Everything You Need To Know About Customer Service Metrics in 2021
Tracking productivity and performance of the customer service function emerged as the #1 challenge of customer service leaders through the pandemic crisis, as per The New CX Mandate report. It isn’t surprising that 79% of these leaders in the US are investing 31% more in measurement and analytics in 2021.
Whether you are starting a new business or have a newly formed customer support function, a strong set of customer service metrics will guide you in measuring customer service efficiently and deliver high-quality support to your customers.
This blog will cover why metrics matter in customer service, the need for a balanced portfolio of metrics, and the top 15 customer service metrics that companies commonly use to measure customer support. If you like to read about a specific metric, use the index below.
- What are customer service metrics and why do you need them
- When and how to set up customer service metrics
- A balanced metrics portfolio: The answer to tracking customer service metrics that matter
- Productivity Metrics
- Customer service performance metrics
- Quality metrics
- Pro tips for finding the right customer support metrics for your business
An effective support function should be driven by a clear and well-understood process supported by objective metrics. Your customer support processes will address the mechanics of how support services are provided, enabling staff members to focus their attention on the customer’s issue.
Examples of these processes include capturing customer information about their issue, reviewing customer contact history, using troubleshooting guides to diagnose issues, escalating to other support resources, and following up to ensure that the customer’s problem is fully resolved.
Customer service agents use tools like ticketing systems, knowledge management databases, customer contact systems, and diagnostic tools to access information and resources that’ll help them solve a customer’s issue more efficiently.
The wide range of processes and tools available to employees may be helpful but can also be distracting. This is where metrics come into play. Customer service metrics enable you to gauge the effectiveness of every process and give quantifiable information to guide your employees about these processes. You can then map out what activities need to be done consistently and also measure the performance of your team of customer service representatives.
A good set of customer support metrics will help you –
- Understand how well your support processes are meeting customers’ needs
- Identify improvement areas that will increase cost-effectiveness and customer impact
- Visualize how your customer service team performance is improving over time
- Set up specific and measurable customer service goals for your team
- Understand capacity utilization and plan resources accordingly
By working on the inputs you derive from customer support metrics, you are better equipped to deliver exceptional customer service leading to satisfied customers, greater loyalty, and a positive brand reputation.
While it might seem like establishing metrics and KPIs are something that can wait until your customer support function starts growing, establishing the right set of customer service metrics from day one, measuring them consistently, and using them to drive decision making can help set your team up for long term success.
Though it may be confusing to figure out what metrics you need while starting a new customer service function, vital customer service metrics help your team grow and mature faster. If metrics are part of your customer service department from day one, employees will be less resistant to changes when your business evolves, and you decide to expand the measurement mechanisms later.
Different businesses have varying objectives for their customer service function, but a standard set of metrics apply to all companies. While you set out to measure customer service and look into the feedback data, remember that, like any other operational metrics, customer service metrics need to be clearly defined and well understood to be effective and actionable. The SMART (Specific, Measurable, Achievable, Realistics, Timebound) guidelines also apply for customer support metrics.
When you build a customer service metrics portfolio, it’s a good idea to relate the metric to the different aspects of your support function. For most companies, there are three aspects of customer support where metrics and KPIs are most helpful:
- Productivity: Understanding the amount of work being done
- Performance: Understanding how long it takes to resolve issues
- Quality: Understanding the impact you are having on customers
A balanced metrics portfolio isn’t just about what you are measuring; it is about what you use the information for. Metrics is a tool to provide insights to leaders and decision-makers that result in operational change.
Some metrics provide insight into what is happening (such as the number of issues raised by customers) – there isn’t much that leaders can do to change these metrics; they can just understand them. Other customer support metrics represent things that can be influenced or controlled – for example, the effort spent working on each issue can be improved through staff training.
Knowing the difference between these two types of metrics can help the organization understand the levers used to tune operational results.
The most basic customer support metrics are productivity metrics which help you understand the amount of work being done within your support function. There are four productivity metrics that every organization should track from day one.
The number of tickets created over a day, a week, or a month is a direct measure of the input to your customer service process and indicates the demand for support services from your customers. Also referred to as the ticket volume, keeping an eye on this metric will help you see how often customers interact with your brand and the frequency of them running into problems with your product.
Note that it’s important to not just track the average number of issues logged during a period but also the specifics of when the request was received. This will help you determine staffing needs, their working hours, and gain a better understanding of your customers’ behavior. For example, you may find customer return requests are more common on certain days of the week or product setup questions are more frequent during certain periods.
