Contact center analytics: What are they and how to analyze call center data
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Keeping a contact center running smoothly is no easy feat. It takes a tremendous amount of effort to oversee agents and provide tailored coaching while ensuring that all customer interactions are positive across each communication channel.
A contact center analytics solution like the one offered by RingCentral enables you to gain a better understanding of how your agents are performing and offers a comprehensive view of every customer conversation and journey.
By using software that provides analytics for contact centers, you’ll also benefit from more opportunities to optimize agent performance.
Learn how RingCentral can help your contact center provide the perfect balance between delivering outstanding customer service that exceeds customer expectations and keeping costs to a minimum.
By using software that provides analytics for contact centers, you’ll also benefit from more opportunities to optimize agent performance.
Learn how RingCentral can help your contact center provide the perfect balance between delivering outstanding customer service that exceeds customer expectations and keeping costs to a minimum.
What is call center analytics?
Call or contact center analytics is the collection and analysis of vital information relating to contact centers. It provides valuable information about how well a contact center is doing, offering insights into customer experience and agent performance.
It encompasses the analysis of metrics like customer satisfaction scores, average handle time, and average hold time. Good contact center analytics tools will also delve deeper into data that reveals whether staff are achieving their goals and whether customers are receiving an experience that encourages retention and expansion.
With the help of call center data analytics, organizations have concrete information that informs them of how they can improve operations, from training to process refinements.
It encompasses the analysis of metrics like customer satisfaction scores, average handle time, and average hold time. Good contact center analytics tools will also delve deeper into data that reveals whether staff are achieving their goals and whether customers are receiving an experience that encourages retention and expansion.
With the help of call center data analytics, organizations have concrete information that informs them of how they can improve operations, from training to process refinements.
Why is contact center analytics important?
You may well be thinking that tracking and analyzing contact or call center performance sounds like hard work. And you’d be right. However, it is worth it to get the kind of valuable insights which are out there just waiting for you to uncover them. Here are a few key ways in which contact center analytics may prove vital to your business:
It can help you streamline processes and improve operational efficiency
Using the right call center analytics software allows you to get a well-rounded, holistic view of your contact center operations. That makes it easier to accurately pinpoint any areas where process or workflows can be improved.
Key metrics in this regard include things like:
Key metrics in this regard include things like:
- Average handle time (AHT)
- First call or contact resolution rates (FCR)
- Agent idle time
To take the first of those as an example, perhaps your call data tells you that in the past week AHT has been steadily increasing. When you dig a little deeper, you find that agents are fielding calls from customers who are struggling with a new product feature. Unfortunately, your agents haven’t had the information they need at hand to quickly solve these queries.
What that may tell you is that your agent training surrounding—and documentation of—new features may be lacking. You could then implement a new process whereby agents are briefed on new product capabilities and answers to potential questions are added proactively to your knowledge base.
What that may tell you is that your agent training surrounding—and documentation of—new features may be lacking. You could then implement a new process whereby agents are briefed on new product capabilities and answers to potential questions are added proactively to your knowledge base.
It makes up for feedback shortfalls
Undoubtedly one of the best ways to assess the customer experience your contact center offers is with direct feedback from your customers. That’s why businesses regularly send out customer surveys after each touchpoint a customer has with their organization.
The problem is that gathering this feedback is difficult. People are often busy and not minded to take the time to fill out surveys. Contact center data analysis can help to fill in the gaps.
While direct feedback is invaluable, analytics can still create a good picture of customer behavior. Cross-channel analytics can help you learn which routes to help customers are most satisfied with. Sentiment analysis, meanwhile, can give you an idea of how customers are feeling on calls or during other interactions—even if they don’t directly reach out and tell you.
The problem is that gathering this feedback is difficult. People are often busy and not minded to take the time to fill out surveys. Contact center data analysis can help to fill in the gaps.
While direct feedback is invaluable, analytics can still create a good picture of customer behavior. Cross-channel analytics can help you learn which routes to help customers are most satisfied with. Sentiment analysis, meanwhile, can give you an idea of how customers are feeling on calls or during other interactions—even if they don’t directly reach out and tell you.
It can improve customer satisfaction
What’s the ultimate result of improved operational efficiency and a better understanding of customer behavior? Greater customer satisfaction, and therein lies the fundamental importance of contact center analytics.
By seeking out and acting upon data-driven insights, you can make positive changes to your call center operations that you know will make a difference. Rather than guessing what your customers want or your agents need, you’ll have the information at your fingertips.
That means you can pre-empt some problems before they happen and solve others before they escalate. That’s a tasty recipe for better customer satisfaction.
