AI-powered call center coaching: What every manager needs to know

Customers are turning to chatbots and knowledge bases to answer their most straightforward questions, but the majority still prefer to talk to human agents when they have a complex issue—making call center coaching more important than ever.

“Agents are taking complex call after complex call,” says Simon Black, Chief Operating Officer of Creovai. “They’re struggling, and then they end up leaving the call center because they don’t have the tools to support them in their day-to-day job.”  

Unfortunately, traditional coaching—in which a supervisor manually reviews a handful of their agents’ calls and shares feedback in a coaching session—isn't cutting it. Manual quality assurance (QA) programs review less than 5% of all call center interactions on average, leaving managers with large blind spots about their agents’ performance. Agents may feel the calls selected for a coaching session aren’t representative of their overall performance, and supervisors may struggle to find meaningful opportunities for improvement based on such a small sample size.

AI-powered call center coaching overcomes these limitations. Using machine learning and generative AI, coaching technology can analyze every interaction and provide real-time guidance to agents, making high-quality coaching scalable and personalized. (Think of it like having an expert coach sitting in on every call, using their extensive knowledge to improve call outcomes.)  

How AI coaching works, during and after the call

There are two call center software categories that power AI coaching: real-time agent guidance and conversation intelligence.  

Real-time agent guidance

Real-time guidance platforms listen to live calls (capturing audio and transcription), use AI to identify what’s happening, and offer in-the-moment, context-based prompts and workflows. They support coaching through features such as:

• Dynamic checklists—AI analysis allows the software to display checklists that adapt as the conversation unfolds, keeping the agent on track no matter the scenario.

• Real-time alerts—If the software detects language that could signal a potential compliance breach, churn risk, or anything else the agent needs to be aware of, it can trigger a relevant pop-up with information about what to do.

• Real-time coaching prompts—You can train the software to deliver relevant coaching prompts, such as save offers during cancellation calls or rebuttals during sales calls, based on the approaches that have been most successful in past interactions.

• Unified desktop view—The software’s UI brings everything the agent needs to help the customer, including workflow steps, coaching prompts, and information from integrated systems like a CRM or knowledge base, into a single desktop view.

• Automatic data capture—The system can use AI to automatically fill in CRM fields, generate a call summary, and answer agent questions about the interaction, providing valuable documentation that can inform future coaching and real-time guidance.  

Post-call analytics & conversation intelligence

Conversation intelligence platforms use machine learning to analyze every call center interaction, identify and categorize key events, and surface trends and insights into customer and agent behaviors. You can use these insights to inform agent coaching sessions or prompts in your real-time guidance platform. Features may include:

• QA automation and custom scorecards—You can build a custom QA scorecard in the platform (and choose how you want to weight different criteria), and the software will automatically complete the scorecard for every conversation. This can help you coach your agent based on their performance across 100% of their interactions.

• Insight categorization—The platform may go beyond basic QA categories and track call reasons, friction points, product or competitor mentions, and other categories that can be determined based on the language used in the call. This can help you spot knowledge gaps or issues agents need additional coaching on.  

• Predictive scoring—The platform may use advanced AI models to predict things like customer satisfaction, effort, and sentiment based on the full context of the conversation. This can give you a better idea of how agent behaviors impact the customer experience, allowing you to better tailor your coaching.

• Root cause analysis—AI and statistical modeling can determine the factors impacting metrics like average handle time and first call resolution, enabling you to prioritize the coaching areas that will have the biggest impact on call center KPIs.

• Coaching hub—Some conversation intelligence platforms also include coaching hubs, which consolidate call recordings, coaching session notes, goal tracking, and action plans in one place—reducing the time you spend prepping for coaching sessions.

Why AI coaching must be on your radar

AI-powered coaching software can automate 80% (or more) of your QA process, identify coaching opportunities you might have otherwise missed, and guide agents to more successful call outcomes in real time. It won’t replace you, but it can put your call center data to work to improve agent performance—while giving you more time to focus on developing your team and working on strategic projects.

Scalability & consistency

It’s easy to end up delaying or canceling coaching sessions, especially when it feels like you have a million other items on your to-do list. AI coaching technology ensures agents get regular feedback based on all their interactions. Conversation intelligence software analyzes interactions based on what customers and agents say, allowing you to track QA scoring criteria and other important agent behaviors. This surfaces opportunities for improvement that you can discuss in coaching sessions and build into your real-time guidance software so agents always get relevant coaching during their calls.  

