Most brands keep a close eye on sales numbers, marketing performance, and other parts of the business that generate revenue. But they don’t do a great job measuring customer support performance, usually because they don’t understand the link between customer experience and revenue.
Your customer support team might already measure how quickly you respond to support tickets, which is a great start. The list of metrics we share below paint a fuller picture of the larger impact customer support has on business growth. And once you can demonstrate your impact on business growth, you can start making the case for better tools and more staff.
Track these customer support metrics, improve them, and watch your customer loyalty, repeat purchases, and revenue rise.
Why should ecommerce businesses track customer service metrics?
Happy customers are the best fuel for growth. In other words, the performance of your customer support team (and overall customer experience) has a direct impact on your bottom line. Customer service metrics help you understand — and improve — the value that customer service brings to your business.
Understand customer support’s impact on revenue
90% of American consumers say that customer service is a deciding factor in whether or not they will do business with a company. Potential customers might ask a question about delivery or the product before making a purchase. And shoppers depend on quality support experiences after the purchase for a great end-to-end experience. If you flub that chance, they may never come back.
Existing customers are also your biggest spenders, and they rely on quality customer support to stay loyal. According to Gorgias research, repeat customers generate 300% more revenue than first-time customers of ecommerce brands. We estimate that by increasing your repeat customer base by 20%, you could increase your revenue up to 6%.
Measure the quality of your customer experience
Customer experience is mission-critical — see above for its impact on your revenue — but it isn’t easy to measure. That’s because it encapsulates your on-site shopping experience, customer support interactions across many channels, post-purchase interactions like shipping and returns, and so much more.
Customer support metrics help you evaluate your customer experience across all those touchpoints so you can benchmark your team’s performance, communicate your performance with company leaders, and find opportunities for improvement.
Find specific, actionable opportunities for improvement
As we just mentioned, tracking a full suite of customer support metrics can also help you find specific areas of improvement. If you don’t keep track of many customer support metrics, you’ll only have extremely high-level impressions and small samples of customer feedback to paint a picture of your strengths and weaknesses.
But if you have real-time tracking for a wide range of metrics, you can better diagnose the problem and find a strategic solution. For example:
- If your average resolution time is longer than eight hours, you might create new templated responses to help your agents send fast, helpful answers
- If your contact rate is too high, you could create more self-service resources such as chatbots, self-service flows, or knowledge bases to deflect more low-impact support requests
Make a case for additional training, staffing, and tools
Concrete metrics are great ammunition for your customer service team when making the case to business leaders for more budget to hire additional agents and purchase additional tools.
You can communicate which projects have produced early improvements to argue for more investment. For example, if you set up an FAQ page and see lower contact rates, you can expand the page to a fully-fledged help center.
You can also quantify challenges to make a case for more tools. For example, say your agents often ask customers to repeat information or lose time copy/pasting order information from your ecommerce platform to customer support conversations. You could make the case a helpdesk that unifies all your customer support channels and store data in one platform.
Likewise, metrics can help you forecast your customer service staffing needs and proactively hire customer service agents before it’s too late.
25 key customer service metrics for ecommerce
Below, we describe 25 of the most essential customer service metrics for your team. Some metrics have to do with the performance of your team — like how quickly and well you respond to tickets. Other metrics look deeper at the impact your team has on larger company goals, like customer retention and revenue generation.
We’ll also share how to calculate each of these metrics. For some, a simple formula will suffice. For others, a dedicated tool like a helpdesk or survey automation tool will save tons of time.
That said, here are the top customer support metrics to track:
1) Customer satisfaction (CSAT)
Customer satisfaction (CSAT) is a metric to measure your customer base’s level of satisfaction with their experience. CSAT is one of the most important measurements because satisfied customers return to your store, refer friends, leave reviews, and unlock reliable revenue for your brand.
CSAT compiles responses to a very simple question: “How would you rate the help [Agent] gave you?” You can use a survey or a website feedback widget to ask customers to rate on a scale of 1 to 5 how satisfied they are with a support experience.
CSAT aims to get an overall benchmark for your team’s performance, plus information about the service experience each agent provides. If this score suddenly drops or peaks, you should act fast to see what happened. For example, you may be sending delayed or unhelpful responses after launching a new product, getting a spike in ticket volume, or changing a policy like refunds and returns.