Freshdesk gives you the option to drill down on the tickets created by source (Email/chat/widget/phone/social media), priority, status, or type (shipping/onboarding/payments, etc.), which gives a better grasp of the nature of these incoming tickets.
The number of support tickets resolved in a specific time period is a measure of your process output and a simple indicator of the capacity of your support function. If the number of issues resolved each day is consistently less than the number of new issues coming in, it may indicate that you are developing a backlog of work which could cause customer issues to be delayed. Conversely, if all the customer requests that come in during a certain day can be resolved, this could indicate excess support capacity.
Looking at the tickets created and resolved volume trends data over a date range gives you insights on agent productivity, when to expect ticket volume peaks, and helps you allocate resources accordingly.
Monitoring the number of unresolved tickets over a week, month, or a specific period gives you a fair understanding of your team’s workload. When the unresolved tickets are consistently high for a few months, you may have to rethink your team size or structure.
A good way to use this metric would be to combine it with the overall ticket trends data. You can then quickly identify abnormal jumps in unresolved tickets and map them to specific issues that cropped up on a particular day (e.g., website down or server outage problems).
Measuring the active time spent working on support tickets can help you understand how long it takes for an agent to resolve a customer request. This may indicate the need for further training or additional hiring is needed.
It can also provide you a baseline for setting expectations or SLAs with customers – you don’t want to commit to having issues resolved within 30 min if it takes an average of 2 hours to address them.
While productivity metrics focus on the amount of work taking place, customer service performance metrics focus on how long it takes for certain activities. Depending on the complexity of your support processes, there are quite a number of customer service performance metrics you could measure. Make sure to configure the business hours properly before measuring these time-bound metrics.
First response time is the amount of time a customer service agent takes to give the first response to a customer. The average first response time is the average time taken by the agent to send the first response to a ticket over a specific time.
Maintaining a low average first response time and being channel-sensitive with this metric results in happy customers since time-sensitive channels like Twitter, Facebook, and chat have a very low average first response time. You could also consider switching to lower FRT channels like Swedish Fintech company – Klarna did, bringing down their overall first response time to 60 seconds.
The average time taken by a customer support agent to respond to a customer’s message is known as average response time. This metric is calculated on an agent basis and not for every ticket. So if a customer service agent has 12 tickets assigned in a particular time frame, then the average response time would be the time difference between agent response and customer response divided by 12.
Boost average response times by setting up canned responses and solution templates to help agents send the proper response faster.
As indicated by the name of the metric, the average resolution time is the average time taken by the agent to resolve a ticket. Monitoring this customer support metric shows how efficient your agents are and the complexity of support requests at your service desk. Analyzing the average resolution time according to ticket priority will allow you to see if higher priority tickets are resolved quickly unless the case is specifically tricky.
The resolution time counter doesn’t stop when an issue gets transferred between support agents, is pending input from a 3rd party, or is outside of the company’s business hours. The counter stops only when the customer’s need is met.
Our recent study on the speed of customer service clearly shows that longer resolution times don’t negatively impact customer satisfaction as long as customers are acknowledged and sent regular updates of the solution.
Though longer resolution times are okay with customers, it’s a best practice to let customers know how long they’ve got to wait for the issue to be resolved. You can set this by defining Service Level Agreement (SLA) policies for your customer service team. The SLAs can be set in varying standards for response or resolution according to the priority or business impact of an issue.
The resolution SLA % metric is the percentage of tickets that were resolved within the defined SLA.
While working to resolve any customer service query, there will be interactions between the customer and the support agent. Keeping a tab on the number of customer responses and agent responses gives deeper insights into the service agent’s performance or the complexity of the problem.
When the average number of customer responses is way higher than an agent’s replies, it could indicate an unresponsive agent, a misalignment in your customer service strategy, or even a deeper problem in the product, and your customer satisfaction is at stake.
Upskilling and training the customer service representative is one way to tackle such situations. You could also initiate reminders to agents about follow-ups on a customer’s response or trigger timely notifications when a customer’s query needs a reply from the agent.
Quality metrics help you assess how successful your customer support team is in executing its mission of fulfilling customer needs. Some of these metrics also have the element of time attached to them, but they’re primarily focused on customer sentiment that needs to be measured by organizations.
A critical customer service metric, FCR is the percentage of customer issues that were resolved right after the first contact made by the customer. This could mean resolving the issue in a single email, phone call, or live chat session.
