How to increase customer satisfaction & productivity with Call Center Analytics?
While interacting with customers, contact center agents collect a huge chunk of information. However, these valuable insights get lost without the partnership between technology and experience. According to research, only 17% of organizations are actually putting call center analytics to use, while others are leaving a good deal of opportunities on the table.
But what is call center analytics and how can we put it to the right use for increasing customer satisfaction and improving overall productivity? Let’s check it in detail.
What is Call Center Analytics?
Many organizations claim that they have some sort of quality monitoring process in place. However, it is difficult to determine the effectiveness of parameters on assumptions. Call center analytics is the process of collecting, measuring, and reporting the performance metrics of any contact center.
Call Center Analytics provides a bird’s-eye view of different metrics, such as Average Handle time, calls in queue, call volume, CSAT rate, NPS score, and a lot more. Most often, this data is a part of weekly or monthly reporting and is limited to team leads and supervisors.
Modern contact centers leverage technology by creating an automated & centralized repository of all these analytics, providing them in real-time for access across the organization. With all these insights processed automatically, the call center workforce will not be impacted.
Currently, there are different generations, with distinct behaviors, as our customers. One size does not fit them all. Hence, it is important for organizations to not only analyze the words customers speak but also understand the sentiments behind how they’re speaking. Having a diverse customer group, it is important for brands to continuously fine-tune their call center quality assurance parameters.
Different Types of Call Center Analytics
With ever-evolving technology, organizations are going beyond the traditional call center metrics and adopting different forms of analytics, for specific performance improvement. Below are some of the major types of call center analytics.
1. Interaction Analytics
The significance of interaction analytics is identifying key trends as well as tracking agent performance. It includes real-time, as well as historical information of call center performance parameters, such as average handle time, first call resolution rate, call transfer rate, etc.
2. Speech Analytics
Speech Analytics is the process of analyzing customer interactions, by tracking positive and negative customer sentiments. With the booming conversational artificial intelligence and machine learning technology, call center quality analysts are no longer required to listen to entire calls. The entire process can be automated, and organizations not only analyze what customers say but also the intention behind it.
3. Customer Surveys
The post-interaction survey is a powerful analysis to measure customer engagement. It not only measures customer experiences delivered by a brand agent but also helps identify the specific areas of opportunities for improvement. Brands can utilize the survey results to further fine-tune their customer engagement process.
4. Predictive Analytics
Predictive analytics is a forecast of what will happen in the future based on historical data and trends. With the help of predictive analytics, brands can forecast future customer interaction volumes. This can help tremendously for effective workforce management. However, to start benefiting from predictive analytics, we must develop a good set of information to improve prediction accuracy.
There are also other types of analytics that modern contact centers use, which are self-service analytics, text analytics, and different business intelligence tools. We will discuss those in future newsletters.
Using Contact Center Data to Improve Customer Experiences
Customer interactions are a gold mine of data, although they don’t deliver much value individually. When we combine the insights derived through these interactions, we can identify customer behavioral patterns and understand customer sentiments. However, leveraging call center analytics requires a tech stack that makes critical metrics easy to understand.
Here is how you can leverage call center analytics to improve your overall performance.
Track & Improve Agent Performance
In order to deliver a consistent brand experience, it is extremely vital to track, monitor, fix, and improve agent performance. There are a variety of reports that can be generated through the latest call center quality monitoring software, such as Average Handle Time analysis, summary reports, activity reports, call states, etc.
The goal is not to micromanage agents, but to identify their strengths and weaknesses by helping them consistently improve their performance.
Boost Customer Satisfaction
Once we start monitoring agent performance, we can identify key opportunities for boosting customer satisfaction. The next step should be to understand customer sentiments and consistently fine-tune the customer engagement process.
We’re in a dynamic world with extreme competition, where customer preferences are rapidly changing. To stay updated with the latest trends, call center analytics can prove helpful.
With our 20+ years of experience in the call center domain, Etech has played an important role in digitally transforming the customer engagement process for some of the most well-known brands in the world. Contact Us for a FREE CONSULTATION on how we can help you.