Keeping customers satisfied is an important part of business no matter what industry you’re in, so using smart software to analyze your business practices can be useful for identifying where your business’s strengths and weaknesses are.

When consumers get in touch with your business via the phone, email, social media, or live chat, they expect prompt and efficient customer service every time. So, how can you ensure that’s what you’re offering? Good call center analytics software will allow you to dissect your business processes.

Whether you’re looking to invest in smarter call center analytics software or you want a better insight into how call center software can help your business improve, this comprehensive guide will dive into what call center analytics is and how it may benefit your company.

We’re going to discuss:

Call center or contact center analytics software allows you to deep dive into the inner workings of your call center, including customer satisfaction insights and analysis of how your agents' performances stack up. It captures and tracks call center data from inbound calls and outbound calls.

It typically records information such as call length, wait times, how many times a customer calls before a solution was found, and customer satisfaction levels. What’s more, it can even incorporate speech analytics to further your knowledge of customer interactions, such as picking up on when customers are happy or frustrated.

But how does it work? It records the touchpoints a customer has made from calling the contact center. This includes hold time, call times, types of calls, the number of calls they’ve made, and what answers were given to the interactive voice response (IVR) receptionist.

This data is then safely stored in the call center software to be revisited whenever needed. It may be used for call analytics or training in the future. Ultimately, analyzing customer behavior can help you analyze how your agents deal with customers, allowing you to improve on future customer interactions to come.

Call center software can also work with your CRM (customer relationship management) system, giving you a more powerful set of tools to ensure customers remain happy and loyal, reducing customer churn.

Call center tracking is a quality management process where inbound and outbound calls are recorded to monitor and analyze agent performance. This can be done using automated technology, or by analyzing data yourself manually. You can also tailor contact center analytics software to suit your business needs. To track an employee’s performance, you can use features such as call recording and transcriptions.

This is all to keep in line with your long-term business goals. For instance, you may have a target of X number of outbound calls each day, with X number of new customers onboard. Alternatively, your business goals could be in relation to customer service.

You may want to reach a 90% customer satisfaction level within a certain time frame. Call center tracking can help you do all of this and much, much more as you have access to data that can help you see if you’re on track with your goals. Perhaps you need more staffing, or you need to implement more specific questions to get the caller to the right agent faster.

Using data analytics software in your call center can ensure your business is operating efficiently and effectively. Data and analytics can help you streamline your business processes, improve your customer service, and monitor your call center performance.

Analyzing data in a call center is best done using specific software designed for this purpose. You can look back on your call logs of outgoing and incoming business calls. This means you can see how many calls you’re making and receiving each day, how long they last, and when your busiest periods are.

This information can tell you a plethora of insightful statistics that can help your business function, such as when you’re likely to receive the most calls during the week. This way, call center managers can ensure there are enough agents on hand to facilitate the incoming calls.

What’s more, you can also track where the calls are coming from. This can help you in terms of marketing and advertising in specific areas. For instance, if you notice you’re getting an increasing number of calls from a specific city, you may wish to increase your advertising budget in that area.

Other ways you can analyze call data include:

• Response times
• Average handle time
• Average abandonment rate
• First contact resolution, also known as first-call resolution (FCR), rate
• Customer satisfaction and feedback scores from surveys

An overview of your call handling may look something like this:

To improve your call center stats, you need to understand what they mean and identify the steps that you have to take in order to improve them.

For example, if your statistics are telling you that over 60% of customers are on hold for more than 12 minutes, you need to find out the reasons why the waiting times are so long. Is your system taking too long to connect the customer to the right agent? Is your current call-forwarding system inefficient? Customers may already be frustrated by the time they even get through to an agent.

It’s difficult to know exactly which areas of your contact center need improvements without good contact center analytics software. The right software will enable you to dive into the inner workings of your call center and analyze exactly where the issues are.

Here are some ways to improve call center statistics:

1. Quantify customer feedback
2. Use real-time metrics
3. Use cross-channel analytics
4. Emphasize self-service channels

Let's look at each in more detail:

1) Quantify customer feedback

Customer support is all about offering customers assistance and gaining insight into what their needs and expectations. If customers are providing feedback at the end of the call, ensure you’re asking some questions with numerical responses such as “What would you rate your call today out of ten?”. This can make it easier to quantify their feedback and, in turn, improve customer support.

You can also calculate the customer effort score with a series of questions. This determines how much effort the customer has had to put in to reach a solution. The data from these questions can be used to improve the overall resolution rates of your call center.

2) Use real-time metrics

Your call center agents need to understand how their service impact customer experience and satisfaction. Analyzing metrics such as abandonment or conversion rates can give you insights into improving your team’s customer relationships.

3) Use cross-channel analytics

It’s good to have a grasp on how customers are interacting with different channels. It’s also important to analyze the demographics of your customers to find out which groups interact with your company through which channels. For example, Millennials and Gen Z are more comfortable accessing help via a company’s website than picking up the phone. These customer insights can help you form customer management strategies tailored to your target market.

