By Rachana Chotia / In Customer Support / February 9, 2021 / 15 Mins read
Customer support metrics provide data on your support team’s performance, efficiency and quality.
Many platforms give you reports and dashboards showing this data, but they do not necessarily explain what they mean. And what’s important is knowing how to improve these metrics.
Peter Drucker is credited for saying one of the most important management quotes:
This saying couldn’t be more true. To know if you are doing something right, you need to measure it. For example, if your goal is to lose weight, you have to step on a weighing machine to measure it. Similarly, if your goal is to provide excellent customer service, you need to measure it. And you need to do it with the right metrics.
Delivering high-quality customer support is important to retain customers. By regularly tracking customer service metrics, you get a good insight into what’s working and what needs to improve.
When you start your customer support function, or to be honest when you start anything new, it’s common to think that now is the time to focus on the service and you can always track the metrics later. But by establishing a clear measuring system early in the system goes a long way.
Identifying the right set of customer service metrics, measuring them consistently and using them for decision making is a sure-fire way to achieve success — for both you and your customers.
Measuring metrics will help you:
Metrics, or in other words Key Performance Indicators (KPIs) can broadly be classified into three categories:
Below is the list of the key customer service metrics that fall under these three categories:
Let’s look at each of them in detail and see how we can improve them
Definition: New tickets is the number of customer support tickets created across platforms and channels.
This metric shows the demand for customer support from your customers. In general, as your business grows, so will your customer base and hence the number of support tickets created.
For this metric, you should consider the tickets being raised on different channels, such as phone, emails, chats, social media, etc. to get an accurate number.
This customer service metric should be measured on a daily, weekly and monthly basis. It not only shows how often your customers need support but also points to the pressure on your support agents.
By regularly tracking this metric, you get an idea on how many people you need in your customer support team to address your customer’s queries. Thereby, letting you plan your staffing needs.
You can reduce the number of support tickets created by proactively communicating with your customers. You can do this by sharing how-to guides, keeping your knowledge-base up to date and accessible and onboarding them on time.
Definition: Unique users are the number of individual users who raise customer support tickets in a given period of time.
Repeat or recurring users are the number of users who raise multiple tickets in a given period of time.
Not all new tickets created are from unique individuals. Some are also created by repeat customers. By subtracting the number of unique users from the total new tickets created, you can find out how many repeat customers are there.
While tracking this customer support metric, you should be worried if you have a high number of repeat customers. While there could be many reasons why they raise multiple tickets, the main reason is that their issues aren’t resolved to their satisfaction. This could lead to lower customer satisfaction.
To reduce the number of unique users raising tickets is by preemptively serving them by sharing relevant information at the right time.
To reduce the number of repeat customers, it’s important to understand where the system is breaking. There could be two possibilities:
Definition: Tickets resolved is the number of tickets successfully solved by the customer support team.
This metric is important because it shows your customer service team’s capacity. If the ratio of new tickets to resolved tickets is high, it means your support agents aren’t able to handle the load. This has a cascading effect as it creates a backlog and eventually leads to lower customer satisfaction.
On the other hand, if you can successfully resolve all tickets that are created, it could mean you are overstaffed. You can assign other tasks to your agents.
You can also go into details here to see the number of tickets resolved by individual agents and find out how productive they are. This way you can identify your top performers and use them as an example to train your underperformers.
It’s a big problem if you have a high number of unresolved tickets. To reduce this number, you can automate some aspects of your customer support like frequently asked questions.
Using a chatbot for this service is highly effective. A lot of tickets can be auto-resolved and the support agents only need to focus on complex queries.
Definition: Hourly customer demand is the hourly break down of when customer support tickets are created.
This customer support metric shows you the demand for support at different hours of the day. By tracking this data, you can identify which hours of the day or days of the week/month you see a surge in customer support tickets.
Depending on your business type, you will notice a trend and can provide a better customer experience. For example, a food delivery company will see daily surges during meal times and a cosmetics company will see a surge of tickets during sales/ festivals.
Based on this information, you can set your agents’ working hours. You can increase the number of support agents handling tickets at those hours. By tracking this metric, you are prepared for surge and ensure your customers are getting a good experience every time.
Definition: Average time spent per ticket is the mean amount of time agents work on an open ticket.
While the definition of this customer service metric is pretty straightforward, the implication is big. This is a clear indication of how productive your agents are.
A similar metric would be the number of interactions per ticket. If the number of messages between the customer and agents is high, it usually means that the time spent on a ticket is also more.