Data-backed coaching opportunities

AI is great at sifting through and making sense of large data sets. Conversation intelligence software can uncover your top coaching opportunities from your interaction data, helping you get more targeted with your coaching feedback. You can also use that data-driven feedback to inform your real-time workflows and prompts, increasing the likelihood of positive call outcomes.

Efficiency & cost savings

Agents equipped with AI guidance resolve calls faster and more accurately. (For example, Creovai customer NRTC reports that real-time agent assistance helped them reduce their average handle time by 42 seconds.) On the supervisor side, conversation intelligence can significantly reduce costs by automating QA (Creovai customer Thrasio reports saving $260k annually). Together, these solutions help call centers operate more efficiently while saving money on training and coaching.

The impact of AI-powered call center coaching

Higher first-call resolution rates

With the right information immediately available, agents solve more issues on the first try. Agents can also get coaching prompts to help them proactively address secondary issues (e.g. offering account add-ons) that customers tend to call back about.

Lower average handle times

By bringing everything the agent needs into one interface, AI coaching software reduces the time agents spend searching for information. You can also identify your agents’ biggest knowledge gaps with conversation intelligence software and address them with real-time prompts, helping agents resolve issues faster.

Increased customer satisfaction

Quick, accurate service boosts customer satisfaction. And higher satisfaction increases the likelihood that customers will keep buying from you, increasing the average customer lifetime value.  

“There’s no doubt that Creovai’s real-time technology plays a crucial role in driving frictionless and timely resolutions to much of the support we provide.” -Roddy Forfar, Managing Director, Aquarius

Faster onboarding

Onboarding—especially for inexperienced agents—can be time-consuming, driving up operational costs. By some estimates, it can take new agents four to eight months just to meet their call center’s minimum performance standards. Real-time coaching helps new agents get on the floor faster, helping keep your call center fully staffed and reducing onboarding costs. One Creovai customer, 360insights, reduced their training time by 23% thanks to real-time guidance.

Higher agent confidence and retention

In-the-moment coaching makes agents feel supported, helps them do their jobs more efficiently, and reduces the stress common in the call center industry. Additionally, conversation intelligence can help track areas where agents are improving, enabling you to highlight these positives in their post-call coaching sessions. Real-time and post-call coaching backed by data improves the agent experience and reduces the risk of attrition. Creovai customer BCU reduced their agent attrition from 40% to 10% in part by establishing data-driven employee recognition and coaching programs.  

Proven coaching ROI

AI turns coaching from a “nice-to-have” into a measurable driver. You can use conversation intelligence to link coaching directly to outcomes (e.g., showing that agents who followed AI suggestions had higher sales or CSAT scores). This makes a clear business case for continued investment.

What to look for in AI tech for coaching

When evaluating AI software for agent coaching, keep these factors in mind:

• Unified vs. point solutions—Look for platforms that combine real-time coaching, conversation intelligence, and QA in one suite. Creovai, for example, integrates all these so that insights flow seamlessly from post-call analysis into live guidance.

• Customization and flexibility—Ensure the solution lets you tailor workflows, checklists, and scorecards to your business requirements. The platform should be vendor-agnostic (i.e., it works with your phone system, CRM, knowledge base, etc.).

• Depth of insights—Look for true AI (machine learning and generative) over simple keyword triggers. Creovai’s use of generative AI allows it to handle open-ended questions (e.g., “What steps did the agent take to troubleshoot the issue?”) and create context-aware scripts.

• Ease of deployment—How quickly can you get the real-time guidance and conversation intelligence software up and running? And how easy is it to build scripts, generate reports, or find agent coaching insights? A low-code, user-friendly interface will help you get value from the platform faster—and prevent IT bottlenecks when you need to make changes.

• Proven results—Look at case studies and success metrics on the vendor’s website. See if there are specific case studies that address the coaching challenges you’re trying to solve.

• Security and data privacy—Ensure the vendor provides reliable support and that their use of AI meets privacy regulations. If your calls have sensitive data, confirm the platform’s audio capture is secure.

Uplevel your coaching with AI

There are a lot of potential AI use cases for the call center, making it hard to know what to invest in now. The best thing to do is to ask yourself, “Where can AI increase productivity and deliver the fastest return on investment?” For many call centers, AI-powered coaching is a great place to start.

AI coaching helps you harness one of the most valuable resources your call center has—your conversation data—and turn it into agent guidance. Agents get the support they need to resolve even the most complex customer issues, leading to better outcomes for your customers.  

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