The COVID-19 pandemic significantly changed how customers shop for many goods and services. It also changed the way businesses accommodate and respond to customer needs.
Call centers have been at the forefront of much of this dramatic change, with the call center market expected to grow to nearly $70 billion by 2028, with a compound annual growth rate of 14.59%.
The need to use call center analytics to better respond to customers' needs, improve customer satisfaction and grow sales has seldom been more important to businesses of all sizes. Call center analytics help companies make the changes needed to be successful.
Growing Customer Expectations
Today’s customers want businesses to meet their expectations no matter where they shop — digitally, in-store or a mixture of both.
A 2021 Talkdesk report highlighted some of these expectations:
- 58% of consumers polled said their customer service expectations increased over the past year
- 69% want the ability to move from one channel to another while speaking with a customer service representative
- 78% want to engage with the company on their preferred channel
- 84% expect their questions or concerns to be solved quickly and accurately
What Are Call Center Analytics?
Call center analytics involves collecting, managing and reporting key metrics that affect call centers. Some metrics and key performance indicators (KPIs) include the volume of calls, how long agents handle each call, first response time and hold time. Companies can use this data to improve response times, reduce hold times, increase efficiency and more.
Call center analytics have transformed these communication hubs from an essential service function to a strategic differentiator. In fact, one Salesforce study revealed that 79% of consumers believe the experience a company provides is more important than its products or services.
An Omnichannel Approach to Call Center Data
That same Salesforce study also found that customers use an average of nine channels when communicating with a company — whether they’re seeking information, asking for advice or making a purchase. And that number increases for millennials.
To provide a consistently excellent experience, businesses need to track all of these interactions. Without doing so, it would be nearly impossible to gain a 360-degree view of how customers interact with a company.
While there are dozens of metrics call centers can use to measure performance, they won’t need every single one. Instead, they should choose the metrics that will best pinpoint and optimize areas requiring improvement.
Related Article: Providing Experience in an Omnichannel World
Pros of Using Call Center Analytics
Analyzing calls, texts, emails and surveys — any form of communication you receive from a customer — will allow you to make needed changes to your call center and achieve consistent customer service. Some benefits provided by call center analytics include:
Data is much easier to quantify than what your customer service representative might glean about the customer's attitude. Focus on the essential metrics you can collect and interpret.
Most good call center software offers built-in analytics. Even small businesses can use data from customer interactions. Plus, your service representatives won’t need to develop coding skills or learn how to use a system such as structured query language (SQL) to extract the critical data they need.
Metrics should help improve customer interactions and allow agents to achieve desired results. When you select the most appropriate metrics for your business, those metrics should also be the ones your service agents have significant control over.
Cons of Using Call Center Analytics
While it might not seem possible, call center analytics can have some downsides, including:
It would be nice if employees solved customers’ problems as quickly as possible. However, that’s not always possible, and you should be wary of metrics discouraging agents' communication with customers. For instance, don't use the amount of time handling a call to stifle employees' meaningful interactions with customers.
Take a story from Zappos, an online shoe and apparel retailer known for its stellar customer service, as an example. One employee handled a customer service call that lasted 10 hours and 43 minutes, only taking one break during the call to use the restroom.
From a metrics standpoint, that call length might look like a bad thing, and it's not feasible to do with every single caller. But there are exceptions. In this instance, the customer had a genuine interaction with an employee, a memorable (in a good way) experience and even bought a few products.
On the other hand, not every store has the kind of customer service Zappos offers and some call service representatives learn how to game the system.
For example, if a company has a strict rule about call handle times, such as a goal of keeping calls under three minutes, some representatives will cut calls short at the expense of resolving a customer’s problem. If this issue continues, call handle times will look great, but retention rates might drop significantly.
Inattention to Detail
The calls that come into a call center sometimes don't reach far beyond the center itself. If company executives aren't paying attention, they will never understand what customers are trying to tell them or why customer retention rates are dropping.
The key is to focus on the numbers and metrics most important to your company and to train your team to respond with the right behaviors. Provide your agents with feedback about performance and give them training if needed.
The Importance of Omnichannel Analytics
Provide your teams and agents with a way to view performance across all the channels customers use to engage with the company. Representatives will be able to diagnose and resolve issues more efficiently, and managers will be able to judge agent productivity more effectively.
Think about the times you needed information from another company to complete a purchase. How long were you on hold? How many times did you need to explain your problem to different agents? Were you happy with the resolution? If your experience was bad, what is the chance you will do business with that company again?
Now think of how your customers might answer those questions. Don't keep your customers on hold for too long, don't make them explain their problem multiple times and make sure they're happy with the resolution.