If the agents are spending more time on tickets, it could mean two things:
Whatever might be the case, a high average time spent per ticket indicates your staff is not asking the right questions or is having trouble understanding the customer’s requirements.
One way to reduce the average time spent per ticket is by automating repetitive tasks. When customers can easily find the answers, it takes fewer steps to find the right answers and close the ticket.
If the reason for spending more time on a ticket is the agent’s inefficiency, you can put the agent on a learning and development training. You can also reduce the time spent on a ticket by providing the agents with relevant information in one place. Agents will not have to toggle between different platforms and waste time.
With this information, you can also set the right customer expectations by giving them accurate time estimates of how long it will take to resolve their queries.
Definition: Bot deflection is the total number of tickets closed/resolved by an AI-powered customer support conversational chatbot.
This customer support metric is also a measure of self-service ability. Wherein, you provide a system to your customers through which they can resolve their queries on their own. The automation can be in form of chatbots, voice assistant, etc.
Around 70% number of customers prefer self-service.
The more the customers use self-service option, the better it is for your company. Why?
You can increase the number of tickets resolved by automation by keeping your FAQs and Help & Support pages updated. You can train your chatbot to understand customer intents and show them relevant information to help the customers resolve their issues, quickly and accurately.
The key here is to refresh the data regularly.
Definition: Keywords used by the users are the terms/phrases/keywords used by customers in their queries.
This customer support metric helps you understand what questions/topics your customers are having trouble with. If a topic is being talked about by many customers, it indicates that there is some problem and you need to fix it.
You can also track the categories of questions being frequently asked. If a category is being asked more often than others, you can work on how to improve this section, making it easier for the customers to find relevant information.
With this data, you can improve your frequently asked questions in the chatbot and Help page. If this information is easily available, your customers will not raise tickets for it.
You can also use this data to understand how your users talk and train your customer support staff to mirror the language, making them feel comfortable.
Definition: First response time is the time elapsed between a customer raising a ticket and a support agent first responding to it.
First response time has the same energy as first responders. Just like how the first responder is the first to arrive and provide assistance at the scene of an emergency, first response time is the time taken to first respond to a customer query, providing immediate acknowledgement of the customer.
The faster the response, the better is the customer experience.
The average FRT changes depending on the platform/channel on which the customer is contacting the customer support. It differs for phone calls, chatbots, support agents on live chat, email, etc.
You can calculate the first response time for different channels and identify which is the fastest. You can then promote this channel to your customers so they can resolve their queries quickly. This can have a big impact on the quality of your customer service function.
To respond to a customer asap, it’s best to automate the process. You can install a chatbot on your website to talk to the customer and help them solve their queries by themselves. If the chatbot doesn’t have the answer, it can transfer the ticket to an online agent.
The chatbot can be deployed on social media platforms such as Facebook or messaging platforms such as WhatsApp too.
If the customer is contacting through email, and automated response can be sent to the customer, letting them know of estimated time to hear back from an agent.
Definition: Average handling/resolution time is the average amount of time taken to resolve and close a ticket.
This customer support metric shows how efficient your support team is. In a way, you can say that your customer satisfaction score depends on this one metric.
The clock for this metric starts ticking from the time the customer raises a query to the time the customer’s need is met and the ticket is closed. It includes the waiting time and talk/chat time.
To ensure your team is efficient, prioritise this metric.
You can improve the resolution time by understanding what’s taking the agents time to resolve tickets.
For commonly asked questions, you can automate them. Simple, repetitive questions can be answered by chatbots and knowledge bases, reducing the average resolution time. A chatbot also allows you to use canned responses to reply quickly, helping in resolving the tickets quickly.
One of the common reasons for higher resolution time is the availability of data. The agents don’t have enough information on the customer in one place because of which they have to toggle between different software and platforms, increasing the user wait time as well. This can be easily solved by integrating your CRM tool on the customer support platform and showing all customer information in one place.
Definition: User wait time is the amount of time a user has to wait in between their ticket being picked up by an agent and transferred between agents/departments.
This customer support metric is a measure of the time the customer is expected to wait or be on hold. This usually happens when the customer is being transferred from one agent to another or if the agent is taking time to gather information to resolve the query.
Needless to say, a longer the user wait time leads to customer frustration and irritation. This in turn leads to a poor customer experience.