How to calculate this metric
Calculate your customer satisfaction score by asking a question like, “How would you rate your satisfaction with the goods/services you received?” Then, you would give the customer the option to respond on a scale of 1-5. The scale would look something like this:
- Very unsatisfied
- Very satisfied
With Gorgias, you can automatically send one of these surveys after each interaction with customer support.
Once your customers respond, you’ll need to use the responses in this formula if you don’t have a helpdesk that does it automatically:
(Total number of 4 and 5 responses, or “satisfied customers” / number of total responses) x 100 = CSAT
An example of this could look like this:
(126 4 and 5 responses) / (300 total responses) x 100 = 42% CSAT, which indicates you aren’t doing a great job of satisfying customers.
If you use Gorgias, you can automatically send customer satisfaction surveys and track your scores over time. Learn more about our satisfaction survey and dashboard:
Want to obsess over customer happiness? Check out our Director of Support's guide to measuring and improving customer satisfaction (CSAT) scores.
2) First response time (FRT)
First response time (FRT) is a metric that tracks how long it takes for you to reply to the first message in a conversation with a customer. Top performing companies using Gorgias have an average first response time of .54 hours. However, the benchmark varies per channel: aim to respond to email tickets within 24 hours and live chat messages within 90 seconds, according to Klipfolio.
How to calculate average first response time
Calculating your average first response time is relatively simple — most helpdesks will report this number for you. If you don’t have a helpdesk, you can find first response times for tickets by comparing the time stamp when you first received the customer request with the timestamp of the first response. If you received the message at 8 AM on Monday and respond at 8 AM on Tuesday, your first response time is one day.
Add up all of your first response times from the period of time you’re looking to analyze — for example, one month — and then divide that number by the total number of resolved tickets during that same time frame:
Total first response times during chosen time period / total # of resolved tickets during chosen time period = Average first response time
Using real numbers, here’s an example of what this calculation looks like:
74,000 seconds / 800 resolved tickets = 92.5 seconds (average first response time)
Learn how to improve your customer service response times with our full guide
3) Average resolution time (ART)
Average resolution time (ART) refers to the amount of time it takes for your customer support team to fully solve the customer’s problem and close the ticket. We analyzed data across about 6,000 ecommerce companies using Gorgias to provide customer support and we found that the top-performing companies have an average resolution time of 1.67 hours.
Inside Gorgias, your average resolution time is automatically tracked. In your account, you’ll get visual reports showing your average resolution time in a given time period.
How to calculate average resolution time
To calculate average resolution time, also sometimes referred to as “mean time,” begin by choosing a specific time period to analyze. Then, total up the length of all of your resolved conversations with customers during that time period. Once you have that number, divide it by the number of conversations had during the time period you’ve chosen to analyze:
Total duration of resolved conversations / # of customer conversations = Average resolution time
Want to solve customer issues faster? Read our Director of Support's guide to resolution time.
4) Support performance score
Support performance score is a metric Gorgias created that combines average first response time, average resolution time, and CSAT for a single score out of five that serves as a concise representation of your customer service performance. If you could only track one customer service metric — which we do not recommend, by the way — it would be this one.
Support performance score balances these three metrics to represent three of the most important elements of quality support:
- Speed, with first response time
- Helpfulness, with average resolution time
- Customer satisfaction, with CSAT score
How to calculate support performance score
Support performance score is calculated with a series of thresholds for CSAT, FRT, and resolution time. You have to meet the threshold in each category to reach the next level. Here are the thresholds for FRT, for example:
- Level 1 (poor): 13+ hours
- Level 2 (lagging): 12 hours
- Level 3 (fair): 6 hours
- Level 4 (strong): 1 hour
- Level 5 (exceptional) 10 minutes
If you use Gorgias, you’ll see your support performance score over time, plus a breakdown of each metric that makes up your score.
5) Average reply time
Your average reply time (or average response time) refers to how long it takes for you to respond to any customer support message, not just the first message of a ticket. Your average response time should be similar to the first response time. You don’t want to keep customers waiting, even in prolonged conversations.