4) Emphasize self-service channels

A robust self-service channel can be beneficial for both your customers and your contact center agents. If customers can resolve known issues themselves, they won’t need to contact support anymore. This will result in higher overall customer satisfaction and reduce the burden on your customer support staff.

Set KPIs and objectives

You should ensure your call center metrics are tied into your business goals so that they measure important aspects, such as revenue, conversion rates, and costs. This way, you can effectively analyze the data against your business objectives.

Here are some of the key benefits of using call center analytics software:

Improved customer satisfaction

One of the biggest benefits of using call center analytics software is that it can enhance your customer service by helping you collect agent performance and customer data for analysis. Having a clear view of how your call center is doing will allow you to make strategic decisions for improvements in service, resulting in overall higher customer satisfaction.

You can also cross-reference responses across your omnichannel contact center to understand customer satisfaction levels even better - do customers generally have a better experience over the phone or online? Call center analytics software can tell you!

Improving customer experience should be one of your business’s top priorities if you wish to see consistent growth and revenue increases. If your customers are satisfied, they’re likely to remain loyal and return in the future, increasing customer retention rates. What’s more, they may also tell their friends and family about your business, which equals free word-of-mouth marketing.

Understand consumer preferences with predictive analysis

With call center analytics, machine learning can be used to improve predictive analysis. This contact center technology learns from previous customer behavior and uses this data to predict customer behavior in the future. This means your agents can provide customers with a solution more efficiently, improving customer experience.

For example, if you find that the analysis from your data is telling you that customers prefer to use chatbots instead of communicating on the phone - you must ask why this is. Is it because that’s simply down to the customer’s preference? Or have they tried to call your business before but were met with long call waiting times and an agent who wasn’t experienced in handling the type of issue that their call was about?

By taking the time to understand consumer preferences, behaviors, and decision making, you can put more effort into areas that need attention.

Self-service analytics

As mentioned earlier, self-service tools in a contact center analytics system are beneficial to both the business and the consumer. Businesses receive fewer phone calls as customers can find the information they need online, so you won’t have to worry about hold times and abandonment rates.

Self-service mainly includes FAQs and a knowledge base, which let customers explore topics and find answers. Chatbot self-service systems can be operated by AI, and they can be taught to assist customers through machine learning or sophisticated programming.

This can produce highly accurate responses to customer queries, and as they’re learning over time, they’re constantly improving with each customer interaction. The amount of historical data to look over also increases.

Creates a customized experience

By using intelligent routing and AI (artificial intelligence) to deal with customer issues appropriately, the customer experience is improved, and there’s an opportunity for conversions to grow.

The customized experience can start as soon as the customer gets in touch with the contact center. By accessing previous call history data sources, the agent is able to quickly lookup all customer information to establish the nature of their previous calls.

This improves agent productivity because the background information from these analytics tools could help the agent with the current call. The customer may be chasing up an existing issue that’s yet to be corrected. They then know how to precisely assist the customer before the discussion has even begun.

Improved contact center speech analytics

There are two main types of speech analytics. The first is post-call analytics, and the second is real-time analytics. While both have their own merits, combining the two can improve the customer experience and business efficiency.

Post-call analytics is used to perform interaction analytics on conversations that have already occurred. This can be used to examine specific details of a previous customer call or a group of calls, searching for specific patterns and potential moments to flag. For instance, post-call analytics can be used to analyze a large call volume to listen for a specific keyword, which could help identify the exact root cause of an issue.

Real-time analytics can be used to analyze the customer interaction then and there. For example, how long is the interaction going? Is there a growing pattern of customers hanging up in the middle of calls? Monitoring real-time interactions is just as important as post-call analysis.

Collecting customer feedback for call center data

Call center analytics software allows you to gain actionable insights into customer behaviors throughout the customer journey. The most direct way to gain data is by asking for feedback. You can create feedback forms with specially curated questions designed to help you understand where your team’s strenghts and weaknesses are.

Customer engagement is vital if you want to see where customers may be feeling unhappy within the customer journey.

For instance, you may include questions such as “How would you rate the service you received today?” or “Would you recommend this service to a friend?”. This information can help you understand how the customer is feeling towards your business and the service level you’ve provided.

Text analytics

Most call center advanced analytics software will allow you to transcribe the customer conversation or, in the case of live chat, keep a copy of the written conversation. This can be used in the future with predictive analysis to see how a customer responds to certain questions.

It can also help identify customer behavior when it comes to specific topics or areas of the business.

If your current contact center solution software doesn’t include a well-rounded analytics solution, then it may be time to invest in a new system. Call center operations rely on great, accurate software to keep customer interactions smooth and manageable.

Choose a contact center analytics software system that can optimize your business processes and streamline your workflow to increase customer satisfaction and improve your agent’s work tools. Why not get in touch today to see how our call center analytics system can benefit your business?