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Sara Yonker
July 20, 2022
January 23, 2023
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.
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.
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.
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.
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…
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.
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:
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.
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:
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.
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 info@tethr.com or book a demo to take our conversation intelligence platform for a spin.