UX metrics are the indicators that show whether your product design strategy is working or not. They also allow you to track design changes over time and see how your product performs in dynamics.
The number of UX metrics is ever-growing and questions like “What metrics are the most valuable for my project?” are very popular among product creators. It is tempting to measure everything and hope that, ultimately, you will be able to distill valuable insights out of the raw data. But it’s better to avoid that temptation.
In this article, we will discuss what UX metric really is, define two categories of metrics and review the most common types of metrics.
What is a metric?
Metric is quantitative data that you collect & analyze and, hopefully, make better design decisions based on this analysis.
Two categories of UX metrics
It is worth mentioning that most metrics in the product design field are marketing-oriented, not experience-oriented. They can tell you how successful your recent marketing campaign was in terms of the number of sales, but not how good your user experience is. For this article, I’ve tried to use only the most common UX metrics (although sometimes it’s really hard to distinguish UX metrics from marketing metrics).
It’s possible to define two categories of metrics — behavioral (what users do) and attitudinal (what users say).
Behavioral metrics tell you how users interact with your product and what problems they face along the way. Most behavioral metrics mentioned below are relevant to the usability (ease of use). Good usability is an integral part of UX because when users can’t complete their goals in your product, they quickly find an alternative solution. Behavioral metrics can be collected during lab usability testing or using analytics tools.
Time on task
Time on task is a time that a user spends doing a particular activity, usually an absolute number (seconds, minutes, hours). This metric works perfectly for task-focused activities, where the user goal is to get something done as efficiently as possible. For example, for an online shopping experience, you can track the time it takes for the user to submit a new order.
Average session length
Average session length is an excellent metric to measure user engagement. Generally, the more time users spend in your app, the more engaged they are and the more they enjoy an experience you offer. For social media apps, it can be the average time users spend in app.
The abandonment rate is the ratio of the number of abandoned purchase attempts to the total number of initiated transactions. This metric is especially relevant to the online shopping experience because a high abandonment rate can strongly indicate that something is wrong with your checkout experience.
The user error rate is the number of users who made mistakes while completing a task. For example, users can accidentally choose the wrong action or make an unsuccessful attempt to enter data in the contact form. Most of the time, errors are closely related to usability issues. You can calculate the error rate by dividing the number of attempts that had errors by the total number of attempts.
Problems encountered by many of your users are an excellent candidate for solving. Thats’ why this metric can help you identify areas in your product that your users are struggling with it.
Attitudinal metrics will tell you how users perceive your product. Attitudinal metrics are adoption (Which features people use?), satisfaction (Do your users enjoy your product?), credibility (Do your users trust your service?), and loyalty(Do your users plan to use your service again?).
Daily/Monthly Active Users (DAU/MAU)
How many people use your product on a daily/weekly/monthly basis. Tracking DAUs and MAUs can help you measure user retention. Good retention trend is when the number of active users is higher than the number of new users.
The DAU/MAU ratio, also known as stickiness, is the proportion of monthly active users that engage with your product every day. If you have a ratio of 50%, it would mean that your users engage with your product 15 out of 30 days.
Net Promoter Score (NPS)
Net Promoter Score (NPS) is a simple survey with only one question. You ask your users, “How likely is it that you would recommend our product to a friend or colleague on a scale from 1 to 10?”. Those who respond with a score of 9 or 10 are called ‘promoters.’ Those who respond with a score of 7 or 8 are called ‘passive’. Those who respond with a score of 0 to 6 are called ‘detractors.’ The NPS score is calculated by subtracting the percentage of detractors from the percentage of promoters.
NPS is a fast way of providing feedback to users. Basically, it’s only one question. At the same time, it lacks any customization, and it can be hard to understand why a particular person provided the score ‘7’ without asking follow-up questions. Another downside is that NPS requires a large sample size.
Customer satisfaction score (CSAT)
Measuring: Satisfaction, Loyalty
CSAT will tell you how satisfied a customer is with a particular interaction or overall experience. CSAT is collected in a format of a questionnaire or online survey. Unlike NPS, which measures overall customer loyalty towards your brand, CSAT measures how satisfied customer is with a specific part of your product. The problem with this type of method is that not all users are willing to spend their time filling out the survey.
User Retention Rate
User retention rate is the percentage of users who have stayed with you over a given period of time. This metric can tell you whether your retention strategy is working or not. To calculate the user retention rate, you need to subtract the number of acquired users throughout a period from the number of users at the end of the period and then divide it by the number of users at the beginning of the period.
System Usability Scale (SUS)
Measuring: Satisfaction, Loyalty
System Usability Scale (SUS) is a set of questions you ask to assess the usability of a product (how easy it is for users to accomplish what they want to do). It consists of 10–12 statements that users need to rate on a scale from strongly disagree to strongly agree. The great thing about SUS is that it requires a relatively small sample size.
So, what metrics should I choose for my project?
Unfortunately, there is no universal set of metrics that work for every project. That’s why the first thing you need to do when choosing metrics is to learn your business model and KPIs your organization tracks. Learn what has a significant impact on your business bottom line and select metrics to help you understand that.
Second, always tie selected metrics back to design decisions. It will help you track changes over time and benchmark against iterations. You will be able to see whether your design decisions work as expected or not.
Last but not least, remember that data only tells part of the story. It can tell you what’s happening but not why it’s happening. So it’s essential to conduct qualitative studies such as user interviews and contextual inquiries to understand why something is happening. When you pair UX metrics with qualitative research, it will help you create a bigger picture of how your product performs.