By seeking out and acting upon data-driven insights, you can make positive changes to your call center operations that you know will make a difference. Rather than guessing what your customers want or your agents need, you’ll have the information at your fingertips.
That means you can pre-empt some problems before they happen and solve others before they escalate. That’s a tasty recipe for better customer satisfaction.
Types of contact center analytics
Call center analytics reporting allows you to gain access to various types of analytics, including:
Text analytics is a similar approach to speech analytics. The main difference, however, is that it analyzes conversations between agents and customers in text format, such as exchanges over email, social media, and chat.
This approach to contact center analytics reporting takes a comprehensive look at what happens on agents’ desktops or screens. Desktop analytics provides insight into workflow and process inefficiencies that become roadblocks to agents. It can also show security issues that you’ll need to address for compliance and determine if the system in place is working or not.
Forward-thinking companies know that to alleviate pressure on their agents, they have to invest in self-service technologies. These are usually deployed via chatbots in website chats and digital messaging channels, or via the interactive voice response (IVR) feature on inbound calls. Artificial intelligence (AI) and machine learning are making big strides in the self-service space. Self-service analytics analyzes how effective these technologies are in both serving customers and reducing contact center interactions.
This approach considers your historical data and analytics, using past performance to predict future performance. By using predictive analytics, your organization can anticipate upcoming problems, mark those in an events calendar, and come up with a solution. A good example is when your historical data shows that the company receives higher than average call volume during the holidays. By knowing this upcoming scenario, you can schedule more agents on certain days or weeks.
This approach is all about aggregating the data from all the voice and digital channels your business supports. This helps you identify how your customers interact with you and what their preferred interaction channels are. From there, you can pinpoint opportunities where you can improve those customer journeys to provide better customer experiences.
Benefits of contact center analytics
Leveraging call center analytics can give your business a crucial edge over the competition. Here are just a few of the benefits you’ll see when you implement an analytics strategy.
Improved service delivery
The more you understand how your agents are performing, the better. With targeted analytics, you’ll be able to determine each employee’s strengths and weaknesses, and where the team as a whole is performing well or poorly.
This means you can tailor your feedback and any required training precisely to each individual agent’s needs. Data is crucial for making sure your customer service constantly improves.
Better strategic decision-making
When you’re making big decisions about the direction your company is going, you first need the facts.
Using analytics is the best method of finding out everything you need to know in granular detail and making a business case for strategic shifts. For example, where should you set up your next contact center? Should you focus more on hiring or upskilling your existing agents?
Deeper understanding of customer trends
Some customer trends are obvious to any interested observer—but not all. And often, spotting developing trends early can be the difference between growing your market share substantially or losing out to competitors. If you want to get ahead of the curve, using analytics will help.
Call center analytics best practices
No matter how good your analytics tools are, you won’t make the most of them without bearing a few key principles in mind.
Here are some best practices to follow when collecting and analyzing data:
Here are some best practices to follow when collecting and analyzing data:
Unify your data
Rather than trying to track call center metrics across a variety of different analytics and reporting tools, save time and resources by unifying your data from multiple sources. The simplest way to do this is by using a single, complete communications platform that provides all your speech and text data from different departments in one centralized place.
Be mindful of security
Undertaking any project that involves the manipulation of large volumes of data necessarily involves making security a top priority. Be careful to adhere to any data privacy laws or other compliance standards that apply in your industry.
Conduct regular reviews
Don’t assume that what was effective yesterday will continue to be effective today. Businesses, industries, and contact centers are constantly changing, so you’ll need to review and fine tune your analytics approach regularly to keep up.
Features of the best contact center analytics solutions
Historical reporting
Track performance trends like Average Handle Time (AHT), Average Speed of Answer (ASA), and Abandon Rate. Select a pre-built report, or build custom reports tailored to your organization's needs.
Real-time dashboards
With a widget-based live dashboard, you can build customized views for different business members. You can also monitor overall contact center performance levels, queue information, and other critical real-time data.
Conversation intelligence
Analyze every interaction to find insights, such as overall customer sentiment, key topics, and competitive mentions. Leverage these insights to identify trouble areas with customer service to provide better experiences.
Voice of the customer
Gather feedback directly from your customers with post-interaction surveys. Select from a variety of question types, including simple boolean, multiple choice, and rankings to track customer satisfaction (CSAT), customer effort score (CES), and net promoter score (NPS).
How to approach call center data analytics
When you’re considering how to analyze call center data with analytics software, the first step is to establish exactly what it is you want to know. Even with the best tools, you need to first have a clear understanding of what you’re aiming for.