In the above Salesforce study, 92% of customers said that having a positive customer service experience makes them more likely to make another purchase from that company. And the flip side of that is that poor experience could make them turn elsewhere.
Call center analytics provide you with many ways to alleviate or eliminate problems. For instance, when looking at a system that provides real-time feedback and data, it's easier to see logjams develop and assign staff at peak periods to reduce or eliminate long wait times.
3 Phases of Acting on Call Center Analytics
Using call center analytics effectively boils down to three phases:
Avoid silos. You want to collect as much data in the appropriate areas as possible from all the channels you can. Make sure each department shares the data they collect with other departments. For instance, call center agents often can't track resolution rates. Use customer relationship management (CRM) or analytics software to provide that information.
Data by itself is just data. Organize and present it understandably so that your team can read and use it easily. Call center analytics software often includes templates you can use to create these analytics reports.
Once you've analyzed and studied the data collected, use it to improve the performance of your agents and fill gaps in your customer response plan. Consider each metric or KPI you want to use to improve your call center. Think about how to get the most benefit out of each metric.
Related Article: 3 Key Benefits of AI in the Call Center
Call Center Metrics and KPIs That Focus on Customers
There are a lot of different metrics your call center can look at. Some analytics software offer templates that give companies a good jumping off point. After a while, you might want to add or subtract different metrics from these templates.
Some metrics you might track include:
Machine learning and conversational artificial intelligence have changed the way speech analytics works. Previously, analyzing speech required manually reviewing many hours of conversations.
Today, companies use automated processes programmed with keyword searches to perform the same functions. Companies can track positive and negative keywords used in customer conversations and then delve deeper into those specific interactions.
Surveys complement the other call center data you collect. Once a customer completes a purchase or hangs up the phone on a service call, you can automatically send them a survey measuring their satisfaction and how they felt about their recent interaction.
Predictive analytics is like using a crystal ball. It's designed to tell you and your team what will happen next. You can use it to forecast your staffing needs during peak hours or holiday seasons. Predictive analytics will also let you know if you should program specific responses into your chatbots or interactive voicebots due to specific customer inquiry trends.
You can collect a plethora of data using real-time chat, interactive voice response (IVR), short messaging service (SMS) and email. Text analysis allows you to mine this data and find keywords, terms and phrases your customers may prefer you use.
For instance, if customers request information on how they can update their home address, don't send them a link to update their "location." Send them a link that will allow them to "update home address."
Customer Satisfaction Score (CSAT)
Customer satisfaction scores provide essential data about customer loyalty and if you can expect long-term revenue opportunities from that customer. Companies can use surveys to discover how satisfied people are with their products, services and customer service.
Companies can learn a great deal from the customers who complete the surveys — both about the changes they may need in the call center and important information about the customers themselves.
Customer Effort Score (CES)
The customer effort score is one of the most important metrics a company can use to determine how a customer feels about the brand. It specifically looks at the amount of effort it takes a customer to accomplish a specific task with that company.
Customers often get frustrated when they feel they have to put in a lot of work — or effort — to do something simple, whether it's get a question answered, sign up for a newsletter or purchase a product.
A CES survey might ask a customer: “Do you agree or disagree that [brand] made it easy for you to handle your issue.”
Net Promoter Score (NPS)
You might call this the "word of mouth" metric. It aims to measure how happy customers are with their experience and how likely they are to recommend the company to other family members or friends.
Call Abandonment Rate
If a customer is on hold for too long, they may abandon the call. If the caller sought more information about a product or wanted to make a purchase, they may have moved on to a competitor.
Number of Calls Blocked
Companies use this metric to measure the number of callers who call but receive a busy tone or are routed to leave a voicemail or callback. Current and potential customers find this extremely frustrating. Companies can use this kind of information to staff call centers appropriately to reduce the number of busy signals.
Time on Hold
No matter how hard you try, there will be times when customers must wait on hold. This metric measures how long they wait to speak to a call center agent. Ideally, you want this metric to show the lowest number possible.
A high number will mean many people will likely abandon their calls and potentially move on to competitors. Combining this metric with the rate of call abandonment metric will inform you about staffing issues and if your agents are answering questions promptly.
Call Center Metrics and KPIs That Focus on Agents
Many of the above metrics indicate customer satisfaction with your company's products or services and the customer service you provide. However, companies also want metrics to give them an idea of how their agents perform. These metrics allow them to measure agents' performance and give guidance on areas in which they can improve or need to make changes.
This metric provides a real-time way to measure an agent's productivity by looking at how many calls they answer within a specific number of seconds.