To decrease the user wait time, you can automate a few processes, such as transferring the ticket to the right person in the right department. You can also provide the agents with all customer data in one view so they have information to help them out, quickly.
Definition: Goal completion rate is the percentage of users who complete a task while conversing with the agent.
GCR measures the number of customers that complete a task. For this, you need to first define your goals. The goals vary from industry to industry. The goal could be to identify the number of users who asked for a refund or the number of people who scheduled an on-site tour.
A high goal completion rate means a lot of your customers are reaching your set goals. On the converse, a low GCR means your goals are not being met.
Once you identify low performing goals, you can work towards how to reduce the number of steps required to achieve the goal. At the end of the day, the aim is to make it easier for the customers. Analyse low performing goals and change the strategy to reach them.
Definition: A backlog is the number of tickets that remain open after the SLA time.
In simple terms, tickets that don’t get closed on time are termed as backlog. Needless to say, this customer service metric should be kept at a minimum. The higher your backlog number, the more unhappy customers you’ll have.
It’s important to define what a backlog is. It depends on what you tell your customers on how long it takes to resolve an issue — it could be 24 hours or a couple of days. If the ticket is not resolved in the timeframe you promise a customer, it’s moved from open to backlog. And it also changes from channel to channel. A call centre or a chatbot has lower SLA than an email.
There could be many reasons for backlogs. Your team could be understaffed, or you are seeing a surge in tickets after a new product/ service launch. Either way, it indicates your customer service team isn’t performing well.
To improve the backlog, you need to understand what’s causing the backlog. Are you understaffed? Are the tickets being missed by agents? Is the complexity of backlogged tickets high?
Once you’ve analysed the tickets in the backlog and found the source of the issue, you can rectify it. Increase your customer support staff, automated commonly asked questions, promote the preferred communication channel, etc.
Definition: A preferred communication channel is the channel from which the customer raises a support ticket.
This customer service metric tells you the customer’s preference in contacting your company for customer support. Based on this data, you can optimise the most preferred channel and improve your customer’s experience even further.
There are many channels of communication these days. From website chatbots to WhatsApp chatbot, social media to call centres, emails to voice-assistants.
This data changes with the nature of your business and your target audience. For example, Baby Boomers prefer email, Millennials and Gen Z prefer messaging.
With this data, you get to know which channels are performing well and which are underperforming.
Underperforming channels should be a source of concern. You should ask yourself if the channel is outdated, are you giving it enough attention, how many agents should be allocated to this channel, if you should continue it or not, etc.
If a channel is performing well, you can consider enhancing the customer experience there.
Definition: Customer satisfaction is a measurement that determines how happy customers are with a company's products, services, and capabilities.
Happy customers are good for business. They:
It is calculated by asking customers questions in the form of a survey and having them answer on a scale of 0-10. They can be categorised into:
It’s a good opportunity to gauge the customer’s experience with your brand. This customer service metric gives you data that can be used to prevent customers from churning.
More often than not, angry customers are more likely to take your survey or leave reviews. To improve CSAT scores, you should encourage your happy customers to complete the survey and reward them with gifts. This way you’ll have a balanced score.
Definition: Net Promoter Score is the percentage of customers likely to recommend a company, a product, or a service to a friend or colleague.
While on one hand CSAT measures the customer’s overall happiness with the company’s services, NPS indicates the impact customer support experience has had on the customer’s perception of the company. Basically, it tells you how likely they are to recommend your business to a friend.
To get this metric, companies should ask the customers questions about how likely they are to recommend and give their reasons by elaborating their answers.
The customers rate the company or the product or the service on a scale of 0 to 10 and can be categorised into:
You can improve the NPS scope by providing product/service features that the customers want. Listen to what customers are asking, ask for more feedback and provide good customer service on time.
Metrics guide your team in the right direction. It’s like driving a car. First, you need to start by understanding getting comfortable with holding/releasing clutch, knowing where is the accelerator and brakes and changing gears. Once you master these things, you can confidently drive and steer your car in the direction you want to go.
Similarly, first you need to identify which metrics you want to track and then start keeping a tab on them. Once you have data, you can steer your customer support in the direction of better customer experience.
By optimising the above-listed metrics, the benefits you see are:
At Verloop.io, our dashboards and master reports showcase these data in a friendly/intuitive manner. If you’d like to learn more, talk to our team to demo the product for you.
Content and Marketing, Verloop.io
Here to write about all things Customer Support Automation. If I’m not writing, I’m either reading or planning a trip.