How to calculate average response time
To find your average response time, add up the total time your team has taken to respond to requests during a specific time period. Then, divide that number by the total number of responses your team sent during that time period:
Total time taken to respond during chosen time period / number of sent responses = Average response time
6) First contact resolution (FCR) or single-reply resolution rate
You know what customers absolutely love? When they can get their issues resolved with a single interaction. Single-reply resolution rate calculates what percentage of your tickets are handled with the first reply. It’s also known as the first contact resolution rate or FCR.
Single-reply resolution rate = Total number of requests resolved with one interaction in a single time period divided by the total number of requests in the same time period.
How to calculate this first contact resolution
To find your single-reply resolution rate, you can simply divide the number of support issues that were resolved on the first reply by the total number of tickets that are FCR-eligible (FCR-eligible means only including tickets that are possible to give a resolution in one response). As a formula, it would look like this:
Number of support issues resolved on first contact / total number of FCR-eligible support tickets = FCR rate
7) Conversation abandonment rate
Conversation abandonment rate is a metric to understand how frequently your customers abruptly end interactions with customer support before reaching a clear resolution.
Whether the conversation is happening via email, chat, or phone call, conversation abandonment signals something larger is wrong. Most conversation abandonment happens after customers wait too long or become frustrated by poor service.
How to calculate conversation abandonment rate
To calculate this metric, all you need to track is the number of abandoned incidents and the total number of incidents. In this context, “incidents” refers to either calls, emails, or live chat sessions. Once you have those two numbers, you can plug them into the following formula:
Conversation abandonment rate = (Number of abandoned incidents / Total number of incidents) x 100
8) Unresolved ticket rate
Your average number of unresolved tickets is a very important metric to track because unresolved tickets are a leading indicator of unhappy customers. You don’t want too many unresolved tickets piling up. Set a company-wide goal for the maximum number of unresolved tickets per day, week, and month.
Your unresolved ticket rate includes all abandoned conversations, which you read about in the above section. They also include any tickets where the support team couldn’t provide a real solution, plus tickets that your support team forgot to follow up on.
How to calculate unsolved ticket rate
Similarly to ticket volume, you don’t need a specific formula to calculate your number of unresolved tickets. Rather, all you need is a reliable system (whether it’s a helpdesk or a process) for keeping track of how many tickets are left unresolved after a certain length of time.
9) Customer effort score (CES)
According to The Effortless Experience, 96% of high-effort customer experiences drive customer disloyalty. In other words, the amount of effort across your entire customer journey has a huge bearing on the success of your customer experience and, by extension, your brand’s revenue.
By measuring CES, you and your team members can work towards reducing customer effort, which in turn will increase the lifetime customer value and the likelihood of word-of-mouth referrals.
You may be wondering what exactly is considered “high effort.” This could include long wait times when a customer calls in or reaches out via email, or not getting a concise response — which leads to time-consuming back-and-forth. Of course, “effort” is subjective and highly dependent on the individual customer and their expectations.
How to calculate customer effort score
To measure CES, you’ll need to utilize another survey. The questionnaire should ask the customer how much effort they had to exert in order to get their question answered. For example, “[insert company name] made it easy for me to handle my issue.” Then, you’d provide a scale of 1 to 10. A score of 1 would be “strongly disagree,” while 10 would be “strongly agree.”
Once you’ve collected the data, you can calculate your average customer effort score:
Total sum of all responses / total number of responses = CES
10) Customer contact rate
Customer contact rate measures the percentage of active customers who contact support each day, month, or year.
A high customer contact rate is an indicator that your customer experience is confusing and unclear. It also means your agents will be swamped with tickets and may not have enough time to provide quality responses.
A high contact rate might also drive down revenue: a customer support interaction is 4x more likely to drive disloyalty than it is to drive loyalty, according to The Effortless Experience. While you want to make your interactions as helpful as possible, you’re better off giving customers a clear, effortless experience without having to reach out to support in the first place.
You can drive down customer contact rate with clearer self-service resources, like an FAQ page and shipping and returns policies.
How to measure customer contact rate
Divide the number of customers who contact your customer service team for help over the course of a month by the number of total customers. Then, multiply that number by 100.
Contact rate = (Number of customers who contact you in a month / Total number of customers) x 100
11) Average ticket handle time
The average handle time (AHT) is an important metric to track if you offer customer service via phone. In today’s online world, most ecommerce companies handle tickets only with chat and email. However, very large ecommerce brands may choose to provide phone call support as well.
