7 Key usability metrics to unlock user insights

Have you ever launched a new product or feature, only to discover everything you expected users to do... they didn’t? Your team put in countless hours, but it didn’t pay off the way you thought it would—in fact, your user base is shrinking. Whether it’s the UI design, platform functionality, or navigation, something is causing a disconnect.

Enter: usability metrics.

Usability metrics are the specific measurements and type of statistics used to review the usability of your product. They can track how quickly users complete certain tasks, how frequently they make mistakes, their overall satisfaction using the platform, and more. By reviewing different types of usability metrics, you can paint a picture of the user’s experience and understand the overall usability of your product.

Different usability testing methods provide different metrics. Determining which metrics to track is an important step when creating your usability testing plan, as you’ll be able to tailor tests to provide relevant insights.

Usability testing metrics are usually divided into four categories—each providing insights into different areas of your product's usability. With a robust usability testing platform, you can automatically generate reports to digest and organize your metrics. This gives an at-a-glance view of how your product is performing for any key stakeholders—and helps prepare for future sprints.

To maximize your takeaways, include a mix of these four types of metric:

“The biggest benefit to conducting usability testing is that you get to build scalable products with a short learning curve, which then translates into satisfied users,” says Belén Ardiles, Product Designer at StockFink. This benefit can be more easily tapped into if you’re tracking usability metrics, as these will be the backbone of your decision-making process.

Remember: surveys and interviews can give you valuable quantitative insights, but they won’t provide broad statistics or necessarily show you a numerical translation of how your users interact with and experience your product’s UI.

Let’s take a look at some of the other benefits of tracking usability metrics.

Conducting usability and other forms of user testing reduces the risk of test participants falling for the Aesthetic-Usability effect. This effect is a cognitive bias that occurs when users perceive aesthetically-pleasing designs as more usable. While it’s great if a product’s UI is beautiful, it also needs to be functional. Relying on a specific set of usability metrics ensures you have an objective approach to how your design performs, instead of relying on potentially-subjective understandings of what users say they like.

When you're knee-deep in a project, it can be easy to lose sight of the bigger picture—the ultimate goal is to create a user-centric product. If you track usability metrics, you can more clearly identify pain points or areas for improvement within the user experience (UX).

For example, if a high percentage of users are unable to make a purchase, it may be an indication that your product's design or navigation needs to be adjusted to clarify the checkout process. By identifying these issues early on, your product team can steer focus and make data-backed decisions to create a more effective product.

Usability metrics help you decide which improvements are most important right now, and which can be focused on later. Let’s say one of your company’s OKRs is to increase conversion rates by 3% month-over-month. You get these insights from your usability studies:

While all of those usability problems are important, there’s one metric which clearly has a direct impact on your company’s sign-up goals—and ultimately conversion rate—as users are abandoning the task. By identifying this failed completion metric, you can quickly review usability results and start rectifying the problem.

Sometimes different product stakeholders have different opinions. You might think the navigation bar should be black with white text, while a colleague believes it’ll stand out more as white with black text. The team vote is split 50/50, but luckily, you’ve got a usability test coming up. By tracking success metrics, you identify that 83% of users completed navigation quicker with option A. The decision is clear.

Belén Ardiles, Product Designer at StockFink, and her team had a similar experience. “I discovered that if we had developed the prototype as we designed it, we’d have failed to make the app truly intuitive to the end user,” said Belén. “Test participants experienced difficulties around handling alerts and taking proactive steps to get educated and mitigate future risk.”

When you conduct usability tests, your design and UX choices going forward are anchored in user-backed data, so the decision comes down to what’s working and what will benefit your users—rather than internal debates or personal preferences.

Quantitative usability metrics mean you can easily compare results—see how the feature performed last time, and assess if the new design has improved following a change. When you conduct usability tests at regular intervals—from initial concept development to post-launch optimization—you start building a narrative of data that can be used to track your progress and overall success.