Spend some time thinking about what kind of insights would be the most valuable to your business. Do you want to know more about agent performance so you can fine-tune your service delivery? Or maybe having a better grasp of the ebb and flow of call volumes would be beneficial for schedule planning?
Once you decide what you want to know, the next step is to select the metrics that will help you get there.
Remember that some metrics are more relevant to certain industries and businesses than others, but no metrics should be looked at in a vacuum. Context is key—if your hold times shot up in the past week, some contact center leaders may look at agent performance first. But what if you just released a new product that had an unexpected bug, which prompted many of your customers to call in? That context turns this into a very different conversation.
Other crucial elements to think about include:
Once you decide what you want to know, the next step is to select the metrics that will help you get there.
Remember that some metrics are more relevant to certain industries and businesses than others, but no metrics should be looked at in a vacuum. Context is key—if your hold times shot up in the past week, some contact center leaders may look at agent performance first. But what if you just released a new product that had an unexpected bug, which prompted many of your customers to call in? That context turns this into a very different conversation.
Other crucial elements to think about include:
- Assigning someone to take responsibility for metric collection
- Establishing a fixed timeline for the project
- Setting out clear KPIs
- Deciding how you will apply any insights generated
How to analyze call center data: What to measure and why
With the wide-ranging functionality of the best call center analytics software, your call center managers may feel a little overwhelmed. Which of the dozens of possible performance metrics should they focus on?
It will depend somewhat on your contact center, your customers, and your business objectives. However, here are a few examples of metrics and KPIs that many call centers pay close attention to:
Average speed to answer
Before you even get to thinking about things like your agents’ performance, you need to think about how long you keep customers waiting. In a call center, the average speed to answer is the amount of time a caller spends interacting with your IVR and waiting in a queue to speak to an agent.
Typically, the longer the time spent waiting, the less satisfied the customer. So, keeping this metric in hand can be crucial for customer satisfaction. Some possible solutions include:
- Hiring more agents
- Introducing self-service options to ease pressure on queues
- Adapting call routing rules to make the process more efficient.
Call abandonment rate
This metric is closely related to the one above. The call abandonment rate in a call center is the proportion of calls which are hung up before the caller even gets to an agent. You want to keep this rate as low as possible.
Some of the most common reasons for call abandonment include:
- Your call queues are too long
- You don’t keep callers updated on their position in the queue or time left to wait
- IVR menus are too complicated.
Keeping this metric in check ensures as few of your customers as possible are left disappointed by not being able to resolve their issues.
Average handle time (AHT)
AHT is a more holistic metric that accounts for the entirety of a customer interaction. It’s the average time taken in your call or contact center for a customer’s issue to get resolved. So, it includes:
- Time in the call queue
- Time speaking to your agent
- Time on hold
- Time for any call transfers
- Any after-call work (ACW) time.
At the simplest level, this is another metric you’ll want to be as low as possible. However, there is a little more nuance here.
For instance, a slightly higher AHT may be preferable if the resolutions provided are better. It’s better all-around for agents to take a little longer but ensure customers aren’t forced to get in touch again a few hours, days, or weeks down the road.
So, what you’re looking for here is the right balance between the time each interaction takes to resolve and the success of the resolution. However, the ACW element of any call is one area you should always be looking to make more efficient. Fortunately, AI can help with this.
For instance, an AI-powered contact center solution can use Natural Language Understanding (NLU) and Processing (NLP) to accurately transcribe calls. If it’s then also integrated with your CRM, the transcription can get drawn upon to fill out any post-call notes. That’s one job your agents no longer have to do!
For instance, a slightly higher AHT may be preferable if the resolutions provided are better. It’s better all-around for agents to take a little longer but ensure customers aren’t forced to get in touch again a few hours, days, or weeks down the road.
So, what you’re looking for here is the right balance between the time each interaction takes to resolve and the success of the resolution. However, the ACW element of any call is one area you should always be looking to make more efficient. Fortunately, AI can help with this.
For instance, an AI-powered contact center solution can use Natural Language Understanding (NLU) and Processing (NLP) to accurately transcribe calls. If it’s then also integrated with your CRM, the transcription can get drawn upon to fill out any post-call notes. That’s one job your agents no longer have to do!
First call or contact resolution (FCR)
Finally, first call (or contact, in the case of contact center interaction analytics) resolution rates are another vital metric to keep an eye on.
They tell you the rate at which your agents resolve customer queries or issues at the first time of asking. Meaning, customers don’t have to call back or otherwise reach out again for the same reason.