The average ticket handling time includes the total talk time and total hold time for that caller. You can calculate the average for larger periods of time to get better insights, such as per week or per month.
How to calculate average handle time
To find your average ticket handling time, add up the total time spent on all voice tickets within the time period you’re analyzing, including talk time, hold time, and follow-up time. Then, divide that number by the number of tickets a customer support agent handled on all channels within that same period of time:
Total voice ticket time / # of total tickets touched = Average handle time
12) Self-service resolution rate
Want to know how well your self-service strategy — whether that’s automated chat conversations, self-service chat flows, a blog, or any other self-service resource — lowers customer and agent effort?
You can separate out tickets that did not have a customer support representative work on them, and that were resolved only with automation. You can also track the amount of views your self-service resources get to understand how many tickets they deflect entirely.
How to calculate self-service resolution rate
Finding your total self-service resolution rate is a bit difficult because you don’t have a ticket to open or close. You can track views on your self-service resources to understand whether they’re being adopted, and track changes to your contact rate to see if they reduce the number of tickets coming in.
Automated support resolution rate is a little easier to calculate:
Automated support resolution rate = Total number of requests resolved with only automation in a single time period divided by the total number of requests resolved with automation, manual support, and a combination of both (in the same time period).
(Solved tickets with automation / total tickets received) x 100 = Resolution rate
Interested in helping your customers help themselves for a low-effort experience? Check out our VP of Success's guide to customer self-service.
13) Social media brand mentions
How frequently your brand is mentioned on social media is a critical metric to track if you want to provide incredible support and get on top of PR disasters. You should have a good benchmark for how often your brand is mentioned per day and per week. If the number spikes, then one of your products might have gone viral, or you’ve got a PR nightmare happening.
You can pay attention to brand mentions with a social listening and brand monitoring software. It’s also smart to use a helpdesk built to manage social comments.
How to calculate this metric
To keep an eye on your social media brand mentions, you’ll need to tap into a social listening tool, as mentioned above. You can certainly try to do this manually and track it all in a spreadsheet, but similar to tracking the volume of tickets, digital software will make this process easier and more efficient.
14) Social media support tickets
Customers’ issues do not only exist in your desired support channels like email and chat. Do you get support tickets on social media? Rather than fight against this trend and attempt to ask customers to submit a ticket via chat, you should respond and help them. Just don’t share sensitive data, of course.
Measure the number of social media support tickets that you get every day, week, month, and quarter. When that number grows, it’s not necessarily a bad thing. It could mean that more of your customers are interacting with your social media profiles. However, it’s still important to pay attention to the benchmark metrics and key performance indicators (KPIs). Sudden changes could represent an issue with your product or shipping speeds.
With Gorgias, you can track and respond to every support ticket that comes through social media — or any channel — from within the helpdesk:
How to calculate this metric
Unfortunately, there isn’t a clear-cut way to measure and analyze social media support tickets, so we encourage you to use a social listening tool that allows you to do a number of things. For instance, tracking brand mentions on social media, as well as how many tickets are coming in through your social platforms during various periods of time. Having all of your social metrics in one place will make them much easier to analyze than pulling them one-by-one out of several different spreadsheets.
15) Net promoter score (NPS)
Similar to the CSAT, the NPS is a common metric for measuring customer satisfaction. Customers will rate on a scale from 1 to 10 how likely they are to recommend your business to a friend. It’s best to measure this regularly, so you can determine your company’s benchmark and look for any drops or spikes in the average rating.
You can use a feedback widget on your website to collect this data, or include the quick survey at the bottom of emails for transaction or shipping updates.
Want to raise your NPS? Check out our in-depth guide to measuring and improving net promoter score.
How to calculate net promoter score
To calculate your net promoter score, you first need to gather data using a customer survey. Send a survey to customers after they make a purchase that asks them, “On a scale of 0 to 10, how likely are you to recommend [products or service] to a friend or colleague?” On this scale, 0 would be not at all likely, and 10 would be extremely likely.
Customers fall into three categories based on their responses to these surveys: promoters (scores 9 or 10), passives (scores 7 or 8), and detractors (scores 0 to 6). Once you have all the data collected, you can apply the numbers to this formula:
Total % of promoters - total % of detractors = Net promoter score
16) Converted tickets
The number of support tickets your customer support team converts into a purchase shows the value of your customer support team in cold, hard cash. We count a ticket as converted whenever a customer places an order within five days of contacting customer support.
