User experience (UX) focuses on the design and usability of a website, application, or product. Good UX means that the user can solve their problem or fulfill the need without too much difficulty. This leads to greater user satisfaction, a higher conversion rate, and fewer business costs.
Still, we all know that only user decides whether your product has good or bad UX. Then, how to understand that you and your design team are doing everything correctly and the product is going to provide a great user experience?
UX design KPI examples come in handy here. As Eleken is a team of product designers, measuring KPI performance is one of the components in our work on projects. UX KPIs allow us to measure the success rate of the product in numbers and therefore see how effective the product is. As well, in case we make some changes to the existing design, measuring the right indicators can show whether those improvements work the way we want.
As you may have already understood, in this post we want to discuss what metrics to use to measure user experience and therefore the success of your design solution.
As well, we'll:
- explain the difference between the two main types of UX metrics
- provide you with UX metrics examples
- tell you how to collect data for them
- tell how and when to use these design success metrics.
Main types of UX metrics
UX metrics help you to understand the current state of the UX so that you can decide in what direction to make the improvements. Generally, we divide design KPIs into two types: behavioral and attitudinal.
Attitudinal metrics focus on what users think and say about your product, while behavioral ones focus on customers’ direct interactions with your product. Over time, these indicators will help you track and compare the quality of your user experience.
There are many behavioral metrics, this list will provide the most helpful metrics to measure and track changes in the quality of the user experience:
Pageviews is an engagement metric that shows the number of pages the user has viewed on your site over a time period. It shows if your users are interested in some content on the website, or vice versa have trouble finding certain information. To add the context to this metric it’s best to combine it with other metrics we will discuss next.
- Time per task
Time per task determines how long it takes for the user to complete the task. To get the average TPT score we add the results of each respondent and divide it by the total number of respondents. In most cases, the shorter it takes for the customer to succeed, the better UX your product offers.
- Task Success
This KPI shows the percentage of customers who have successfully completed a specific task (for example, complete the profile, fill in the billing information).
How to calculate:
The more respondents you’ve got, the more accurate the result of Task Success is. As well, take into account if the user completes the task for the first time. This way you can track how their experience changes over time.
- Errors rate
Error rate shows how many times users enter incorrect information (make mistakes while completing the task). It allows you to understand how user-friendly your product is.
There are two ways to calculate the errors rate:
- If it is possible to make one error per task (or there are many error opportunities but you want to track only one) we calculate the error occurrence rate:
For example, three out of twenty users made a mistake when entering their password. We calculate the error rate as follows:
- In case it is possible to make several errors per task you can calculate an average error occurrence:
For example, 5 users were filling in the billing data, this task has 6 error opportunities. User 1 made one mistake, user 2 - three mistakes, user 3 made no mistakes, user 4 made two mistakes, and user 5 - two mistakes. And we calculate the average error occurrence rate:
- Bounce Rate
Bounce rate shows how often users give up on a task, for example filling out payment details. To learn the reason why users bounce, you should combine this metric with some of the attitudinal metrics we are going to discuss below.
Collecting data for behavioral metrics is quite easy. Moreover, in automatic mode, without involving an interviewer or observer in the process. You can collect data for behavioral metrics in web analytics and application analytics, based on user sessions on the site, search history, bug tracking, and so on. So this is an easy and inexpensive way to start tracking UX metrics.
You can also track these metrics with the help of other UX research methods: observation, A/B testing, eye tracking, usability testing.
All these metrics are, of course, important, but they do not give a complete picture and understanding of why you are getting these numbers. And this is where attitudinal metrics come into play.
Attitudinal metrics measure what people say and how they feel about your product. There are fewer of these indicators than behavioral ones, but they are not of less importance. Here are some of them:
SUS (System Usability Scale)
This metric is widely used among UX designers and researchers. It is based on a survey that aims at evaluating the ease of use of a site or product. The survey consists of 10 questions, which the user should answer with a score from 1 to 5 (ranging from strongly disagree to strongly agree).
You can also use this metric to compare your product with competitors’ or with your previous version before improvement. For this purpose, you take each score from respondents, add them together and multiply by 2 to get from 0 to 100 points. The average SUS score is 68.
If you get 68 and more points then everything is OKAY with the usability, in case you’ve got lower than 68 - your product requires optimization.
CSAT (Customer Satisfaction)
It is often important to be aware of the overall level of user satisfaction concerning everything from features to app functionality. UX satisfaction can be measured using the CSAT - Customer Satisfaction score.
