What is call center analytics?
Call center analytics software gives call center managers, leaders, and executive teams crucial data that helps them evaluate agent performance and the quality of customer support.
This process typically includes collecting and evaluating customer data and incorporating common scoring methods like the Customer Satisfaction Score (CSAT), Net Promoter Score (NPS), or interaction-based metrics such as Average Handle Time (AHT) and First Call Resolution.
Additionally, some call center analytics tools provide their own metrics, such as Tethr’s Tethr Effort Index (TEI), and Agent Impact Score (AIS). Other analysis methods may include simply evaluating customer interactions, agent productivity, and customer retention over time, revenue, and average churn rates.
Call center analysis can be performed manually using overall business performance metrics or surveys, but the more common method in the digital era is to use call center software that automatically evaluates your customer conversations and implements automatic scoring tools and machine learning solutions that evaluate performance over time.
Overall, call center analytics is an essential part of running and managing a call center, since it provides a method for gauging customer service efficiency, determining pain points that are causing churn in your business, and tracking the customer experience.
Now that we’ve determined what call center analytics is, let’s take a moment to explore how it works and some tools for implementing it.
How do you analyze data in a call center?
Analysis of call center data can be done manually, or done with a tool like Tethr that tracks all data sources related to agent performance, issue resolution, and customer experience. The best of these types of tools will have several dashboards that allow you to customize what you want to report on and track changes in those metrics over time.
Common QA metrics for a call center
While this isn’t an exhaustive list by any means, here are a few of the most common metrics you’ll see related to measuring quality in a call center.
- First Call Resolution tracks how often call center agents resolve a customers’ issue in the first call, without the customer having to call back, follow-up with an email, or any other contact with your company.
- Average Handle Time tracks the average time spent on handling a call (talk and hold time). While it’s important to resolve customer issues quickly, it can also be challenging to solve all their issues in that time. Strike a balance!
- Average Abandonment Rate tracks how often customers hang up on you, or abandon a call while they’re on hold. Many customers are busy and don’t have time to wait around, so having a short wait time is key to helping them before they bail.
- Customer satisfaction scoring, often called CSAT, measures how satisfied your customers are with your company. Surveys are often employed here, as are polls, forums, and other ways of trying to discover customer opinions.
- Customer experience scoring, often called CES or TEI, measures how smooth your customer’s experience with your company is by looking at a wide range of variables within the call. This can often include metrics you might never have thought to include, like how the agent talks to the customer.
- Agent Turnover Rate: Another oft-forgotten metric, this metric tracks call center turnover rates, helping you identify why agents are churning and how to address that.
All these metrics are ways to analyze the data in your call center and track both agent performance and customer experience. While there’s certainly more you can measure, this list can give you a good idea of where to start if you’re looking to build up your call center analytics.
Once you collect and measure call center data, you can evaluate it.
How can I check my call center data?
In order to measure your call center analytics, you have to track that data. There are many popular call center tools out there for measuring and tracking call center data, but the best tools are conversation intelligence platforms.
These cloud-based software platforms will break down your raw data from calls, case, and chats using text analytics and voice analytics. They then break down the information into useful and parseable data on many of the above metrics that you need to measure and more.
For example, as an AI-powered conversation intelligence tool, Tethr offers a wide range of call center analysis options with our TethrRx platform. Capabilities of TethrRx include…
- Agent monitoring that delivers insights into your team’s performance across the call center. This information gives you insight into how each individual performs, as well as how your team stacks up in the marketplace.
- Customer reporting that ships insights from conversational data right to your dashboard, including details on the customer experience, what your customers want to see from you, and more.
- Churn diagnosis that casts a light on what business practices are causing your customers to churn, as well as the primary sources of customer dissatisfaction throughout your business.
- Sales insights into your sales team’s performance—including the most common sales objections and details on the best performing pitches.
- Cost analysis, so that you can always know what’s costing you money and what’s saving you cash. Find out where your operational costs lie and take action to bring down your spend easily and efficiently.
Checking your call center data can be hard when you don’t have the right tools for the job, but thankfully there’s a lot of really great tools on the market that can make your life easier. Say goodbye to unstructured data and data silos, and hello to customer satisfaction.
Types of call center analytics software
There are many types of contact center analytics software out there, and not all of them have all the capabilities listed above. It’s important to know what’s available and what your needs are, so that you can make the best decision for your team and your customers. As mentioned, thanks to innovations in automation, it’s possible to track and measure a lot more than we used to.
What you decide to measure depends on your team and your product. Here are some common types of call center analytics software, and the use cases they might be used in:
- Interactive Voice Response (IVR): This software responds to input from the customer on the phone or dialpad. Usually this software guides your customer through to the correct department, and collects analytics as it does so. Information is also available through pre-recorded messages.
- Automatic Call Distributors (ACD): Similarly, an ACD system guides your caller through a series of questions to direct them to the right department. This is less involved than an IVR system, but achieves a similar end goal. Many of these systems now also collect speech analytics insights.
- Call Accounting and Analytics: These systems are often older than the above two mentioned, and simply track call logs and time on call. This less refined method will get you basic insights, but won’t deliver as robust analytics.
- Predictive Dialer: This type of automated dialer places phone calls before agents become available, aiming to increase efficiency. This is often part of other tools now, but can be found as a standalone in some legacy systems.
- Conversation Intelligence: This is cutting-edge call center technology that delivers data-backed insights for sales and customer service reps based on customer conversations from every single call.
That’s a short overview of some of the most popular types of call center analytics software. Now it’s time to determine which one is right for you.
What kind of call center analytics software do I need?
The kind of call center analytics software you need will vary based on your goals and needs as a company - hat KPIs you track, how leadership evaluates ROI, and more. Does your team track customer experience, or just customer success? Do we care about agent retention? What’s the ideal call length? Do we want to turn the call center into a revenue-driver, or just maintain the status quo? While this may seem like an overwhelming quantity of items to weigh and consider, there’s really just a few questions that can make this decision easier.
We recommend asking the following questions:
- How big is your operation? The solutions available for enterprises often differ widely from those that would be useful for smaller operations in both cost and capacity. Sometimes, you can find a scalable solution that works for both.
- Do you personalize service for customers? Many call center analytics solutions use AI to augment human customer service in order to increase efficiency and better serve their callers.
- Is your service omnichannel yet? It should be! Supporting the customer across their journey is an integral part of customer service in this day and age. Many conversation analytics platforms provide analysis of chatbots, live chat, and emails along with phone calls.
- Are you taking into account the entire customer experience, or just a single element of it? A seamless and low-effort customer experience is an essential component of any call center analytics software that aims to truly reduce customer churn and improve operational efficiency.
All just a few things to consider when thinking about a call center analytics software. And of course, in any scenario, we recommend investing in an advanced call center analytics tool that specializes in conversation intelligence. Regardless of your individual call center goals, a conversational intelligence tool like Tethr can help you with all the above questions, issues, and more.
Why is call center analytics software important?
Call center analytics is the means by which call center managers, leaders, and executive teams analyze performance within the call center. Metrics tracked can include average handle time, first call resolution, overall customer satisfaction, and more. One of the best ways to perform call center analytics is with a state-of-the-art conversation intelligence tool.
If you’re interested in learning more about call center analytics and how they can improve your call center’s performance and operational efficiency, we’d love to chat.
Shoot us a line at email@example.com or book a demo to take our conversation intelligence platform for a spin.