Average Speed of Answer (ASA)
With this metric, you can look at how long it takes an agent to answer inbound calls. The average global answer speed is 28 seconds, and many call centers follow the 80/20 rule — attempting to answer 80% of calls within 20 seconds.
Higher ASA times signify a greater risk of customer dissatisfaction and possible agent problems. It can also point to efficiency and accessibility issues.
Average Handle Time (AHT)
This metric calculates the time an agent is on a call — from when they first pick up the phone to when they disconnect. Innovative businesses allow some flexibility in this metric because the reality is some problems are more challenging to handle than others (Remember the Zappos story!).
Many companies want agents to resolve calls as quickly as possible. And shorter AHTs tend to point to answering customer queries quickly and efficiently. Still, as pointed out above, the danger with promoting short AHTs is that some agents will intentionally keep calls short to hit the desired standard without solving customer problems.
First Call Resolution
The first call resolution metric, also called first response time, is a sign of excellent customer service and one of the most important ways to ensure customer satisfaction. It measures how often agents handle customers’ problems without escalating the call, transferring it or having to call back.
Call centers aim for a high first call resolution number. A high number usually indicates a well-trained and knowledgeable team of agents who use call center analytics to help them answer queries.
Call Center Metrics and KPIs That Focus on Operations
Managers and supervisors must determine how to measure a call center's performance. General call center operational metrics help managers spot trends and understand the effect that company initiatives, such as product launches, have on call volume and customer satisfaction.
Number of Calls
This metric measures how many calls an agent handles during a specific timeframe. It does not include abandoned calls.
Cost per Call (CPC)
What is the average cost of a call handled by a call center agent? CPC provides insights into the call center's efficiency and resource allocation. It shows if the call center is operating in a cost-effective way.
Peak Hour Traffic
One of the most valuable metrics to forecast staffing needs, peak hour traffic is designed to measure when call center agents receive the highest volume of incoming calls. The task is to identify the specific parts of the day that experience higher call volumes.
Age of Query
If an agent can't resolve a problem on the first attempt, this measures how long it remains unresolved. It can provide clues about which channels have longer unresolved times than other channels. You should combine it with the first call resolution metric.
If a customer calls during a hectic time and can't reach an agent immediately, companies are now offering the opportunity to receive a callback. It gives customers the option of eventually speaking to an agent without having to wait on hold.
Using this metric is another way to determine staffing needs and increase efficiency. Ideally, this metric will be low since most customers want their concerns dealt with immediately.
Another metric that relates to first call resolution, number of repeat calls helps companies determine if agents had problems or issues during the first call. You can combine this metric with customer feedback using surveys or direct interviews to identify recurring issues.
Remember, you may not need to use all of these metrics to improve your call center. Identify the numbers most important to your business and focus on them.
This data can help your company gain a deeper understanding of customer service quality. It can also be used to increase customer satisfaction, which results in more revenue.
Related Article: A 4-Step Recipe for Improving Your Contact Center Agent Experience
Use of Advanced Call Center Analytics
Once you get your feet wet using the data from call center analytics to understand and improve your business, you’ll want to look at the next stage of advanced analytics. As McKinsey described in 2019:
"Advanced analytics has fundamentally changed the role of contact centers from a basic service offering (and a net cost to the business) to a strategic differentiator that can make dramatic improvements in customer satisfaction and financial performance.
Companies have already applied advanced analytics to reduce average handle time by up to 40 percent, increase self-service containment rates by 5 to 20 percent, cut employee costs by up to $5 million, and boost the conversion rate on service-to-sales calls by nearly 50 percent — all while improving customer satisfaction and employee engagement."
McKinsey identified some traits common to the best analytics-driven call centers:
Clear Vision and Strategy
Businesses and organizations which operate call centers require a coherent company-wide vision of how to use analytics. They must tie decisions to the overall business strategy and include plans to improve essential operations in the call center.
Agility With Analytics
Companies need to be agile to capitalize on analytics-driven data insights. These insights should align with the organization's strategic goals.
Forget about gut instincts. The best call centers make daily decisions based on available data. They use that data to make decisions about hiring, coaching and bonuses for agents, as well as areas that need improvement to increase customer satisfaction.
Improve Customer Experience in the Call Center
Call centers are no longer just organizational afterthoughts. Changes in how people shop and look for information due to the COVID-19 pandemic — along with other factors — have transformed call centers into critical elements of any business operation. The better your call center, the happier customers will be and the more likely they’ll remain with your company and buy more of your products or services.
The way to create those efficient call centers is with data from call center analytics. If you’ve been hesitant in the past to embrace call center analytics fully, there is no time like the present.