On the face of it, high FCR rates are better. However, be careful not to make FCR the be-all-and-end-all.
An ultimately more satisfactory resolution that takes a couple of calls or contacts is preferable to a single interaction that only just about deals with the issue. The latter scenario may leave customers feeling like all you care about is getting them off the phone as quickly as possible.
They tell you the rate at which your agents resolve customer queries or issues at the first time of asking. Meaning, customers don’t have to call back or otherwise reach out again for the same reason.
On the face of it, high FCR rates are better. However, be careful not to make FCR the be-all-and-end-all.
An ultimately more satisfactory resolution that takes a couple of calls or contacts is preferable to a single interaction that only just about deals with the issue. The latter scenario may leave customers feeling like all you care about is getting them off the phone as quickly as possible.
How do you use call center analytics to track performance?
We’ve already spent a little time discussing how to approach your call and contact center data, and which metrics to keep the closest eye on. How, though, do you translate that into an effective process for tracking and improving performance? Here are some tips:
Define your key performance indicators (KPIs)
You’ve seen our list of potentially useful call center metrics. Your first job is to decide which of those are the best benchmarks against which to measure your contact center’s performance.
These are your KPIs. Noticeable movement one way or another in these areas is what provides your barometer for the success or failure of any changes you make in your call center.
These are your KPIs. Noticeable movement one way or another in these areas is what provides your barometer for the success or failure of any changes you make in your call center.
Continually track agent performance against those KPIs
With your KPIs established, you know what you’re looking for from your agents. The right contact center analytics software will make it easy to create custom reports and dashboards to help you track their performance in these terms.
A key thing here, though, is to not get bogged down in numbers and data and forget the human element. Make sure you also stay in constant contact with your agents. Explain to them clearly why you’re tracking what you are and invite them to provide feedback. They’re on the frontlines so may have insights that might get lost in the data.
A key thing here, though, is to not get bogged down in numbers and data and forget the human element. Make sure you also stay in constant contact with your agents. Explain to them clearly why you’re tracking what you are and invite them to provide feedback. They’re on the frontlines so may have insights that might get lost in the data.
Always keep the customer front of mind
As useful as the quantitative measures of performance that analytics solutions provide are, ensure you don’t focus on them at the expense of your customers. At the end of the day, you’re looking to improve performance and boost KPIs so that you make your customers happier. Better stats mean nothing if that ultimate goal isn’t met. That’s why you should also factor more qualitative analysis into your contact center analytics. Make sure you still reach out to customers and speak to them whenever you can about what your center does well and what you can improve on.
RingCentral contact center analytics
Contact center reporting
Contact center reporting
Track Key Performance Indicators (KPIs) such as AHT and ASA. Display the data in charts, graphs, tables, and other infographics.
Take advantage of over 200 pre-built reports or use custom ones to address your business’ unique reporting requirements.
Monitor trends in real time with customizable dashboards to make informed decisions based on what’s happening in the moment.
Conversation intelligence
Conversation intelligence
Analyze customer interactions to understand customer needs, agent performance, and operational trends.
Use data from each interaction to find opportunities to improve agent and customer conversations and avoid dissatisfaction whenever possible.
Leverage conversational insights to enable effective business decisions.
Customer surveys and feedback management
Customer surveys and feedback management
Capture customer data that gives actionable insights to improve customer loyalty, satisfaction, retention, and experience.
Contact center managers can review agent performance and provide rewards for positive customer feedback and improvement plans for negative ones.
Gather unbiased feedback from different channels and funnel them directly from customer to agent to avoid misinterpretations.
Contact center analytics software
An effective contact center analytics solution allows your organization to gain insight into how your contact center is performing across multiple communication channels. For example, the RingCentral contact center analytics platform supports a wide range of advanced analytics tools to give you different views of the business along with a variety of dashboards that present different types of data.
Learn more about RingCX today
Create effortless employee and customer experiences from one AI-powered platform.
FAQs about contact center analytics software
- Speech analytics - Studying voice recordings to derive insights
- Text analytics - Similar to the above but for text-based communications
- Desktop analytics - Tracking everything that happens on an agent’s desktop to assess efficiency and processes
- Self-service analytics - Collecting and evaluating data on self-service elements such as IVR menus and chatbots
- Predictive analytics - Using data to forecast potential issues and proactively introduce solutions
- Omnichannel analytics - Cross-channel analysis of all customer interactions.
Call center key performance indicators (KPIs) are measurable values or metrics. Companies can look at them to evaluate how well the call center is meeting its goals and whether the agents are meeting the customer's needs when they interact with them via inbound or outbound calls.