Customer support agents can provide helpful pre-sales answers to new customers asking about things like product sizing or your returns policy. Likewise, a helpful interaction after a purchase could make a customer feel confident and loyal enough to place a repeat purchase.
With Gorgias, you can measure your converted tickets and other revenue statistics in a convenient dashboard. Converted tickets can be from self-service, or automated, and manual responses.
How to calculate converted tickets
Before you start calculating, make sure that both numbers are from the same time period. Then use this simple formula to calculate your converted tickets:
Total number of sales within five days of a customer support interaction / total number of tickets = Ticket conversion rate
17) Revenue backlog
Revenue backlog helps you measure how much revenue your business will see in a coming period. This metric is especially for ecommerce brands with a subscription-based model.
Keeping tabs on your revenue is vital to ensuring the growth and continued success of your brand. By tracking your revenue backlog, you’ll be able to see if revenue is going to drop before it actually does.
How to measure revenue backlog
To determine your revenue backlog, you’ll just need the sum of the values of your customers’ subscriptions. If you don’t exclusively sell subscription packages, you’ll need to use tools like Dataweave or Y42 to measure upcoming revenue.
18) Tickets closed per agent
You might also want to measure the number of tickets closed per agent for a certain time period. For example, you could look at the number of tickets each agent is closing per day to spot differences in productivity. You could look at a longer period of time, such as per month, to find which agents are consistently closing more tickets, assuming they each work the same number of hours.
This will help you discover the agents who deserve praise and bonuses, and which ones might need training. If you find an agent that is always closing too few tickets, it may be time to let them go, unfortunately.
With Gorgias, this metric is automatically tracked in your account:
Plus, you can zoom out to understand trends among agents over time, to compare performance or plan your weekly coverage schedules:
How to calculate this metric
To calculate the number of tickets closed per agent, take the total number of tickets closed during a certain time period and then divide it by the number of agents working during that same time period:
Total # tickets closed / # of agents = Tickets closed per agent
18) Ticket quality
Ticket quality isn’t a metric on its own, but it’s a metric you can create to score your agents’ tickets and work toward a consistent quality of response.
We recommend all customer support teams develop a sort of rubric that defines, in objective terms, what a “good” response looks like. The rubric can include things like:
- Response time
- Level of empathy
- Adherence to brand voice
- Correctness (or adherence to company policies)
Your agents will appreciate having concrete goals for their tickets. Plus, you will have an easier time holding agents accountable to standards if they’re written down. You can, and should, regularly update your rubric as you dig into data to understand what ticket qualities actually produce the best results.
How to measure ticket quality
As we said, this isn’t exactly a metric to measure. So instead, we’ll recommend that you spot check each agent’s tickets against this rubric. This doesn’t have to be an intimidating process. Some support companies have weekly ticket breakdowns where the entire team — or team leadership, for larger companies — discuss and score tickets against the rubric to get on the same page about ticket quality.
20) Template utilization
Templated responses save your agents a lot of time and, by extension, mean customers get answers faster. If you don’t have a customer support platform, you can create templated responses in Gmail to answer common questions like, “Where is my order?” (WISMO). If you use helpdesk software, you can also likely add pre-written responses agents can use for each channel. At Gorgias, we call these Macros.
You can get statistics on the utilization of your Macros in any given time period. You can then compare this to the use of tags. For example, if the tag “Cancel Order” was used 100 times in one week, but the Macro was only used 50 times, then that means that your reps only used the Macro half the time.
Talk with your reps about why they’re underutilizing certain Macros. You might need to improve the copy of the Macros or add more variables to make it more useful. Or, you might simply need to remind new reps about the Macros feature.
How to calculate this metric
If you don’t use a helpdesk, you’ll likely have to manually review tickets to see when the template was and wasn’t used. Helpdesk software will automatically report on template utilization.
21) Repeat customer rate (RCR)
Your company will always have two types of customers: new customers and repeat customers. Tracking both is important, but tracking repeat customers specifically will help you determine if your retention efforts are working. Repeat customers also have a larger impact on overall revenue: Repeat customers generate 300% more revenue than first-time customers, according to data from Gorgias merchants.
