Call center analytics play a vital role in the success of your organization.
Call center performance depends on the kind of experience being provided. Whether customers reach out to take care of a routine task or with a complaint, they expect to find answers with ease. When they don’t, they’re left with negative impressions that reflect on your brand and stick for a while.
Call center analytics let you measure the efficiency of your customer experience, the effectiveness of agent workflows, and provide gap analysis for the entire operation.
And the great news is, you can monitor just about every aspect of your call center.
Like football teams, call centers use “footage” of past games to improve their future strategy. The only real differences are the tools and metrics used to analyze the play.
Here we explore which call center analytics best practices you should focus on and how they can help you keep your call center reach peak performance.
Types of call center analytics
Every interaction is an opportunity to collect data that can help you improve call center efficiency. But human conversation is complex and when you’re fielding hundreds of calls a day, mining for deep insight can be a gargantuan challenge. This is where AI and machine learning become a call center rmanager’s best friend.
Phone calls contain some of the most valuable data in the call center. Speech analytics lets you mine that data. Advances in artificial intelligence, natural language processing, and machine learning have made this process more efficient than ever.
Text analytics has risen in popularity thanks to the number of channels call centers use to communicate with customers. Customer interactions now happen on social media, SMS messages, and live chat. Text analytics makes sure valuable data from those conversations isn’t overlooked.
Past performance measurements like wait times, first-time call resolution rates, and abandonment rates fall under predictive analytics. In depth, the review provides insight into areas that need improvement.
You can tailor the services you offer your customer by meeting them where they already are. Cross channel analytics help you determine where that is.
Call Center Analytics Best Practices
Call center analytics best practices can be divided into three categories: agent, customer, and business performance.
Agent analytics tells you something about your agents. They give you insight into their knowledge base, emotional intelligence, and overall engagement.
Call monitoring and scoring
Call center managers can deliver objective performance evaluations by leveraging call monitoring and scoring. Driven by speech analytics, it can help you determine a conversation’s emotional tone, how to target keywords were used, and agent performance.
This data can be used to:
- Improve customer experience.
- Learn what knowledge agents might lack.
- Create tailored learning opportunities.
- Train agents on hard to teach skills like empathy, active listening, and using positive language.
An agent’s desktop is their access point to all the tools available to them. Agents need to be able to utilize it in the fullest sense.
Desktop monitoring is a useful performance management tool. It lets you follow along with agents’ processes during customer interactions.
With desktop monitoring you can:
- Make sure call center agents are knowledgeable of your system.
- Train agents on system tools.
- Empower agents to leverage the technology available to them.
This has everything to do with what kind of experience your customers are having. Customer analytics tell you about customer service level, satisfaction, and preferences.
The amount of times your customers try to reach you but hang up before they are connected to an agent, live or virtual, is the abandonment rate.
A low abandonment rate is a sign of a healthy call center. It means that more of your customers’ needs are being met, and fewer are leaving frustrated.
When analyzing your abandonment rate ask yourself:
- When are calls being abandoned?
- Why are calls being abandoned?
- How can I decrease my abandonment rates?
Customer satisfaction survey scores (CSAT)
Customer satisfaction surveys are one of the most widely used call center metrics, and rightfully so. They are a chance for customers to tell you directly about their experience and can provide deep insight. CSAT surveys can tell you:
- Your customer’s preferences.
- Customer satisfaction level.
- How to correct mistakes.
First-time call resolution rate
First-time call resolution rate is how often your customer’s inquiry is resolved during their first interaction with your call center. Higher first-time call resolution rates indicate greater customer satisfaction.
Increased first-time call resolution rates can also decrease your overall call volume. Customers that have to call back multiple times for the same issue contribute to higher call volumes and can have a severe effect on the efficiency of your call center.
Analysis of first-time call resolution rates gives you insight into how your system is performing as a whole and where you need to make adjustments. If you have low first-time call resolution rates try to:
- Find out why agents are unable to resolve the call the first time around.
- Route your calls more efficiently.
Average handle time
Average handle time (AHT) is the average amount of time it takes to complete each call. It includes hold time, talk time, and after-call work time.
Measuring AHT helps:
- Identify inefficiencies in your call center.
- Have more productive conversations.
- Streamline the customer service process.