset.
Author: Kevin Able
Author: Jennifer Barton


Your customer care agents are your company’s biggest brand ambassadors. No matter what other customer experience upgrades you make, one poor experience with a representative can undo years of goodwill.  

On the other hand, each interaction with a customer signifies an opportunity – an opportunity to deepen a relationship with the company, to build brand, strengthen loyalty, and most obviously, to resolve an issue promptly and satisfactorily. However, whether this opportunity is a success hinges on the agent’s effectiveness in addressing customer needs.  

Traditional quantitative metrics and coaching techniques used in call centers are evolving as new Artificial Intelligence (AI) tools become available. These AI-driven coaching tools provide novel insights into agent behavior, hyper-customize personalized coaching programs, enhance efficiency, enable continuous monitoring, and even provide real-time coaching. 


The Relationship Between Metrics and Coaching 

Currently, many companies employ metrics-driven behavioral coaching to foster active listening skills, demonstration of empathy, and improve problem solving skills. The idea is to bridge the gap between quantitative performance metrics and the qualitative nuances of agent behaviors. By leveraging performance data, coaches empower agents to refine their skills, driving operational efficiency, enhancing customer satisfaction, and reinforcing the pivotal role of call center representatives as the frontline of the organization.  

Metrics serve as the backbone of call center operations, providing valuable insights into various aspects of performance. Key performance indicators (KPIs) such as average handling time (AHT), first call resolution (FCR), customer satisfaction scores (CSAT), and net promoter score (NPS) offer a quantitative measure of agent efficiency, effectiveness, and customer experience.  

As agents refine behaviors, their influence on key metrics becomes tangible, leading to improved overall performance and greater customer satisfaction. This symbiotic relationship between behavioral coaching and metrics not only elevates individual agent performance but also cultivates a culture of continuous improvement within the call center, driving sustained success and organizational excellence. 

Simply tracking metrics is not enough; it is crucial to interpret them in the context of agent behavior and customer interactions. For instance, a high AHT might indicate inefficiencies in communication or problem-solving skills, while a low FCR could signal a need for better product knowledge or training. By analyzing these metrics alongside call recordings and customer feedback, supervisors can pinpoint specific behaviors that contribute to performance gaps. 

This kind of analysis allows supervisors to customize coaching sessions to address individual agent needs more effectively. Rather than employing a standardized training approach, coaches can focus on targeted skill development, such as active listening, empathy, or product expert, based on the individual agent’s performance metrics and observed behaviors. This personalized approach ensures that coaching efforts are aligned with the agent’s strengths and weaknesses, maximizing their potential for success. 




AI-Driven Coaching 

AI-powered analytics solutions are emerging as invaluable tools for enhancing coaching effectiveness and driving performance improvements. Their power lies in their ability to analyze vast amounts of data, including call recordings, transcripts, and customer interactions to identify patterns, trends, and correlations between specific behaviors and performance metrics faster and more accurately than a person can. 

AI tools can analyze call recordings to identify instances where agents demonstrate active listening skills, empathy, effective problem-solving, or product knowledge. Having readily available quantitative behavioral data allows supervisors and coaches to correlate these behaviors with performance metrics, providing valuable insights into how behaviors drive the desired outcomes.  

Even better, AI-powered coaching solutions can provide real-time feedback to agents during customer interactions, alerting them to behaviors that may be impacting performance and providing timely suggestions for improvement in a way that no human coach can. This proactive approach enables agents to make immediate adjustments to their behavior, leading to more positive feedback and improved customer experiences. 

Finally, AI call center tools can facilitate continuous monitoring and analysis of agent behaviors over time, allowing supervisors to track progress, identify trends, and adjust coaching strategies as needed. By leveraging AI-driven insights, supervisors can tailor coaching sessions to address the specific behaviors that have the greatest impact on performance while driving continuous improvement and maximizing the potential for success in the call center. 

In this article, we’ve discussed some of the potential of AI tools in call centers. Next time, we’ll dive into some of these specific tools and how you can leverage them in your organization. Until then, please reach out if we can help you with any call center technology questions or visit our Artificial Intelligence site to learn more about our services.


Headshot of Kevin Able, RevGen Partners Principal Architect

Kevin Able is a Principal Architect in RevGen’s Digital Enablement practice.  He is passionate about delivering practical solutions that drive value to his clients.





A headshot of Jennifer Barton, a RevGen Sr. Consultant.Jennifer Barton is a Senior Manager at RevGen focused on aligning cross functional teams across organizations to ensure they’re meeting their goals.

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