The value of repeat customers is compounded by the fact that retaining a current customer is five times less expensive for a business than finding a brand new customer.
How to calculate repeat customer rate
To calculate your repeat customer rate (RCR), you can divide your number of repeat customers by your total number of customers, then multiply that by 100. This means that in order to calculate the RCR properly, you need to already be tracking repeat customers versus new customers. The formula for RCR is as follows:
(Total repeat customers / total paying customers) x 100 = RCR
Using real numbers, here’s an example of what the RCR calculation looks like:
(80 repeat customers / 230 paying customers) x 100 = 34.78%
22) Customer retention rate (CRR)
As mentioned previously, retaining customers is always less expensive than finding new customers. That’s why customer retention rate (CRR) is a vital metric. Ecommerce companies in particular have an average CRR of about 30%, according to Omniconvert, so if your company’s CRR is lower than that, it could be a sign that your customer support isn’t as effective as it could be.
How to calculate customer retention rate
To calculate CRR, you will need the following information: number of customers at the end of a given time period (E), number of customers gained within that time period (N), number of customers at the beginning of the time period (S).
Then, plug those numbers into this formula:
CRR = [(E-N)/S] x 100
23) Net retention rate (NRR)
Net retention rate, sometimes called net dollar retention (NDR) or net revenue rate, measures the percentage of recurring revenue retained from your existing customers over a month, quarter, or year. Klipfolio reports that a good NRR is anywhere between 90% and 125%, depending on your brand’s niche, product, and total addressable market (TAM).
This metric is most common among SaaS companies and subscription-based ecommerce companies, but it can absolutely apply to all types of ecommerce brands and even other industries.
How to measure net retention rate
Net revenue retention depends on your business model — it’s easier to calculate for subscription companies than companies that sell standalone products. That said, here’s the formula for net retention rate:
NRR = [(Monthly recurring revenue (MRR) at the start of a month + expansions + upsells - churn - contractions) / MRR at the start of the month] x 100
24) Customer churn rate
Customer churn rate measures the amount of customers your business loses over a given time period.
Customer churn is a more common metric for SaaS businesses and other subscription-based business models because those business models can easily spot the moment when an active customer cancels their subscription, or churns.
However, all businesses, including ecommerce businesses without subscription-based products. But ecommerce businesses might find revenue churn rate, which we discuss below, easier to track.
How to measure customer churn rate
To calculate customer churn rate calculation, gather the total number of customers who were with your business at the beginning of a time frame and the number of active customers at the end of the time you’re analyzing. Then, use this formula:
[(Customers at the beginning of the time period - customers at the end of the time period) / Customers at the beginning of the time period] x 100 = Customer churn rate (%)
Read our ecommerce churn rate article for more information on both customer and revenue churn rates.
25) Revenue churn rate
Revenue churn measures changes in your store’s incoming revenue from existing customers. Businesses that sell standalone products might find this more simple to track than customer churn rate, which is better geared toward subscription-based businesses.
Revenue churn rate is easier to conceptualize and measure because you’re measuring changes in revenue from existing customers, which is a clear-cut number for every type of store, not changes in existing customers themselves. Th
Formula for calculating revenue churn rate
First, find your monthly recurring revenue (MRR) — or the incoming revenue you got from existing customers — at the beginning of the month and subtract that from your MRR at the end of the month. Divide that amount by the total MRR at the beginning of the month. Here’s the formula:
[(Revenue from at the beginning of the time period - revenue from customers at the end of the time period) / Customers at the beginning of the time period] x 100 = Churn rate (%)
Track and improve your customer service metrics with Gorgias
Now that you have all the important customer service metrics and formulas to support your customer success program, you may be ready to explore a product to help make tracking it all easier. A centralized customer service software like Gorgias can help save you and your team hours upon hours of time. That time you can spend getting back to what you do best: great customer support.
The Gorgias platform connects all of your integrations and allows for robust analytics tracking, so you can:
- Track support performance
- Monitor agent-by-agent live statistics
- Measure revenue generated by your support team
- Launch customer satisfaction surveys
If you’re on a mission to measure how your customer service team performs (and stacks up against the rest of your industry), check out our benchmark report.