How to improve first call resolution with AI

Madeline Jacobson

September 27, 2023

“I called about this yesterday, but I’m still having the same problem.”

“This is my third time calling you to try to get this fixed.”

No one in the customer service industry wants to hear those words. When a customer tells you they have called your contact center multiple times in an effort to resolve one issue, they’re likely feeling frustrated (and may be ready to stop doing business with you). In addition to creating a high-effort experience for your customers, repeat calls also drive up operational costs for your contact center.

Improving the first call resolution (FCR) rate–the percentage of customer queries or issues resolved through one call–requires contact center leaders to understand the root causes of repeat calls and address the ones in their control. Historically, this meant playing detective and trying to piece together insights from limited data sources, including call disposition codes, superficial verbatim feedback on customer surveys, and quality assurance scorecards for 1-2% of calls.

Now, however, your contact center can use AI-powered conversation intelligence software to listen to 100% of your calls and analyze the language agents and customers use. This helps you:

Get more detailed insights into the reasons for repeat calls
Identify the top repeat-call drivers
Uncover patterns in secondary issues
Find process improvements and agent coaching opportunities

Below, we’ll take a closer look at why FCR matters, how Tethr uses AI to help our customers reduce repeat calls, and tactics you can use to improve your FCR with conversation intelligence.

Why FCR is such an important call center metric

Customer service leaders rank first call resolution as the most important call center metric–and for good reason. A high first call resolution rate indicates that your company is delivering efficient service to its customers, which has a positive impact on the overall customer experience and your call center’s operational efficiency.

Reducing repeat calls can deliver significant cost savings, given that the average 3- to 4-minute customer service call costs around $2.70 to $5.60. And the money saved on avoidable repeat calls can be reinvested in other areas of the customer journey, allowing your business to continue improving its service delivery.

Improving your first call resolution also reduces customer effort, which has a direct impact on loyalty. According to research shared in The Effortless Experience, repeat contacts are the single biggest driver of customer effort, and 96% of customers who have high-effort experiences with a business report being disloyal. When customers have their issues resolved efficiently in a single call, they’re much more likely to view the experience as low-effort–and only 9% of customers with low-effort experiences report being disloyal.

How Tethr uses AI to analyze repeat calls and improve FCR

Tethr is a conversation intelligence platform that uses AI to turn unstructured data into actionable insights–including insights into repeat call drivers that may be dragging your FCR rate down.

Here’s a quick overview of how we use Tethr to conduct repeat contact analyses for our customers so they can improve their first call resolution.

We set a timeframe for tracking repeat calls (e.g., 3 days, 7 days) and use contact IDs (e.g., phone numbers or account IDs from an integrated CRM) to measure the rate of repeat calls during that period.
Tethr labels conversations that have a subsequent call or are a subsequent call. These labels serve as filters that our customers can select to see repeat call volume around specific categories. (Categories in Tethr are made up of phrases or utterances that indicate a specific topic or behavior.)
Tethr uses machine learning to look for patterns in conversation data and assign phrases to relevant categories. Our customers can view the top categories that occur in repeat calls or initial conversations that led to a repeat call. They can also look at the repeat call rates and top categories for individual agents.

A repeat contact analysis lets you answer questions such as:

What topics or issues are most likely to lead to repeat calls?
What secondary issues are customers bringing up on repeat calls?
What can agents forward-solve on initial calls to improve their first call resolution?
Which agents are struggling to resolve issues on the first call, and what additional resources or training do they need to improve?

Once you have answers to those questions, you can begin prioritizing process, policy, or agent coaching changes to improve your first call resolution rate.

3 tactics to improve first call resolution using conversation intelligence

Conversation intelligence gives you a much more detailed view of the customer experience than you could ever get from low-response CSAT surveys, agent-selected disposition codes, or a manual review of 1-2% of your calls. It allows you to get to the root causes of repeat contacts based on what your customers and agents are saying–and come up with a data-driven plan to improve your FCR.

1. Identify the topics with the highest repeat contact rate

When prioritizing tactics to improve your FCR, one of the first questions you need to answer is, “Why are our customers calling us multiple times?” In other words, what are the thorny issues that aren’t getting resolved on the first call?

Conducting a repeat contact analysis in your conversation intelligence platform can help you develop a stack-ranked list of the top issues leading to repeat calls.

Pro tip: When listing the top issues, pay attention to the repeat contact rate and the call volume.

While an issue might have a relatively low repeat call rate, you might find that it comes up a lot on calls and is therefore worth investigating. Conversely, you might uncover an infrequent issue that almost always leads to repeat calls and should be addressed.

Once you have your list, prioritize the top four or five issues, and select a sample of calls with these issues to review. Look for patterns, and start identifying areas for improvement. For instance, is there a topic that agents need to be better educated on? Is there a new product issue that you need to share with your product development team? Is there a knowledge base article that needs to be rewritten to reduce customer confusion?

2. Identify secondary issues and train agents to forward-solve

According to Matt Dixon, co-author of The Effortless Experience (and former Chief Research and Product Officer at Tethr), “Have I fully resolved your issue today?” is the worst question a customer service agent can ask. The question prompts customers to say yes, but in many cases, the solution provided by the agent doesn’t work the way the customer expects it to, or a related issue that the customer couldn’t have anticipated comes up a few days later–leading them to call back.

Conversation intelligence can help you pinpoint the most common secondary issues that customers bring up on repeat calls–and gain a deeper understanding of how they relate to the customer’s initial issue. You can use this information to coach agents on potential issues they may be able to forward-solve for customers, eliminating the need for a second call.

While it’s not efficient (or a good experience for the customer) to address every potential secondary issue on the first call, identifying the top issues discussed on initial calls and their top secondary issues will help you understand where your contact center can have the biggest impact in improving your first call resolution rate.

3. Uncover coaching opportunities for agents with low FCR rates

While you may address some of the drivers of repeat calls through operational changes or by taking a more proactive approach to educating customers, you’ll likely still see variation in FCR rate by agent. Some agents may simply be better at resolving issues on the first call than others; maybe they have been at the company longer and have a better sense of when to proactively address issues based on experience, or maybe they are better at asking probing questions to uncover secondary issues.

Conversation intelligence allows you to view individual agent performance through the lens of different customer issues and their rate of repeat contacts (i.e., the percentage of customers they spoke to who called back about the same or a related issue, even if they spoke to a different agent the second time). This enables you to see which issues specific agents may struggle to resolve on the first call so you can provide additional coaching or relevant resources.

You can also filter agent performance by specific behaviors, such as offering proactive guidance (e.g., “You can always schedule an appointment through our website in the future”) or using advocacy language (e.g., “I’m going to get this resolved for you”). This helps you see which behaviors your top performers are using frequently. With this information, you can go beyond anecdotal evidence about what is working well for your top agents and train all agents on the behaviors that are most likely to improve their first-call resolution.

Interested in diving deeper into how a conversation intelligence platform can help you improve your first call resolution?

Download our guide, Your contact center has a repeat call problem: How AI can solve it.

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