With the rise of new customer support channels such as live chat and messaging, one would expect the number of phone calls to decrease. But this isn’t the case—66 percent of customers still prefer to use the phone for real-time support.
Efficient inbound call centers are the backbone of excellent phone support. Managers can use call center metrics to track the quality of support customers receive and the productivity of agents. From there, teams can identify concrete ways to meet call center goals and showcase wins to higher-ups.
The problem is that there are so many potential call center metrics to analyze—and tracking every metric isn’t always feasible as a busy manager. The key is to prioritize the data that is the most critical for understanding call center performance.
What are call center metrics?
Call center metrics are KPIs (key performance indicators) that measure the success and efficiency of a call center. Call center metric examples include time to resolution, number of tickets solved in a day or week, average handle time, schedule adherence, and talk time.
The best call center metrics for measuring success
There are 12 important metrics every call center manager should monitor to evaluate agent performance and the quality of the customer service they’re providing.
Average talk time
Talk time refers to the number of minutes and seconds that elapses between an agent answering the phone and hanging up. Although sometimes confused with average handle time, talk time is different in that it doesn’t account for hold time or time spent following up after a call has been completed.
To calculate average talk time, divide the total amount of time spent talking to a customer on the phone (in minutes and seconds) by the total number of calls handled.
Average talk time helps managers gauge their team’s ability to handle different types of customer service scenarios. For example, say a manager is analyzing the performance of an individual support agent. That agent’s average talk time is five minutes or less. But this month, the agent had a few calls that lasted more than 10 minutes. Reviewing those 10-minute-plus call recordings can reveal what types of calls that agent may be struggling with. Or, the lengthy calls might point to a bigger problem, such as an underlying issue with the product or service.
Agents deal with a wide variety of calls—some more stressful than others. Average talk time can help uncover the kinds of inquiries that trip up agents the most. Develop knowledge-base resources or targeted training that improves agents’ ability to address similar calls more quickly in the future.
Note that there are exceptions, though. For instance, average talk time isn’t always a mark of success at retail and lifestyle brand Magnolia. The reason: Approximately half of the calls are from fans who call simply to talk or share stories, drawn in by the company’s relatable founders and TV stars, Chip and Joanna Gaines. The lesson: Call center KPIs should always take the unique qualities of the business into account.
Missed and declined calls
Missed calls are when an agent doesn’t answer the phone, so the customer is sent back to the queue. Declined calls mean the agent actively refused the call, most likely because they were on the line with another customer. A large number of missed and declined calls naturally leads to low customer satisfaction rates.
Many call center software tools will automatically track missed and declined calls. With Zendesk, managers can view this metric by individual support agents.
Keep customers happy by identifying the root cause of these missed and declined calls. One common reason is understaffing. Look for spikes in missed and declined calls; if they tend to occur during specific shifts or hours of the day, it could indicate that there aren’t enough agents available during high-volume call times.
Another issue may be the call center software you’re using. For instance, some tools have limits on the number of calls that can wait in the queue at any given time. Check the software license to see if your plan has a cap. If it does, it’s possible that live calls are declined because the system isn’t equipped to handle the volume of calls coming in.
Once managers can pinpoint why calls are being missed or declined, they can identify the systems or personnel needed to resolve the issue.
Transfer rate is the percentage of inbound calls that agents end up transferring to another team member or department.
To calculate this call center statistic, divide the total number of calls transferred to another department or agent by the total number of calls handled. Then, multiply the result by 100.
A high transfer rate could indicate that callers are reaching the wrong first-touch agent. In this case, the call center’s internal routing system may be the problem. At the end of a call, encourage agents to ask the customer whether they found the IVR (interactive voice response) system confusing or challenging to navigate. If so, reducing the transfer rate could be as simple as reworking the IVR menu options to make the system more user-friendly.
If calls are being routed to the right department and the transfer rate is still high, it might indicate a lack of training. Measure the average transfer rate across the entire call center. Look for any outliers—agents who routinely surpass the average percentage—to identify employees in need of additional training or resources.
Call abandonment rate
Call abandonment rate is a call center metric that reflects the total number of customers who hang up while waiting to speak with an agent.
