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Using Call Center Analytics To Improve Customer Experience

illustration of a call center manager presenting call center analytics

In today’s competitive business landscape, it’s more important than ever for companies to provide a responsive, relevant, and friendly customer experience. If you’re looking to boost customer satisfaction and retention, using call center analytics to study the effectiveness of your customer service support is essential.

Data analytics provide important call center stats to help you manage and troubleshoot improvements in the customer experience.

Let’s learn more about call center analytics, why you should use it, and more.

What Is Call Center Analytics?

Call center analytics entails analyzing call center data such as call transcripts which are generated by contact centers. Data is gathered from all client interactions, analyzed, and converted into useful insights.

Call center data analytics refers to the methods and tools that companies employ to generate these insights. These insights then become the basis for building and modifying customer-centric strategies for any type of call center.

Types of Call Center Analytics

To make call center metrics analytics and reporting work for you, it’s important to know about the different types of call center analytics.

Interaction Analytics

Interaction analytics refers to real-time and historical performance data of your call center agents. Some metrics that this type of analytics covers are response and hold times, abandoned calls, resolution time, and call transfer rates.

This type of analytics is useful for identifying trends, but can also be used to track the performance of individual agents.

Speech Analytics

Speech analytics entails collecting data by analyzing previous voice call records to determine how customers are feeling. It can involve sentiment analysis which takes a look at voice timbre, the language used, how quickly the customer is speaking, and the amount of stress reflected in their voice.

Businesses can then use the information to identify flaws in current scripts and replace them with more effective lines.

Text Analytics

Text analytics allows companies to analyze not only documents but also social media comments, posts, and other conversations about the platform’s brand. Text analytics works very well on platforms like Facebook, Instagram, Twitter, and LinkedIn. It can also determine whether the chat is favorable or negative based on the mood of the participants.

Desktop Analytics

What are agents doing at their computers during working hours? This is the question that desktop analytics provides an answer to. Desktop analytics provides insight into workflow and process inefficiencies for agents. It can also reveal security vulnerabilities that must be addressed and non-compliance with established protocols.

Businesses use desktop analytics to examine an agent’s performance, working methods, and activities to guide and assist them in improving their performance. Call center desktop analytics record inefficiencies and enable significant feedback on agent performance via real-time call monitoring. By keeping tabs on interactions in real-time, desktop analytics can analyze the productivity of contact center personnel as well as the systems they use.

Customer Polls/Surveys

Post-call surveys let you find out more about your customer’s experience. It involves automatically sending satisfaction questionnaires to customers to learn how they felt about the support they received.

Predictive Analytics

Predictive analytics is one of the most widely used and sophisticated techniques in the call center industry.  Using predictive analytics, agents can assist customer service departments in resolving issues by translating previous data into useful insights.

How? Before phoning a consumer, agents can see their information and call history. Predictive analytics can assist customer service departments in resolving current issues using historical data. Your company can use predictive analytics to foresee potential problems, add them to an events calendar, and come up with a solution.

Cross-Channel Analytics

Some people prefer a chatbot while others choose to tweet their problems. There are also customers who prefer to have more personal contact with agents over the phone. With the use of analytics software, you can perform a complete analysis of all of these platforms and adapt the consumer experience accordingly.

Cross-channel analytics examine data across different channels to provide a complete view of your customer’s journey. They assist in determining which communication platforms your clients prefer and how each platform is used. You’ll need a program that integrates with all of your platforms if you want to do cross-channel analysis.

Self-Service Analytics

Chatbots, anyone? Once set up within an organization’s technology infrastructure, self-service analytics such as chatbots require little to no human intervention. Self-service analytics can help a contact center lower the risk of human error and reduce the volume of inbound calls. It means lower overhead expenses and less pressure on agents, allowing them to engage with customers more effectively.

Why Is Call Center Analytics Important?

Call center analytics has many benefits to the customers, the agents, and the business itself.


Call center analytics promotes a data-driven culture. It can also be used during recruitment. To identify top talent, you can focus on the performance indicators that your best support agents or sales reps share. Companies can also use it as a basis for awarding performance-based bonuses since it makes performance measurable.

Improve Agent Performance

Call center analytics can help you evaluate agent performance. It can reveal where an agent excels and where they need additional assistance. They also allow companies to identify top performers objectively.

