Why call center analytics are the best tool for improving the customer experience

Call Center Analytics: The Data-Driven Way to Put Customers First

Emily GregorLast updated on January 2, 2024
11 min

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A customer-first culture makes for a successful business. You might think nurturing customer relationships comes down to anticipating needs and understanding behaviors, but one strategy you need to have at your disposal is thorough call center analytics.

When you use analytics to provide a memorable, positive customer experience, you’ll not only see a spike in customer satisfaction rates. You’ll also see an improvement in customer acquisition and retention rates.

Still not convinced? SuperOffice found that customers differentiate brands based on their customer service more than products or pricing. This means prioritizing the customer experience pays off now more than ever.

To make it easier on yourself, comprehensive analytics can…

  • Make your call center more agile

  • Improve sales team conversions

  • Increase internal alignment

… and more. Let’s dive into call center analytics to get started.

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What Are Call Center Analytics?

Because call centers are at the front lines of customer interaction, they’re a goldmine for customer data. You can find out a customer’s age, gender, nationality, and other similar information through your call centers.

Call center analytics collects information from all your customer interactions, analyzes it, and turns it into actionable insights. Using these insights, you can create actionable plans on how to improve customer experiences—whether through increasing customer satisfaction (CSAT) ratings, customer effort score, service-level performance, or all of the above. You can also discover the most common issues with your product or service and take steps to improve upon these areas in the future.

6 Types of Call Center Analytics

Modern-day customers interact with your business through an average of nine different channels. What does this mean for you?

Because your customer interacts with you through several channels, you have many opportunities to collect data and produce actionable insights. The more data you collect, the more accurate your insights. However, you shouldn’t apply call center analytics to all your channels right away. Doing this can overwhelm your call center agents and result in costly bills, especially if you don’t have a system in place for collecting, segregating, and analyzing data.

It’s better to prioritize the most important channels for your call center analytics and gradually build your system from there. This way, you can achieve a bigger impact on the overall customer experience and your call center’s performance levels.

Here are the six most common types of call center analytics to help you determine which channels to prioritize first.

1. Call Center Speech Analytics

Call center speech analytics focus on voice-based call center platforms (such as phone calls and video calls). They use artificial intelligence to detect keywords, vocal patterns, and tone to provide insights on the product, agent performance, and procedural or system issues.

They can also be used to warn agents when the conversation is taking a negative turn. At the same time, call center speech analytics alert call center managers when they need to step in and de-escalate the situation.

2. Call Center Text Analytics

Similar to speech analytics, call center text analytics use artificial intelligence to detect keywords, tone, and patterns in customer conversations. But instead of speech, they focus on written text. Thus, you can use them on documents, surveys, feedback forms, SMS, email, and even social media to identify patterns and relationships among the data.

Call center text analytics are essential for companies today because they can be a complementary tool for social listening. They can collect data from posts, comments, messages, and even brand mentions.

3. Predictive Analytics

Predictive analytics are the most cutting-edge form of call center analytics on this list. Beyond mining and analyzing data, they use machine learning to predict customer behavior, preferences, and needs. For example, if your customer mentions that they enjoy dark red lipstick, your call center analytics can pick up this data and predict that they might be interested in your next dark-red-lipstick product.

Predictive analytics also help you put your customers first. They give you insight into the peak hours and peak seasons of call center activities, so you can adequately increase your staff. They also predict possible issues or concerns customers may have about your new product.

4. Self-Service Analytics

Self-service analytics mine data from self-service communication channels, such as FAQs, blogs, and ebooks. They empower customers to solve their own issues and often prove to be more convenient, as they don’t have to wait to speak to a customer representative.

Self-service analytics identify the most searched keywords, questions, and phrases so you can create better self-service channels. For example, if you discover that “How long does shipping take?” is the most searched phrase on your website, you can add shipping times to your FAQ section. As a result, you’re reducing the number of inbound calls you receive for minor, common issues and improving the customer experience at the same time.

You can also use self-service analytics to program your chatbots and IVR features, further providing convenience to both your customers and your agents.

5. Call Center Desktop Analytics

Unlike the previous items on this list, call center desktop analytics are used to improve both your call center operations and your agent performance. They review the desktop activity of call center agents and help you answer questions such as:

  • How productive are my agents?

  • What applications do they use during work hours?

  • What procedures do they follow during and after each call?

By monitoring your agents’ desktops, you can gauge the individual performance of your agents and give them specific feedback. You can also discover ways to increase productivity by identifying inefficient processes in your call center workflows. As a result, you can reduce how much time agents spend on processes and increase the time they can spend focusing on providing excellent customer service.

6. Cross-Channel Analytics

Customers today expect an omnichannel experience, and cross-channel analytics make this possible. Cross-channel analytics analyze data from all channels and give you a 360-degree picture of your customer journey. They help you understand which communication platforms your customers prefer and how they use each platform differently. They also allow you to segment and personalize your customer service.

To be able to achieve cross-channel analytics, you need a tool that integrates with all your platforms. Anything less, and you won’t have a complete 360-degree overview of your customer touchpoints and the data you’re collecting from each.

Why Are Call Center Analytics Important?

Call center analytics collect and analyze customer data to put customers first (learn how three Aircall customers use this data to their advantage). They also improve your call center and your business intelligence through actionable insights. Here are some added benefits of using call center analytics:

1. Improve Call Center Agility

The point of setting up a call center is to have a dedicated group of people who can prioritize your customers’ needs and wants. However, if your call center agents are overwhelmed by high call volumes and low staffing, they won’t be able to do that effectively. This leads to long wait times, reduced resolution rates, and increased customer churn rates.