CSAT can give you a general idea of how users feel about your product, or it can provide you with more detail on specific features or stages of the customer journey. Typically, the CSAT is based on a scale from 1 (very dissatisfied) to 5 (very satisfied) and asks a question “How satisfied are you with the service/app?”.
But you can also be more specific and ask something like “How satisfied are you with finding the desired good?”, and such
To calculate the percentage of satisfied users, divide the total number of satisfied users (those who voted 4 or 5) by the total number of respondents and multiply by 100.
(Satisfied users/Total number of respondents) x 100 = percentage of satisfied users
NPS (Net Promoter Score)
If users tend to recommend your product, app, or website based on their experience, then your UX is probably good.
To track the NPS you need to ask users only one question: How likely are you to recommend this service/app/website to your friends and colleagues?
Users put the score from 1 to 10, where one stands for “not at all likely” and ten means “very likely”.
According to the results, we divide users into three categories: detractors (those who put from 1 to 6 points), passives (7-8), and promoters (9-10). And calculate the NPS by subtracting the percentage of detractors from promoters.
How to collect data for attitudinal metrics
There are many ways to measure attitudinal metrics but the most popular are polls, user interviews, and widget buttons.
The easiest, most efficient, and least time-consuming way to collect this kind of data is with a CTA you place on a website or app. Users click it whenever they want. You can install such CTAs along the entire user journey or in its specific part.
Polls, unlike a button, are not activated by users, but by your app/website. They tend to be highly targeted, allow you to ask more questions at a time, and segment your respondents.
The two most popular types of polls are slide-out (slides out to the side of the screen) and full-screen (appears right in the middle of the screen). They are also used to recruit users for in-depth interviews or surveys.
User interviews are an easy and effective way to get data/feedback from the customer. During the interview, you ask a user questions on a certain topic that you’ve prepared beforehand.
This method helped us a lot when we were working on the redesign of Gridle, a client experience platform. We conducted six interviews to gather information about their needs and priorities. We transformed the insights from these interviews into an empathy map (you can see it below) to get a deeper understanding of customers.
Remember that quality metrics are not enough to make UX improvement decisions. You will need to "enrich" this data with context and details that are missing. Behavioral and attitudinal UX metrics alone cannot provide answers to all questions.
At the end of surveys, ask open-ended questions so that users can justify their answers and give you more information. This is the only way to understand what experience they received, at what point it was good, and at what point something went wrong.
How to choose the right UX metric
It is impossible to create an objective list of, let us say, "5 best UX metrics to track". There is only a classification into behavioral and attitudinal KPIs for user experience. And first of all, when choosing what to track we should take into account what is important for your customers, your business, and the user experience that you want to measure. And with everything else, Google’s HEART framework will help you.
In 2010, Google experts wrote an article about the framework that helped them choose the right metrics for 20 different products. The essence of Google HEART is to effectively combine behavioral and attitudinal metrics.
HEART stands for Happiness, Engagement, Adoption, Retention, and Task Success. If you look at the description of each item below, you will realize that each of them is either behavioral or attitudinal:
- Happiness includes attitudinal metrics: CSAT, NPS, and SUS.
- Engagement includes usage metrics such as visits per user per week, number of photos each user uploads per day, average session length.
- Adoption and Retention include metrics such as the number of unique users over a while (to differentiate new (adoption) and existing/returning users (retention).
- Task success includes behavioral metrics such as task success rate and error rate.
All of these metrics are useless if they are not tied to some kind of user goal. For example, if your site visitors spend a lot of time on your website, this does not mean that your UX is good. On the contrary, it can mean the opposite - they spend a lot of time just to complete a simple task.
So, firstly define the user goal (What do users want to achieve? How does the product help them reach their goal?) and following it choose the appropriate metric.
“If you cannot measure it, you cannot improve it” – Lord Kelvin
Without constantly tracking user experience KPIs, it's difficult to understand if you're on the right track and that the work you do is meaningful and rewarding.
Don't miss the opportunity to use real-time feedback from users. Use both behavioral and attitudinal metrics to measure, compare and track the quality of the user experience over time. UX metrics will also allow you to see how product changes affect customers and the business itself.
And of course, measuring the success of the user experience alone won’t help to ensure that your business is doing great. Read about key SaaS metrics to measure the right indicators and keep your business on track.