If many customers are hanging up before they reach an agent, a feature to request a callback might improve the experience. With this system, customers can still talk to the next available representative without waiting on hold.
With some call center software, like Zendesk, agents can automatically create tickets from abandoned calls (provided a callback number is available). This can help agents save potentially poor customer experiences by following up with customers who left the queue.
Average speed of answer
Average speed of answer, or ASA, is the total time it takes a customer to reach an agent once they’ve been routed to the right department and placed in the queue.
Managers use the ASA metric to learn how long it’s taking their average agent to answer and solve inbound calls. A high ASA might indicate that agents lack the training or knowledge to answer customer inquiries in a timely manner. A high ASA could also suggest that the call center is understaffed. If average talk time is low but ASA is high, the call center might not have a sufficient number of agents needed to answer the volume of calls coming in.
To calculate average speed of answer, divide the total amount of time customers spent waiting in the queue by the total number of calls answered.
According to research by Call Centre Helper magazine, the industry standard is to answer 80 percent of calls in 20 seconds or less. If agents are struggling to meet this benchmark, it might be time to enhance the onboarding process or provide ongoing training programs. Or, you may need to hire additional call center agents to maintain service level standards.
Average first response time
Calculate this metric by dividing the total of all first response times by the total number of calls. Make sure to exclude calls that come in after business hours, though.
Sarah Reed, former call center leader and now senior director of content and event marketing at Zendesk, explains that average first response time is a key metric that shows whether “you are getting to customers quickly—and not [sending] a canned generic response.”
Ensuring customers don’t wait too long prevents them from hanging up in frustration and leads to higher satisfaction. After all, providing speedy, helpful responses shows customers that you care about them and prioritize their needs.
A high average first response time could indicate that there are too many calls for support agents to handle. Increasing the number of agents available during peak hours can help you boost agent productivity and provide faster support to callers.
Customer effort score
Customer effort score (CES) gauges how much effort customers put in to reach a support agent and get their issue resolved. As Reed explains, “CES indicates how hard it is for a customer to get their needs achieved—be it because of process, product, or tools.”
Data from Gartner shows that CES has a direct impact on customer loyalty. The report found that 96 percent of customers who expend a lot of effort when interacting with businesses became less loyal to the brand. On the other hand, only 9 percent with a low effort experience became less loyal.
To determine CES, begin by conducting a survey to ask customers about the ease of their interaction. The response choices should range from “very easy” to “very difficult.” It’s also a good idea to include space for any optional comments. The most optimal time to send a CES survey is after a purchase, subscription sign-up, or customer service interaction.
After getting the survey results, add up the score ratings and divide the sum by the total number of responses.
A high CES may point to a problem with your team’s communication processes or tools. Customers might have to jump through hoops and listen to endless voice prompts before reaching an agent. If this is the case, reduce the steps customers have to take to speak with agents. Also, providing other contact options—like live chat, email, and messaging—can help reduce wait times.
Agent effort score
Agent effort score (AES) measures how easy it is for agents to provide support for their customers.
According to Reed, AES pinpoints where agents meet challenges that hinder them from delivering the best support experience to customers. It’s the only call center metric that provides insight into agent performance from the agent’s perspective.
To calculate AES, carry out a survey asking agents to rank how easy it is for them to support customers. Then, calculate the average of those scores by adding them up and dividing the sum by the number of respondents.
You should also speak with agents to understand which tasks or processes are the most time-intensive for them. You can take action based on their responses and the trends you’re seeing.
For example, agents might not be able to track customer information because they don’t have access to those details. This makes it difficult to find the proper context needed for support interactions, leaving agents scrambling for relevant information. In such a case, investing in customer service software can set your team up for success. With a centralized workspace and customer data at their fingertips, agents will have the context they need to efficiently provide support and personalized experiences.
Total resolution time
Total resolution time measures the average length of time it takes for agents to resolve a customer issue. Just like average first reply time, it gauges the speed of support responses within specific time frames. According to Reed, total resolution time shows whether agents are “efficiently responding to customers with correct answers.”
