11 Customer Service Metrics to Start Measuring

How do you know where you really stand with customers? Here’s a look at 11 customer service metrics that help companies measure support quality at scale.


Jana Barrett

August 17, 2018

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Customer service has long been an area of focus for marketers and support specialists. After all, 67% of consumers list bad customer experience as one of the primary reasons for churning and 39% of consumers avoid vendors for over 2 years after having a negative experience.

Businesses understand that great customer service isn’t optional–it can make or break a brand’s reputation. Plus, it’s directly tied to revenue as it affects customer happiness and churn rates.

But when it comes to service quality, how do you measure where you really stand with customers? Here’s a look at the top 11 customer service metrics you should start measuring today.

Customer Happiness Metrics

How can you quantify how customers feel about your brand? When it comes to customer happiness, you have to focus on quality over speed. Customers care more about the quality of the answers they get than how quickly they get them. Of course, speed matters, but if a speedy answer doesn’t help, they’ll leave more frustrated than they were before.

To measure customer happiness, turn to CSAT, CES, and NPS®. These three metrics correlate with customer loyalty and retention more strongly than support efficiency metrics.

Customer Satisfaction (CSAT) Score

CSAT surveys measure how customers feel about a specific interaction or experience. To conduct a CSAT survey, you ask: How would you rate your overall satisfaction with the service you received?

Answer choices are graded on a scale, usually from 1-5, where 1 represents completely unsatisfied and 5 represents completely satisfied.

Once customers respond, the average of their scores gives you the overall CSAT score.

Why is CSAT important?

Your brand’s CSAT score indicates how satisfied or dissatisfied customers are with a particular service, product, experience, or interaction. These scores help teams see the impact their actions, campaigns, and initiatives have on customer success.

How do you measure it?

It’s easy to measure customer satisfaction with the prebuilt Customer Satisfaction Score question type. Just add it to your survey, customize your question, and begin distributing CSAT surveys after support interactions. As customers reply, you can keep track of your average score and segment responses by specific criteria (like customer type, region, agent, etc.) to dig deeper into support quality.

Customer Effort Score (CES)

Offering quick and effective support is the surest way to make your customers happy. The Customer Effort Score (CES) has been gaining attention in the support community for years because it focuses on the entire support experience—start to finish—rather than individual interactions.

Instead of asking customers to rate the agent who helped them or share feedback on the company as a whole, CES focuses on how easy or difficult the whole support process is for your customers. This is important, since frictionless support experiences build customer loyalty and combat churn.

While most companies still use traditional metrics like CSAT and Net Promoter Score®, we’re seeing more and more teams shifting to CES to measure their overall performance across channels. As more companies move toward offering omnichannel customer support, CES will continue growing in popularity.

Why is CES important?

Because CES focuses on how easy it is for customers to get help, rather than particular agents or specific experiences, it can give you a big picture view of what’s working and what isn’t in your customer service program.

It’s particularly helpful if you support customers across multiple platforms. You may learn that customers find your knowledge base tough to navigate or that specific channels create more frustration in general.

How do you measure it?

The Customer Effort Score question type presents respondents with a statement (The company made it easy for me to handle my issue) and asks the customer how much they agree or disagree. Each response corresponds to a number (1-7) which is used to calculate your overall Customer Effort Score.

Net Promoter Score (NPS)

Net Promoter Score (NPS) is one of the best-known and most popular scores that companies use to measure customer happiness. It’s based on a simple, straightforward question: How likely are you to recommend our business to a friend or colleague?

Customers rate you a scale from 0 (not at all likely) to 10 (extremely likely). Based on where they fall, you can categorize them as Promoters (9-10), Passives (7-8), and Detractors (0-6). Your overall Net Promoter Score is a good indicator of overall customer satisfaction and advocacy.

Why is NPS important?

At face value, NPS is a pretty simple metric—one score per customer, one overall score. However, you can drive serious business growth with NPS by making the data accessible to all. Marketing can identify potential brand ambassadors by looking at your list of promoters. Customer success can spot upsell opportunities, or prioritize red accounts that need extra love.

How do you measure it?

Like CSAT and CES, you can get started simply by adding the Net Promoter Score question to your survey. We recommend distributing NPS surveys at key moments throughout the customer journey, like after a purchase, before an account renewal, or at set intervals (quarterly, yearly, etc.).

To properly calculate your overall Net Promoter Score, you’ll need to subtract the percentage of Detractors from the percentage of Promoters (% Promoters – % Detractors = NPS).

If you’re using GetFeedback for your NPS survey, you’ll get an automatic summary report with a visual histogram, like the one below. (And when you integrate NPS with Salesforce, you can examine customer feedback against other valuable customer data.)