Some of the most common contact center KPIs include:
Some of the most common contact center KPIs include:
- Average handling time (AHT) – The length of time between the moment the agent picks up the call until the call is disconnected.
- Average time in queue – How long customers wait in the queue before being connected to an agent.
- Call hold time – Customers are annoyed when they’re placed on hold for a long time. This call center metric measures how long an agent puts their callers on hold.
- First call resolution (FCR) – The contact resolution rate of customer issues that were resolved and didn’t need a repeat call.
- Call abandonment rates – The number of callers who hang up before being connected to an agent for inbound campaigns. For outbound campaigns, this refers to the number of dialed calls where the prospect or customer hung up before talking to an agent.
- Escalation rates – The number of times a call to an agent was escalated to a contact center leader like a supervisor or manager.
- Customer satisfaction (CSAT)– This is a metric that displays how happy a customer is with the service they received during their conversation with the agent. This is usually determined through the use of customer satisfaction surveys.
- Total number of customer interactions – Going beyond the number of calls, this KPI measures the number of interactions on each digital channel, including social media, email, and chat.
- Customer complaint volume – The volume and most common types of complaints you’re receiving per channel.
- Visitor intent – When your customers interact with your organization, what do they need? This metric aims to identify the root cause of most customer issues.
- Customer effort score – This KPI measures the amount of effort customers put into reaching your company just so they can get their concerns addressed. Keeping an eye on this can also reveal why customers prefer companies with other channels like chat and social media.
Contact centers use data to identify pain points and areas of improvement that can help them maximize agent productivity. For example, they can use data to:
- Improve call quality – A lot of the call center KPIs are used to analyze call quality scores, which involves measuring average call handling time, average time in queue, and wait time when customers are on hold.
- Review agent performance – Aside from call quality management, you can also use these metrics for agent performance management to see if they meet the company's standards or require additional training and guidance.
- Understand your demographics – Knowing your customers’ pain points, preferences, t and even demographic information can help your organization figure out better workforce scheduling, branding and marketing campaigns, and sales strategies.
- Identify customer emotions – Knowing your customers' sentiments, in general, gives your idea a glimpse of how customers receive your product or service. You can use that information to craft the right scripts and messaging for your agents.
- Improve customer experience – Organizations use analytics to see how happy customers are with the service provided via the contact center. It allows you to identify areas of improvement in agent performance, employee engagement, hiring and staffing, and workflows and processes.
This can help you increase customer retention while decreasing customer churn. - Increase workforce engagement – Analytics will show you that a more engaged workforce correlates to better customer experiences. Use analytics to get your agents more invested in their jobs (for example, by introducing gamification to processes and workflows).
- Uncover customer lifetime value – Analytics can help you predict on average the reasonable profit that you can earn from a customer attributed to the entire customer relationship with them in the future.
One of the best ways to improve call center operations is by taking a data-driven approach, and employing effective contact center analytics. The right call center analytics software can help you track KPIs, assess agent performance against those, and ID bottlenecks or issues in your processes.
Call center analytics can help you uncover valuable insights around operational efficiency, agent performance, and customer behavior. You can then use these to improve processes, better train your agents, and respond to your customer’s expectations. That is a surefire way to improve your business.
IVR analytics is the process of tracking and evaluating the operation and efficiency of the Interactive Voice Response (IVR) feature of your call center. It includes tracking things like which IVR menu options are most popular, how many callers abandon their calls while using the IVR, and customers’ overall satisfaction with the IVR.
Adding analytics capabilities to your contact center requires not only a financial investment, but also time and effort spent on training and set-up. That’s why it’s crucial to take the time to critically analyze your options to help you choose the best contact center solution for your organization.
Take RingCX and RingCentral Contact Center. They offer not only best-in-class customer analytics, but also omnichannel routing, workforce engagement, automation, and artificial intelligence-powered solutions.
Learn more about contact center plans and pricing.
Take RingCX and RingCentral Contact Center. They offer not only best-in-class customer analytics, but also omnichannel routing, workforce engagement, automation, and artificial intelligence-powered solutions.
Learn more about contact center plans and pricing.
Resources
EBOOKS & GUIDES
Excelling in the experience economy
The rules of customer engagement have changed.
INFOGRAPHIC
Disjointed and disgruntled
How broken communications workflow impacts customer satisfaction & the bottom line.
WEBINAR
Disruptive customer engagement
Join industry analyst Shelia McGee-Smith as she shares how companies are using the cloud to transform customer relationships in ways that disrupt their industries.