While your company may view each call, each chat, each ticket, or each support queue as independent engagement with its own set of SLAs, for the customer, there is only one issue that they are trying to resolve.
Measuring first contact resolution helps you understand how efficient your customer service is and how equipped your agents are in using existing resources and an internal knowledge base to address a customer’s issue quickly.
With 76% of global consumers preferring to solve issues on their own before reaching customer support, you could also explore customer self-service options like AI-powered chatbots, help widgets, and a comprehensive knowledge base for zero contact resolutions.
This score is frequently measured using post-support surveys, which ask the customer to rate their satisfaction with the service received. The score is calculated by adding the number of positive responses received from the customer satisfaction survey and dividing it by the total number of survey responses.
The scores from these surveys give a pulse of customers’ happiness but more importantly highlights opportunities for continuous improvement of the support function.
“Being aware of customer CSAT scores means we can zero down on specific areas to improve. We wanted that opportunity to improve,” says Duncan Tyler, customer service manager of Instaprint – UK’s largest online printer. They soon identified having live chat as a support channel would enhance their customer service and saw a CSAT of 4.8/5 upon integrating messaging channels.
While CSAT focuses on a specific action or time-based triggers, the Net Promoter Score (NPS) is one of the simplest (and most accurate) indicators of the impact the customer support experience has on the customer’s overall perception of your company. NPS reveals how likely your customers are to recommend your product or service to their friends and family.
The NPS metric is also measured from survey responses and uses the concept of ‘promoters’ and ‘detractors’. Customers who are most likely to recommend your company’s products and services fall under the ‘promoters’ category, while detractors are the least likely to do so. You can then calculate the metric using the below formula.
Customer Effort Score is a critical customer service metric that measures how easy (or difficult) it was for the customer to get their issue resolved.
CES is a critical metric because it predicts customer loyalty more accurately as Gartner reveals that 94% of customers with low-effort interactions tend to buy again from the same company. In contrast, only 4% would do the favor in the case of high-effort interactions.
Low-effort interactions refer to NOT making your customers contact your support desk multiple times or repeat issue details to different agents to get an issue resolved. Offering an omnichannel support experience allows you to instantly resolve customer problems across channels without losing context.
This support metric is both an indicator of customer sentiment as well as support team member effectiveness. Escalations are indicators that the support agent requires deeper domain or product knowledge or lacks the resources to resolve the customer’s issue independently. Tracking escalation requests can help you identify areas where additional training and resources can be applied to increase agent effectiveness.
The number of tickets reopened over a particular time period directly indicates that the customer wasn’t happy with the support offered initially and has to come back for the correct solution. Analyzing the reopened tickets metric, you can observe the specific issue that triggers reopens frequently and develop a ‘FAQ’ or solution article to address that specific issue.
You can also take a deep dive and see if a particular agent’s tickets get more reopens and offer upskilling assistance. Giving incentives to customer service agents who offer the right solution at first contact would also help bring down the number of reopened tickets.
#1 Keep it simple
When your customer support function is being set up, remember that less is more. Pick a few meaningful customer service metrics that you know you will use instead of measuring things just because you can.
Choose metrics that are easy to track and measure. If the measurement is difficult or complex calculations are necessary, it will focus more on the mechanics of measurement and away from the operations you are trying to improve.
#2 Focus on actionable insights
The reason companies capture metrics and KPIs is to use them to make decisions to improve operations. Whether it’s evaluating staffing levels, driving process improvements, influencing customer perceptions, or identifying self-service opportunities, the key is ensuring that what you measure can be converted to actionable insights.
#3 Use customer service metrics that are scalable
Expect that as your customer support function grows, you will outgrow your metrics portfolio and need to expand it to measure some things in more depth and other facets of your processes that your initial metrics don’t capture. You establish a set of metrics from day one to create a good starting place and foundation for future growth.
You may need more advanced customer service metrics soon. So don’t hesitate to re-evaluate your metrics as new questions, new support channels, and shifts in customer behavior arise.
Freshdesk offers comprehensive reporting and analytics features to monitor agent productivity, performance, and customer experience, complete with live dashboards and curated reports. You don’t just get to capture these support metrics but also analyze helpdesk trends with ease.
With the right set of processes, tools, customer service metrics, you can get your customer support operations off to a strong start – providing the insights you need to execute today and prepare for tomorrow.
Originally published on May 28th, 2018. Updated on August 24th, 2021.