Our 2023 Continuous Research Report shows 83% of respondents believe testing should happen at every stage of the product lifecycle. Yet, 78% believe their company doesn’t research enough—product teams see the value in ongoing usability testing, but aren’t able to use continuous research to make decisions throughout the development process.

Whether due to limited resources, budget, or stakeholder investment, it’s clear that regularly monitoring usability metrics like customer satisfaction or engagement rates is invaluable. It can help you identify areas where competitors are falling short, and tailor products to fill these gaps.

When you start determining which usability metrics to track, start by revisiting your project objectives and consider which metrics will best inform those goals. There are a ton of different ways to track the results of usability studies, but these are the key metrics you can’t afford to skip:

The formulas below used have been sourced from various platforms to find the most widely-used formulations for calculating usability metrics. Remember to measure results against your platform's specific goals and benchmarks so you're optimizing for the metrics that matter most to your product and users.

Type: Success metric

The completion rate—also known as a success rate—allows you to assess the percentage of users that can navigate your product intuitively. Task completion is usually presented as a binary value of ‘1’ if users completed the task and ‘0’ if they didn’t.

“The usability metric that helped me the most was completion rate—it allowed me to validate whether or not the software’s main objective was met, and if users were finding it easy to follow the predetermined path. I used the user data to modify the app which added value and gave us an advantage against competitors,” says Belén.

To calculate the task completion rate, you should divide the number of completed tasks by the total number of given tasks and multiply it by 100.

You can calculate completion rate per user or by study. For example, if a participant gets a 10/10 task success, that user would have a 100% completion rate. But, if 8/10 users complete 3/10 tasks, and the other two have a perfect score, your usability study completion rate would be 44%.

#of tasks completed = (8 x 3) + (2 x 10) = 44

Total number of assigned tasks = 10 x 10 = 100

Completion rate = (44 / 100) x 100 = 44%

Type: Success metric

These metrics are an extension of the completion rate and tell you whether the user completed the task as you expected. For example, if you think someone will click on the signup button from the homepage and that’s exactly what they do, it’s a direct success. But, if they go to the login page first and click on the signup button from there, that’s an indirect success.

It’s a good measure of usability if the majority of your users can complete their tasks using the flow you designed. With a usability testing platform like Maze, you can set the expected paths you think users will take as they navigate your platform. If it coincides with the one users take, the result is a direct success.

To measure this metric you’ll need to analyze the expected path and the actions your user took. If you find a match, there was a direct success; if you don’t, it’s an indirect one. You can calculate the percentage of direct or indirect success with the following formulas:

Type: Success metric

This metric is also a way to categorize your completion rate. Unlike direct or indirect success, a user fails when they can’t solve a task and simply abandon it.

It's important to ensure tasks are achievable in the first place before tracking ‘fail’ usability metrics. For example, if a task is designed to be completed in five minutes but across all users it takes an average of 10 minutes to complete, this wouldn’t necessarily be a ‘fail’ usability metric, because they _did _complete the task, but outside the time parameters—and the average result says perhaps the original timeframe was unrealistic.

However, if a task requires users to enter information that is impossible to provide, this would be considered a ‘fail’ in your usability metrics. You’ll recognize this one if you’ve ever been asked to fill in a digital form with a required field that doesn't permit the correct input, e.g. being asked to provide a phone number in a text-only box.

You can measure this by using usability testing tools that record users’ clicks during the usability test. Or, to calculate a fail rate, follow this formula:

Type: Duration metric

Time on screen measures how long a user spends on a particular screen. Users spending a long time on a screen is an indicator they can't find what they’re looking for (except for blog posts or pages with readable content where the user might naturally spend more time). If you review the time on screen along with metrics like misclick rate, you can spot issues with the interface, labels, or layout of the page.