With it, businesses can determine the best ways to structure teams and operations to deliver optimum outcomes. Moreover, businesses can uncover inefficiencies and time-consuming tasks. This increases agent performance as well as the overall productivity of the company.

Boost Efficiency

The goal of establishing a call center is to have a dedicated group of employees who can prioritize the needs and wants of your clients. However, if your call center personnel are overworked due to excessive call volumes and understaffing, they will be unable to do so successfully.

If this happens, there will be longer wait times, lower rates of resolution, and higher customer turnover. Call center analytics can avoid this by predicting when large call volumes are likely to occur such as around the holidays or during product launches. By leveraging analytics, businesses can rapidly adapt to changes in demand and have enough people to handle all of their inbound calls.

Boost Conversion Rate

An effective call center analytics platform can boost conversion by predicting which matters are of interest to customers based on demographics, behavior profiles, and purchasing history. As a result, agents can recommend certain products or let customers know when items they might be interested in are on sale. It can also help determine the most effective outbound call techniques. For example, contacting leads in the afternoon may result in higher conversion rates than calling leads in the morning.

Get Your Team on the Same Page

Call center activities frequently function separately from other departments. Call center analytics can help customer support departments remain connected with relevant data from other teams. Each department can then learn how they affect each other by making information available across teams.

Determine Training Requirements

Some data analytics systems use artificial intelligence to understand employee behavior based on voice. This form of optimization will go a long way in improving the functionality and effectiveness of a call center. You can rapidly determine which soft skills an employee lacks and adjust your training programs accordingly.

How To Use Call Center Analytics Data To Improve the Customer Experience

According to Microsoft’s 2017 global customer service survey, 96% of respondents agreed that customer service quality influences their loyalty to a company or brand.

To improve customer experience, a call center should keep track of all of the important tasks that occur daily. Here are a few measures to improve the customer experience:

Using Call Reports To Improve Customer Satisfaction

An agent’s response time is a major factor in every customer interaction. Customers expect a quick response when they call. Call center reporting helps in this aspect by displaying historical and real-time information on how your contact center handles incoming calls.

Collecting Feedback From Customers

Asking and requesting feedback from customers can improve call center processes. Asking buyers what they think about an agent from a recent interaction can be a way to gauge customer happiness.

Recognizing Customer Preferences

Call centers can provide better services by actively listening and empathizing with customers. As a result, relationships are reinforced, leading to an increase in revenue. When data analytics are used, data analysts can better understand consumer behavior.

Must-Have Call Center Analytics Features

Data analytics is becoming more common in call centers, however, many businesses fail to reap its full benefits. According to a McKinsey report, only 37% of organizations believed that analytics were being effectively used to produce value.

To properly optimize call center analytics, here are a few must-have features:

Data Integration

Your customer relationship management system, team chat, email, files, dashboard, and other relevant databases should be interconnected. They should be easily accessible and should provide timely insights to all the members of your team.

Omnichannel Approach

Call center analytics should incorporate data from multiple sources and employ an omnichannel strategy. It should connect to all data such as SMS analytics, chatbot answers, customer polls, emails, campaigns, and other marketing data. The more data it can collect, the easier it will be to automate operations.

Metrics Analytics and Reporting

Call center data comes in a variety of formats which can be daunting if you don’t have the correct strategy in place. Instead of merely collecting data, use it to generate reports that are linked to and included with the analytics program.

Real-Time Analytics

It’s no longer enough to rely solely on data. Systems that can deliver data in real-time should be prioritized. These tools should have the capability to combine consumer feedback, call center agent performance, business results, and other factors that must be taken into consideration.

Key Performance Indicator Tracker

Reports can assist in immediately utilizing call data, but they may not cover all key performance indicators (KPIs). Look for an analytics platform that can track all the KPIs for your business. These can include call volume, first response time (FRT), first contact resolution (FCR), average speed of answer (ASA), average waiting time (AWT), and average handling time (AHT).

Make Your Call Center Operations More Data-Driven

Call center analytics solutions can help your company run more efficiently by delivering innovative agent experiences and engaging customer experiences. Today, customers routinely communicate with brands they follow via email, chat, and of course, social media.

Keeping up with today’s demands is critical for businesses. If you’re looking to improve your customer experience, reach out to ULTATEL, a cloud contact center solutions provider. Ultatel’s technology can provide you with a web-based customer management platform that can be accessed anytime, anywhere even if you don’t have a physical office. Request a demo or call 866-984-1638 to learn more.

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