Your customers are more likely to make repeat purchases if they have a good customer experience. In fact, 86% of buyers are willing to pay more if they know they can count on amazing service. So, imagine what happens when your customers call in and get a grumpy response on the other end. Experience ruined.

Agents are drained by tedious work, high pressure, and a lack of resources. As a result, they’re highly susceptible to burnout. And if your agents are exhausted, unmotivated, or frustrated day in and day out, it’s pretty tough to keep customers satisfied.

In contact center management, agent experience should be top of mind. You’re trying to support them with the right tools and coaching to keep them happy, engaged, and productive. But what tools do you need to make that happen?

Contact center analytics are part of the answer.

What Are Contact Center Analytics?

Contact center analytics let you use data to drive improvements in customer service and operations.

Let’s break it down.

First, what are analytics? Contact center analytics are tools and processes that gather and analyze data from your customer interactions on every channel (including calls, emails, chats, and even social media interactions). Why is this useful? Because data is powerful.

Data analytics is integral to growth. It can help you create an evidence-based strategy, understand your customers better, and increase productivity. This means you can focus on key areas of growth.

For example, let’s imagine you could identify a crucial moment of weakness for your team. Using performance metrics and analytics, you see that your agents are quick to answer customer calls (always a good thing!), but they put customers on hold to get the answers they need. A lot.

This insight suggests that you need to pay more attention to your average handle time and hold time over your speed of answer. Now you know where you need to train your agents. And you can see that they need better resources to answer customer questions without transferring or putting them on hold.

Learn more about performance metrics in our blog.

The 5 Types of Contact Center Analytics You Should Be Tracking

Contact center analytics can help improve your efficiency. But more importantly, they help support your efforts to create a better agent experience. Here are five types of analytics you should be tracking.

Speech Analytics

Speech analytics look at recorded conversations between agents and customers to identify patterns, trends, and insights. They can track and analyze customer sentiment and spot specific keywords so you can categorize calls based on the topic or issue. By understanding customer sentiment and identifying recurring issues, you can proactively address customer concerns.

How it supports a better agent experience. With speech analytics, agents can anticipate customer sentiment before or during a conversation, making it easier to adapt to the customer and avoid flailing. This improves morale, helps agents remain efficient, and reduces call handling times.

Text Analytics

Similar to speech analytics, text analytics examine conversations. Instead of verbal conversations, these analytics look at written interactions (your emails, chat transcripts, and social media messages). With text analytics, you can uncover customer preferences, identify emerging trends, and find areas of improvement in agent communications.

How it supports a better agent experience. It’s hard to read between the lines and figure out how to respond well in writing. Plus, it eats up agent time and adds stress. Text analytics help agents understand customers’ feelings based on their written communications. They pinpoint exact words and phrases to make agent writing clearer and more personal, giving them specific, actionable feedback so interactions are effective and pleasant.

Predictive Analytics

With predictive contact center analytics, you can forecast the future using historical data and statistical algorithms. Predictive analytics help you anticipate customer needs, identify potential issues before they arise, and optimize workforce management.

How it supports a better agent experience. Consider this: 74% of contact center agents are at risk of burnout, and 76% report a negative impact on their quality of life because of stress. With predictive analytics, you can reduce that burnout and stress by anticipating how customers will respond and when call volumes will be high. Then, you can allocate resources and schedule accordingly to avoid overwhelming agents.

Customer Journey Analytics

Customer journey analytics focus on understanding the end-to-end customer experience. These analytics help you identify why customers behave a certain way along the customer journey. You can find out why customers reached out when they did or locate pain points and reasons for churn. Then, you can optimize processes to deliver a seamless omnichannel experience.

How it supports a better agent experience. Customer journey analytics give you and your agents insight into where customers are experiencing frustration and where processes are breaking down. With this intel, you can improve your processes, clean up inefficiencies, and empower agents to provide more personalized care. By helping agents provide better service, you’re supporting their growth and encouraging them to succeed. And who doesn’t want that?

Agent Performance Analytics

Agent performance analytics track and analyze your metrics and KPIs. This gives you insight into your productivity, efficiency, and quality of service. Then, with these insights, you can give agents real-time feedback and tailor training to tackle their weaknesses. They also help you identify areas where you need more resources.

How it supports a better agent experience. Performance management and employee engagement are closely intertwined. Your agents want to know how they can do better at their jobs. Using agent performance analytics, you can empower them to improve their performance, enhance their skills, and ultimately deliver a better customer experience.