Time on screen is usually calculated by your testing platform. It records the amount of time your user spends on the same screen before moving to a different one. However, if you’re doing this in person, you can calculate it using a stopwatch or clock.

Type: Duration metric

Time on task measures the duration users take to complete a task; users taking too long to complete a task might indicate they can't find what they're looking for or are lost trying to complete the task.

Time on task isn’t a metric that you should review on its own. You need to contextualize the number and try to understand why it’s taking so long for users to complete a task. You want to know if users are taking longer than expected on a task because of the design, copy, instructions, or information architecture.

Similar to time on screen, your testing platform should calculate this as your users go through your test. It can be particularly useful to review screen recordings at the same time, to pinpoint where users are struggling. If you’re doing this in person, you can use a timer to manually measure the time your users spend on each task and have a moderator track where difficulties arise.

Type: Errors

The misclick rate is the average number of misclicks outside the hotspots or clickable areas of your product. This usually happens when your user finds your platform unintuitive or is expecting it to act similarly to other websites.

According to Jakob's Law, “users spend most of their time on other websites”, so they expect yours to function like the ones they already know. If it doesn’t, this can cause usability issues. Review the misclick rate along with a detailed click heatmap to see exactly where your users are clicking, and adjust your design accordingly to clarify.

To calculate your product’s misclick rate, you need to divide the number of misclicks by the total number of clicks and multiply it by 100.

For example, if a user made 15 clicks during the test and three were misclicks, your misclick rate will be 20%.

Type: Errors

This is a pretty self-explanatory metric: it calculates the number of errors your participants make while attempting to complete a task. This can include errors made while performing a task i.e. accidental actions, slips, or oversights. The higher the error rate, the harder users find your product to use.

For example, let’s say your users can’t register because the platform has strict password requirements—if these prerequisites aren’t disclosed to the user, they’ll end up trying different combinations until they make it or give up. A high error rate here might indicate you need to disclose how many letters, numbers, and special characters the password should contain.

To measure this, you simply need to keep count of the times your users make a mistake while completing a task. Depending on the testing tool you’re using, you might get a detailed description of each error so you can classify them. Or, you might get this rate included in an overall usability score.

Type: Satisfaction metric

To test task-level satisfaction, you should ask your users how satisfied they are with the task they attempted to complete. Do this by including a questionnaire of three to five questions at the end of each task.

Your questions shouldn’t be open-ended, and users should be able to answer using a scale, to gather quantitative results. Open-ended questions can be difficult to measure and may result in unclear or subjective responses. For example, asking "How satisfied were you with your experience?" may result in a range of responses that are difficult to compare or analyze.

This metric is relevant to measure user satisfaction and gather insights into what’s causing users to struggle or succeed. Frame questions in a specific, measurable way, such as “On a scale of 1-5 where one is difficult and five is easy, how easy was it to complete this task?" This allows users to answer in a way that is easy to compare and analyze across multiple respondents.

To assess task level satisfaction, use one of these questionnaires:

Type: Satisfaction metric

To assess test level satisfaction, you should use a longer questionnaire (10+ questions) and share it with users as soon as they finish the test session. This metric allows you to understand how a user feels directly after interacting with your platform.

To calculate test level satisfaction, use one of these surveys:

Depending on the usability testing methods you choose to conduct, you’ll measure a different set of metrics—but every type will offer some insight into your users and their experience with your product.

Here’s a quick recap of the usability metrics you should track, depending on the insights you want to get:

If you want to calculate those metrics automatically, opt for a continuous product discovery tool like Maze: you can get all your usability testing results automatically turned into a ready-to-share report, which allows you to instantly act on the data.

It's easy to forget to plan for usability metrics—after all, you'll gather data either way, right?

But if you want to maximize your insights, it's well worth taking the time to consider what types of metric will best inform your product and answer your research questions.

Once you've pinpointed this, you can design your usability test around these metrics, and start gather data that offers a well-rounded, contextualized understanding of your product's usability.