Self-Service Metrics

Although customers like talking to your support staff over the phone or via live chat, time and effort are saved on all sides when customers can help themselves. The better your self-service content, the fewer cases you’ll get. That means shorter wait times, freed up agent time, and happier customers.

Ultimately, the more time you put into your knowledge base, the more support cases you’ll deflect. But measuring your self-service content is important if you want to maximize its effectiveness. The following metrics will help you measure your self-service experience.

Knowledge Base Article Helpfulness

Some support teams believe that having a searchable knowledge base is enough, reasoning that if a customer wants to find an answer, they can sift through articles to find what they need. But a knowledge base isn’t doing its job if customers have to hunt down answers.

Why is knowledge base article helpfulness important?

Because poorly written or unclear articles will negatively affect the customer experience, you need to measure knowledge base article helpfulness. Helpfulness ratings give you a clear look at which articles are working well and which need updating.

How do you measure it?

Measuring the helpfulness of your knowledge base articles may not seem as straightforward as analyzing survey results. However, it’s easier than it seems. You can embed a GetFeedback survey in your knowledge base (or practically any webpage) with a few lines of code.

And for knowledge bases powered by Salesforce Service Cloud, it gets even better: GetFeedback offers a native survey component for Salesforce Lightning that lets you embed smart, mobile-friendly surveys in every knowledge article. With the Lightning component, you can:

  • Automatically add your survey to every article in your knowledge base

  • Measure the performance of individual articles

  • Trigger alerts to support managers when an article needs improvement

  • Quickly create new cases when a customer needs further assistance

Learn more about GetFeedback for Service Cloud

Knowledge Base Bounce Rates and Time on Page

Customers’ on-page behavior is an important source of insights. If people are spending a lot of time on a particular article, the topic might be complex enough that a tutorial video would help. Or if people tend bounce from an article quickly without submitting a support ticket, then your article is probably doing an effective job.

Examining visitor behavior can clue you into problems you’d otherwise never catch. Plus, it’s just interesting to see how people engage with your self-service content.

Why are bounce rates and time on page important?

Bounce rates can give you a feel for whether someone was able to find the answer they needed from your knowledge base article, especially if they are paired with time on site.

If someone spends 20 seconds on your page, then bounces, it’s unlikely they found the answer they needed. However, if they spend 5 minutes on the page, then left, it’s likely they were able to find an answer to their question.

How do you measure it?

Bounce rates and time on site can be measured through whichever analytics program you use for your knowledge base. While some providers offer built-in knowledge base analytics, others may require you to link up your Google Analytics account.

Case Deflection Rate

Your case deflection rate is the rate that customers are able to find their own answers for problems that they would normally take to your support team. Basically, if your knowledge base or other resource center allows a customer to serve themselves rather than calling your team in for real-time assistance, the case is deflected.

Why is case deflection rate important?

Customers like to help themselves whenever they can. That’s because if they can find the answer on their own, they don’t have to type out their problem, pick up the phone to make a call, or take more time out of their busy day to solve their issue. Instead, they can find an answer in their own way on their own time.

The higher your case deflection rate, the more satisfied your customers are. A higher deflection rate also means your support team can dedicate themselves to handling larger requests.

How do you measure it?

There are a few different ways to measure case deflection rate, but we love how MindTouch approaches measurement. MindTouch uses Google Analytics, and offers a step-by-step tutorial on how you can mimic their process to measure case deflection. One of the ways they reduce case deflection is by offering up relevant articles as a customer is creating a ticket.

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Image Source: MindTouch

Productivity Metrics

Your support system is made up of human beings, and it’s important to measure how they’re doing. How do they come across to customers? How good at they at solving issues?

Some of the metrics we’ll go over may seem at odds with each other. After all, how can you provide the best possible service and also be very fast? The important thing is to focus on what works for your customers and your team.

Remember, quality is more important than quantity or speed. Agents that make customers happy are more valuable than agents that answer a bunch of cases quickly.

Here are the best metrics for measuring agent performance.

First Response Time (FRT)

First response time (FRT) is how long it takes for you to respond to a request for report. Your FRT is the number of minutes or hours that go by before you’re able to respond to a request for support.

Why is FRT important?

Slow response times lead to more tickets. When customers don’t hear back quickly, they’re more likely to call, send additional emails, or ask for support on social media. Plus, it just adds to their frustration if things are already going wrong.

On the other hand, a fast initial response time has been shown to make a substantial difference in satisfaction. According to Zendesk, travel and tourism industries report higher customer happiness than social media companies because of a faster FRT.

How can you measure it?

FRT is easy to calculate and measure. You can get an average FRT by totaling your response times, and then dividing them by the number of cases resolved. This gives you an average FRT.

From there, you can take steps to improve your FRT. No matter what, remember that fast response times don’t necessarily add up to quality service. Zendesk reports that the best customer service experiences are built on efficiency, quality case-handling, and scalable, streamlined processes.