To calculate a call center’s total resolution time, divide the total time of all resolved interactions by the total number of tickets solved.
When faced with a high total resolution time, take a deep look into what may be slowing agents down. Are they having a series of back-and-forth conversations? If that’s the case, agents might not have enough information about the customers, so make sure they know how to access your CRM and find details about past interactions. Are agents constantly dealing with complex customer issues? If so, there might be problems within your product or service that need solving.
Average hold time
Average hold time (AHT) is the average amount of time customers spend waiting on the phone before connecting with support agents.
Calculate average hold time by adding up all customer wait times and then dividing that number by the total number of calls.
It’s best to keep your call center’s AHT to the bare minimum—customers do not like to be kept waiting. According to data from the Zendesk Customer Experience Trends Report, over 50 percent of customers expect their phone calls to be answered in under five minutes.
Donovan Steinberg, director of customer success at BombBomb, adds: “The amount of time customers wait has a direct impact on the support experience.”
Long hold times may indicate you need more agents to handle the volume of incoming calls. Or, perhaps you need to beef up your customer self-service options. Talk to support agents and ask them to identify frequently asked questions or common customer issues, then update your knowledge base accordingly. This can ease support agents’ workload and enable them to help more customers more quickly. Look at individual agents’ average hold times, too, as it might signal a need to retrain certain agents to serve customers efficiently.
When an agent ends a call with a customer, it doesn’t mean their job is done. They still have to carry out some tasks to ensure that the customer is fully satisfied or that the problem is completely resolved. These activities include:
—Recording outcomes of the conversation
—Assigning tasks to other departments
—Sending resources to customers
—Sending follow-up emails
Wrap-up time is the amount of time it takes an agent to finish these activities after a call. To calculate this metric, subtract total hold time and total talk time from the total amount of handle time. Then, divide that result by the total number of customer calls.
A high wrap-up time shows that agents are unavailable to take incoming calls, which has a negative effect on performance metrics.
Call center managers can reduce wrap-up time by automating post-call activities, such as logging customer information, with a CRM. They can also create FAQ pages and other resources that agents can quickly send to customers after a call.
CSAT + QA
Customer satisfaction (CSAT) scores gauge how satisfied customers are with the support they received.
CSAT is calculated using customer satisfaction surveys. Questions could be framed in different ways, such as:
Were you satisfied with ___? (Yes/No)
On a scale of 1–10, how satisfied are you with ___?
How would you rate your satisfaction with ___? (Unsatisfied, Somewhat Satisfied, Very Satisfied)
To get the CSAT score, divide all positive responses (e.g., somewhat satisfied and very satisfied) by the total responses collected, then multiply that result by 100.
Quality assurance (QA) scores measure the quality of an agent’s interactions against a QA scorecard. The call center manager listens to an agent’s conversation with a customer, and then fills out the scorecard to grade different aspects of the interaction.
“QA is like a meta-metric,” says Isaac Lee, demand generation manager at MaestroQA. “The health of each other metric you choose to track shows up in your QA scorecard—and when one of them falters, you immediately know where and how to fix it because a QA analyst has identified that area of opportunity and flagged it.”
To determine QA scores, managers assign points to specific questions related to customer interactions on the scorecard. The final score is a percentage of the total points an agent earns.
After collecting CSAT ratings and QA scores, review customer interactions to see if your agents met internal support standards. For example, did the agents use proper grammar? Did they speak to customers in the right tone of voice? How fast did they solve customer issues?
Managers who view specific CSAT ratings in tandem with QA scores can pinpoint areas of improvement in their call center operations. As Reed points out, combining both metrics can help you “clearly correlate your agent expectations to the needs of the customer.”
Boost customer satisfaction by monitoring key call center metrics
Because most customers still prefer to resolve their support issues over the phone, building and improving call center performance should be a priority for any business. Use the key metrics outlined above to gain the big-picture insights you need to transform your call center.
But as you may already know, noting metrics manually is time-consuming and often error-prone. A CRM like Zendesk can automatically track these metrics to save you time. Integrate our CRM with your call center to collect accurate analytics and insights that help you improve your phone support and increase customer retention.