How to improve call center coaching with conversation intelligence

Madeline Jacobson

December 6, 2023

When Brakes, a Sysco company and UK-based wholesale food provider, began analyzing 100% of their customer calls with Tethr’s conversation intelligence platform, their service leaders braced for resistance from their frontline agents. 

“We got our seatbelts on,” says Ellie Bird, Head of Sales and Services. “But a lot of the feedback we got was, ‘Actually, this is great.’’’ Brakes’ service leaders could use data from every customer conversation to inform their call center coaching, and agents could be confident they were getting objective feedback to improve their performance: a win-win. 

In general, call center agents want to do well at their jobs. And when their leaders coach them effectively, they’re more successful and stay with their company longer. According to a Gallup study, organizations that invest in professional development are 11% more profitable and twice as likely to retain their employees.

Call center coaching also has a positive impact on customers. Agents learn to communicate and resolve issues in the ways that best meet their customers’ needs, improving the service experience and increasing customer satisfaction. Greater customer satisfaction translates to greater loyalty, increased customer lifetime value, and a better brand reputation.

Unfortunately, many call centers struggle to provide effective coaching because their team leaders or quality assurance (QA) managers only review a few calls per agent each month. Feedback is often subjective and based on limited data, making it easy for agents to dismiss.

Let’s look at why coaching falls short and how call center leaders can improve it with conversation intelligence technology.

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The challenges of traditional call center coaching

The majority of call centers have a QA program intended to help them monitor compliance and coach their agents. Team leaders or QA managers are responsible for reviewing a certain number of calls per agent each month and completing an evaluation or scorecard for each call. Because this is a time-consuming process, managers typically evaluate only a small number of calls–about eight per agent each month, according to ICMI

There are several problems with basing call center coaching on such a small sample of interactions. If managers score their agents on only about 1% of their total calls, it’s almost impossible to spot trends in their performance–or to track improvements or declines over time. 

It’s also common for agents to dismiss feedback because they believe their reviewed calls aren’t representative of their performance. “When we were monitoring four calls per month, our agents would always end up saying to their team manager, ‘If only you’d looked at that one interaction instead of this one, I’d have gotten a better score,’” says Ellie Bird at Brakes.

83% of call center agents say they don’t believe their organization’s QA program helps them improve customer satisfaction (CSAT) or first-call resolution (FCR), two of the most important customer service metrics. Even worse: dissatisfaction with QA monitoring is one of the top drivers of agent turnover, according to research from SQM Group. 

Reviewing only a small percentage of agent calls isn’t cutting it, but hiring enough QA managers to review every call also isn’t realistic. (One of our customers, Thrasio, crunched the numbers and said it would take a team of 528 analysts to review all their customer conversations.) 

But businesses no longer have to rely on manual call reviews alone. Conversation intelligence technology can analyze every customer conversation and surface insights into both agent performance and the customer experience.

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How conversation intelligence improves call center coaching

Conversation intelligence is a category of software that uses AI to analyze the words and phrases in recorded conversations. Call centers use this technology to review their customer interactions and uncover actionable insights about agent performance and customer experience. Notably, some conversation intelligence solutions also let call centers automate their QA scorecards so they can track objective criteria across 100% of their agent interactions. 

By using conversation intelligence, call center leaders can:

  • Remove subjectivity from the call review process. All agents are evaluated on the same criteria tracked across every conversation.
  • Uncover trends in agent behaviors. By tagging and tracking agent behaviors across conversations, call centers can identify patterns and trends, such as behaviors correlated with negative CSAT scores or the top customer issues causing agent confusion.
  • Identify team-wide areas of improvement. Managers can see what behaviors or issues are the most challenging for their team, allowing them to set team-wide goals and organize focal point sprints.
  • Tailor individual coaching sessions based on conversation insights. Team leaders or QA managers can look at an agent’s performance across all their conversations and identify the top opportunities for improvement.
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Examples of effective coaching with conversation intelligence

Conversation intelligence software helps call centers track agent behaviors that are proven to increase dissatisfaction or negatively affect metrics like FCR or average handle time. It does this by analyzing and categorizing the language agents use and how it correlates to customer sentiment or operational metrics. Call center leaders can use these insights to prioritize opportunities for improvement and tailor their coaching to teams and individuals. Here are two examples of Tethr customers using conversation insights in their coaching:

  • Connexus Credit Union discovered their agents frequently used language that conveyed confusion as a stall tactic when looking up account information. Knowing that this was negatively affecting the customer experience, they trained their agents to use advocacy-focused language instead (e.g., “Let me access your account so I can tell you”). Within a month of training agents on this behavior, Connexus saw a 42% increase in team-wide use of advocacy language.
  • A dealership management software company used agent performance insights to plan month-long sprints focused on reducing negative behaviors (like powerless-to-help language) and increasing positive behaviors (like advocacy). Within the first three months of these sprints, they reduced their average handle time by 32 seconds, leading to savings of about $0.54 per call.

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5 tips to improve call center coaching

Make coaching a regularly scheduled activity.

Rather than waiting until an agent is struggling, schedule regular coaching sessions to review successes and challenges–and give the agent tangible things to work on. By using a conversation intelligence platform to automate your QA scorecard, you can free up more time to spend coaching your agents to deliver a great customer experience.

Highlight the purpose of giving feedback.

Coaching shouldn’t feel punitive. Make sure to explain why you’re giving the agent specific feedback–using insights from their conversations–and how they can use that feedback to improve their performance. Demonstrate to the agent how their work ties into company goals so they understand their impact.

Celebrate what each agent is doing well.

It’s easy for agents to become defensive when they only receive negative feedback. Conversation intelligence software can help you pinpoint what each agent’s strengths are so that you can celebrate those wins. By highlighting what your agents do well, you can also identify best practices to help other agents who may be struggling in those areas.

Work with agents to plan next steps.

At the end of each coaching session, collaborate with the agent on a plan to address their top areas for improvement. By doing this, you're allowing them to take ownership of their development and providing them with a clear roadmap for improvement. Make sure they walk away with clear action items, and check on their progress in your next meeting.

Make sure goals are clearly defined and achievable.

Work with your agents to set goals that are specific, measurable, and achievable. For example, instead of saying “Be a better advocate for our customers,” you could give them specific examples of advocacy language and set a goal to increase their use of this language by 20% in the next month. By providing clear targets and milestones, you ensure that your agents have a clear direction and know what is expected of them. This not only improves their focus and motivation but also enables you to track their progress and provide meaningful feedback to drive performance.

Final takeaways

Call center leaders might expect their agents to balk at the idea of using conversation intelligence software to analyze all their conversations. But, as the team at Brakes discovered, agents typically want to be coached objectively so they can feel more confident in their roles and have better customer interactions. Conversation intelligence eliminates subjectivity and gives managers data-backed insights to help their team members improve. This improves the agent experience and ultimately leads to a better customer experience.

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