Vital Customer Service Call Center Analytics Metrics to Track

Woman sitting at computer analyzing customer service call center metrics

Measure, analyze, plan, act, and repeat. These are the five broad steps to improving your customer service call center’s performance on a day to day basis.

Since measuring call center analytics metrics is the first step in improving performance, the question for most call center managers is: “what metrics should I be measuring?”

There are many metrics that call centers can track, but many of these metrics can be misleading.

For example, call centers often track metrics such as average handle time. The problem with this metric is that average handle time isn’t always under the phone agent’s control. Some issues simply take longer to resolve, and some customers require more attention and care than others.
With this in mind, here are some of the best call center analytics metrics to track for customer service call center:

#1: First-Call Resolution Rate

One of the most important aspects of any customer service operation is the ability to handle a customer’s needs during their first call. A high first-call resolution rate is a strong indicator of other metrics such as positive customer experience and phone agent skills.

Repeat customer service calls waste time and resources, reducing productivity for your call center.

#2: Contact Quality

An important part of the customer experience for a call center is the contact quality, or phone agent performance. Phone agents that use strong interpersonal skills can strengthen customer relations, saving at-risk accounts or increasing the value of current customers.

Unlike other metrics, contact quality is difficult to measure via traditional means. Analytics solutions such as speech analytics can capture what was said on a call, but not how it was said. This lack of context for customer interactions makes assessing contact quality difficult.

There are solutions to this, however. One solution is to use predictive voice analytics to analyze how phone agents are interacting with customers. By collecting data on a phone agent’s emotional behavior and tone, the task of assessing overall contact quality for calls is made much easier.

That predictive voice analytics automates this process for 100% of all your customer calls allows for far more meaningful and thorough assessments that take into account an agent’s complete performance profile.

#3: Agent Turnover

The customer service call center industry suffers from a very high rate of attrition. According to some estimates, call centers will cycle through about a third of their phone agents every year.

High turnover is a problem because it means more time and capital spent on recruiting & training new agents, as well as lower productivity while new agents learn the ropes. Especially high turnover can be an indication of other problems in the call center that may need to be addressed.

#4: Agent Improvement Over Time

Call centers need to continuously improve to remain competitive in a crowded industry. To this end, many call centers focus heavily on training phone agents to improve call quality. Tracking how much individual phone agents improve over time is critical for assessing the effectiveness and ROI of training expenditures.

#5: Employee Engagement On Customer Calls

Employee engagement sounds like an abstract metric to measure, but it can have a significant impact on other metrics such as call quality and resolution rate. Engaged, attentive employees tend to be more proactive and attentive on customer calls, catching details and finding solutions that more passive, disengaged phone agents would miss.

However, this is another metric that is incredibly difficult to assess using traditional analytics solutions. Typically, such assessments would need to examine several metrics, such a first-call resolution, handle time, adherence to schedule, and post-call time management.

Predictive voice analytics simplifies tracking this metric greatly by creating automated analyses of phone agent behavior and tone. This information is highly useful for identifying phone agents who speak in a bored, passive tone from those who are active participants in a conversation.

These are just a few of the metrics that customer service call centers can track to help improve their day-to-day operations.

 

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