If you’re wondering what FRTs you should be shooting for, take it from Groove. According to their report, most customers expect a reply within 24 hours for email support, and within one hour for support on social media.

Replies per Request

Replies per Request, sometimes called Replies per Ticket, is even more valuable than first response time. Why? Customers get frustrated with continual back-and-forths. They’d prefer a long initial wait time but a quality response.

Why is Replies per Request important?

Lowering your Replies Per Request makes sense—no one wants to send multiple emails to resolve an issue. They want to get their issues solved as quickly as possible without any friction. According to a study by Forrester survey, 73% of customers say that getting their issue resolved in just one reply is a huge contributor to overall customer happiness.

How do you measure it?

Replies Per Request can be measured by the number of messages sent, the number of days that have gone by, or another metric that you believe makes sense for your particular program.

Screen Shot 2017-10-20 at 11.58.31 AM.png

However, if you’re doing support via email, you want to keep your average Replies per Request below two. It’s okay if your support team needs more information from a customer before giving a comprehensive response, but an email thread shouldn’t turn into an endless back-and-forth.

Average Time to Resolution

Average Time to Resolution is how long it takes, on average, for your team to solve a customer’s issue and close a ticket. Average Time to Resolution is similar to Replies per Request—it helps you understand how efficiently you’re solving customers’ issues.

Why is Average Time to Resolution important?

Many customer support departments mistakenly invest a lot of energy into speed. They reason that if they reply to requests as quickly as they can, they’ll have satisfied customers. This simply isn’t the case. If your support team sends too many emails, takes a long time to reply to a second message, or ultimately can’t resolve the customer’s issue, you’re not providing quality support.

How do you measure it?

Average Time to Resolution is usually measured in terms of hours, and often it counts business hours as opposed to real-time hours. If you’re wondering what your goal should be, consider that the industry average is 8.85 business hours, according to MetricNet. Even so, numbers range widely. Some companies have Average Time to Resolution that is as high as 27.5 hours, while some are able to resolve issues in 0.6 hours.

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Business-Level Metrics

Support metrics aren’t just indicators of support performance. They can reveal a great deal about your business and customers overall. How people seek out support tells you a lot about their preferences and needs in general. Here are two business-level metrics that can help you better understand your products and audiences.

Case Categories / Question Types

What topics do customers repeatedly write in about? These sources of repeat frustration can damage your customer experience over time, so identifying them is key.

You need to be measuring case categories and the types of questions you receive. For example, you might receive:

  • Reports on bugs

  • Feature requests

  • Questions on how to perform a certain action

  • Billing issues

  • Cancellation requests

  • Order questions

Why are case categories important?

By capturing case categories, you can see statistics on each topic and adjust your support strategy accordingly. For example, if you recognize that many of your support requests come from a certain product, then you might need to create better knowledge base articles or up-level the issue to your product or engineering teams. This is a fantastic way to keep your product team tuned into customer feedback.

How do you measure it?

You can measure case categories in a number of ways, and it depends a lot on your company. However, many brands measure support requests based on product (requests having to do with Product A or Product B), and some categorize them by department (HR, Finance, Marketing, etc.).

Contact Volume by Channel

Channel preferences can help you determine the best ways to reach new prospects. If customers largely prefer live chat to phone, for example, that’s a pretty good indicator that your customers have more of a millennial mentality when it comes to communication.

That’s why you should measure the metrics by channel. Where do the majority of your requests come from? Is that where you want your audience to meet you?

Why is Contact Volume by Channel important?

It may seem rudimentary, but understanding contact volume by channel can help you understand where to provide the most staffing. It can also give you insight into where your customers are hanging out, which can then be used for marketing campaigns. Companies often offer support on the following channels:

  • Live chat

  • Telephone

  • Email

  • Social Media

  • Online contact forms

  • Text message

How do you measure it?

Although 41% of customers prefer live chat support, and only 3% prefer social media, this may not be the spread for your particular business. Measuring where your support requests come from will help you determine who your audience is and come up with strategies for serving them.

Image Source: Kayako

To accurately measure your Contact Volume by Channel, simply add up the number of tickets you received in a given week or month. (Most service providers will do this for you.) Then calculate percentages based on where those tickets came from. From there, you’ll have an idea of what channels see the most support requests.


In order to provide a stellar customer support experience, you need to understand how you’re performing on all fronts. You can use the above metrics to get to the heart of that.

If you’re struggling to get started, try focusing on your top priority first, whether it’s reducing friction between channels, improving agent performance, or understanding customer preferences at scale. Then, narrow in on the metrics that will help you achieve that goal.

Ready to revolutionize your support organization? Learn how GetFeedback for Service Cloud arms companies with powerful support insights across every channel. Read the Guide

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