Your Handy Guide to Analytics for Contact Center Teams

Analytics for contact center teams plays a key role in enhancing customer service. The ability to quickly gather and process data enables you to make profitable decisions.

Analytics also gives your team clear direction, according to author and consultant Geoffrey Moore. He states, “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

Find out which data points you should track in your contact center and what you can learn from them. Then, uncover which contact center software simplifies the entire process.

Key Takeaways:

Analytics helps your contact center improve customer service and employee engagement.
Top analytics for contact center teams include interaction data and sentiment analysis.
Intermedia’s platform makes analytics easier with customized reports and intuitive dashboards.

What Are Analytics for Contact Center Teams?

Contact center analytics involves collecting, organizing, and examining actionable data about your agents and their interactions. You assess your team’s performance from that information by comparing metrics and key performance indicators.

The goal of tracking analytics for contact center teams is to optimize efficiency and customer service. Consequently, you should see:

Better decision-making
Increased customer satisfaction
Greater employee engagement
Reduced expenses

All of these benefits lead to a stronger brand and higher revenue.

What Are the Most Important Contact Center Analytics?

All data is not equal. You need to focus on the metrics and KPIs you can act on to make a positive difference in your operations.

Interaction Analytics

Interaction analytics encompasses statistics and data on agent-customer conversations. Common KPIs include:

Agent response times
First-contact resolution rates
Time-to-resolution rates
Number of transfers
Abandonment rates

Advanced analytics for contact center teams lets you view these for individual agents. You can also review how your organization performs as a whole. Use these to measure yourself against industry averages and your past performance.

Business Intelligence Data

Easily accessible customer data provides deeper insights to agents as they interact with callers. For example, a screen pop feature provides agents with information about callers from customer relationship management software. The file helps the agent understand how to best serve a customer at the moment.

Might a long-time or high-value customer be at risk of cancellation because of dissatisfaction with previous interactions? An agent can immediately see that on their screen. As a result, your team can prioritize these customers and present personalized offers that reduce churn.

Direct Customer Feedback

Analytics in your contact center can also process customer feedback. For instance:

Online chatbots can request that users rank their satisfaction levels.
Integrated interactive voice response can conduct an automated survey about customer experiences and expectations after calls.
SMS surveys are great for concise feedback.
Email surveys may permit a more detailed assessment.

All of this information goes right into your contact center software.

Even better, artificial intelligence allows your surveys to go beyond simple numeric rankings or closed-ended questions of yes/no or multiple choice. Natural language processing can accept answers to open-ended questions and interpret the feedback. That means you can collect advanced insights without supervisors having to personally read and record each response.

Speech Analytics

Powerful AI also means managers no longer have to personally listen to calls or read email interactions to understand what’s occurring. Performing such reviews manually is time-consuming. It might also present a skewed understanding of the data because supervisors can only review a limited sample size.

Speech analytics can analyze all of your calls and ascertain the following valuable components:

Common topics, questions, and complaints
Potential compliance issues or areas that require additional training
Sentiment analysis to determine a caller’s level of satisfaction and emotional state

As your software reviews these analytics for your contact center, it also transcribes and archives them for easy retrieval. Advanced functions ensure privacy and compliance with automated redaction.

Predictive Analytics

Predictive analytics for contact center teams assimilate the data and forecast significant trends. These insights help you improve staffing. Your supervisors will know when to schedule agents with specific skills to improve call handling times and FCR.

Which Features Are Essential for Your Contact Center Analytics?

Ensure that your contact center software makes your data easier to access, manage, and understand with intuitive features:

Business software integrations: Beyond internal features, connect other productivity software to your system for simultaneous data updates.
User-friendly dashboard: Make data easier to understand with pre-built and custom reports with your most important metrics and KPIs.
Real-time analytics: Ensure you can see what’s happening in the moment and not just historical data so you can keep your team on track.
Omnichannel connectivity: The contact center should handle all channels of communication and have full integration with your internal private branch exchange so agents can reach other experts.

The best way to access all of these features is with a cloud contact center. This digital platform allows you to utilize and manage all aspects of the analytics in your contact center in a remote or hybrid environment.

Take Full Advantage of Analytics in Your Contact Center

Embracing analytics in your contact center allows you to provide customer-centric service that builds brand loyalty. You also empower your agents to perform at their best. Discover how simple it is to start utilizing contact center analytics with Intermedia’s platform today!