Using call center analytics helps you avoid this by predicting when you can expect high call volumes, such as during holidays or product launches. This way, you can quickly respond to the change in demand and have more staff to accommodate all the inbound calls.

Call center analytics also allow you to look at data from all your customer interactions to identify gaps in your systems and processes. For example, if you notice that more of your customers are reaching out to your support teams via social media, you can adjust your staffing requirements accordingly.

The result? Your call center team becomes more efficient and can quickly adjust to meet your needs and that of your customers.

2. Help Your Team Align on Strategy

More often than not, call center operations are considered separate entities from other departments. Thus, the data you collect from your call center and the data you collect from your sales department, marketing teams, and product teams aren’t often collated and shared with each other.

Call center analytics bring together all data sources, so sharing information across teams is not only possible but simple. By making customer data available for all your teams, you learn how each department affects the other. You can also identify ways to better work together. This way, you can align strategies and goals to improve the customer experience and create better customer relationships.

For example, when your marketing team has a promo, you can teach your call center agents about it so they can also endorse it in their inbound and outbound calls. And if you learn from past experience that the promo may increase call volume, then you can adequately staff your call center.

As a result, you also improve your overall business intelligence capabilities and optimize team operations.

3. Encourage Objective Decision-Making

Relying on gut feelings makes for bad business decisions. Gut feelings can’t tell you how to exactly optimize your call center operations or how to reach your KPIs. And they definitely won’t tell you why one business decision is better than another.

Using call center analytics, on the other hand, encourages a data-driven culture. Call center analytics makes data accessible and available to everyone in your company. Call center managers can gauge agent productivity and determine where they’re falling behind and where they‘re excelling. They can also determine how a certain decision can impact call times, conversion rates, and handle times.

And because call center analytics makes performance measurable, you can use targeted coaching to improve individual agents’ skills and give performance-based bonuses. You can also use data analytics in the hiring process. When hiring, you can focus on the performance metrics your star support agents or sales representatives have in common to find top talent.

4. Improve Your Sales Conversions

A good call center analytics tool doesn’t only improve your call center’s efficiency and productivity, but it should also proactively unlock ways to improve revenue. It does this by using behavior profiles, demographics, and purchase history to predict what customers might be interested in in the future. As a result, your sales agents can suggest that product or inform customers when there’s a special promo on it.

Another way it does this is by helping you determine the most effective strategies for making outbound calls. Maybe calling leads during the afternoon leads to better conversion rates than in the morning, for example. It can also teach your reps how to better frame questions or adjust their language to entice customers more into buying, based on the types of sales techniques that have worked best in the past.

5. Boost Agent Performance

As mentioned previously, call center analytics tools don’t only collect customer data. They also help you analyze your agents’ performance. Call center analytics can tell you where an agent is excelling and where they may need further support. They also allow you to objectively identify top performers through set KPIs, such as hold times and first-call resolution rates for support agents or close rates and deal value for sales reps.

By identifying the KPIs that are relevant to your business goals, you can find the best ways to structure your call center operations and teams to produce maximum results. In addition to measuring agents’ performance, you can also identify inefficiencies and time-consuming tasks. This boosts agent productivity and your business’s productivity overall.

How Call Center Analytics Impact the Customer Experience

Especially in competitive industries, it’s getting harder to stand out through products or services alone.

You need to be the best in customer experience so customers will remember and keep going back to you. And to be the best, you need to have a customer-first culture that’s driven by data and analytics.

The good news is that call centers are endless sources of customer data. This means you can constantly improve your customers’ experience to stay ahead of the curve. Through call center analytics, you can monitor customer complaints, identify issues, and actively work toward improving them.

Plus, you can also track your call center agents’ performance, so you can determine how to improve training and onboarding processes. For example, you can leverage call whispering features to give reps on-the-job training during real-life call scenarios, then track their performance metrics before and after to determine if your coaching is effective.

Lastly, call center analytics allows you to segment your customers and personalize their entire journey. It does this by collecting data on purchasing history, previous call recording data, behavior profiles, demographics, and more so you can tailor conversations specifically to them. Additionally, through cross-channel analytics, you’re able to personalize experiences even more by leveraging insights from email tickets, social media messages, and call history, and applying these insights to all of your other customer service channels.

Why Having the Right Call Center Analytics Tools is Imperative to Success

While 76% of organizations acknowledge that utilizing customer data is important, the majority of them fail to fully capitalize on it.

Why? Because they’re using legacy systems and basic analytics tools that barely scratch the surface of customer data and insights. These tools record, transcribe, and analyze call center data after the conversation. As a result, they lose valuable time, money—and, more importantly, customers—because they only resolve the issue once it’s been escalated or deemed high-risk.

However, use the right analytics tools and you’ll not only gain holistic insights, but also real-time analysis. This way, you can turn a potentially bad customer experience into an excellent one. You can also better personalize your customers’ experiences by tailoring your conversations to their interests and needs.

Aircall understands all this and more. We know that putting customers first is crucial to a business’s success. We also know that leveraging data and analytics are the most effective ways to achieve this. That’s why we track KPIs for individuals and teams, filter your call center analytics, and help you keep an eye on your KPIs and progress towards key goals.

Aircall’s cloud calling phone software provides integrated call center analytics with all your other communication channels. Plus, we integrate with over 80 CRM tools, so you can keep giving customers the omnichannel experience they want—no matter which system you currently use.

Ready to create customer-first experiences with powerful, data-driven insights for your customer service and sales teams? Contact us today to get a demo.

Published on July 7, 2021.

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