Measuring the user experience is critical to improving it, and UX metrics are the key to achieving this goal. Different metrics provide insight into different aspects of the user experience.

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1. Behavioral Metrics

These metrics measure how users behave while interacting with a product or service. Some examples of behavioral metrics are:

👉 Click-through rate (CTR)

Measured by dividing the number of clicks on a link or button by the number of impressions (views) of that link or button. The resulting percentage indicates the proportion of users who clicked on the link or button after seeing it. The formula for CTR is:
CTR = (Number of clicks / Number of impressions) x 100%

👉 Time on task

Time on task is measured by tracking the amount of time it takes a user to complete a specific task or set of tasks within a product or service. The formula for calculating time on task is:

Time on Task = Time Task Completed — Time Task Started

By measuring time on task, businesses can gain insight into how long it takes users to complete specific tasks and identify opportunities to streamline workflows and improve the user experience.

👉 Task success rate

This metric measures the percentage of users who are able to successfully complete a task on your website or application. It is calculated by dividing the number of successful task completions by the total number of attempts.

Task Success Rate = Number of Successful Completions / Total Number of Attempts

👉 Bounce rate

Bounce rate is the percentage of users who leave a website or application after viewing only one page or interacting with only one element. The formula to calculate bounce rate is:

Bounce Rate = (Number of Single-page Sessions / Total Sessions) x 100%

A “single-page session” is defined as a session in which a user interacts with only one page or element before leaving. The total number of sessions includes all instances where a user interacts with the website or application, regardless of how many pages or elements they interact with.

👉 Conversion rate

This metric measures the percentage of users who take a desired action, such as making a purchase or filling out a form. It is calculated by dividing the number of successful conversions by the total number of visitors. The formula for conversion rate is:

Conversion Rate = (Number of Conversions / Total Number of Users) x 100%

👉 Error rate

This metric measures the percentage of errors encountered by users while using your website or application. It is important to track this metric to identify and fix any issues that may be causing frustration for users.

Error Rate = Number of Errors / Total Number of Actions

👉Abandonment rate

This metric measures the percentage of users who abandon a task before completing it. It is important to track this metric to identify any areas where users may be experiencing difficulties.

Abandonment Rate = (Number of Abandoned Processes / Number of Started Processes) x 100%

2. Attitudinal Metrics

These metrics measure how users feel about a product or service. They provide insight into users’ perceptions, attitudes, and opinions. Some examples of attitudinal metrics are:

👉 Net Promoter Score (NPS)

This metric measures the likelihood that a user would recommend your product or service to others. It is calculated by subtracting the percentage of detractors (users who would not recommend) from the percentage of promoters (users who would recommend).

NPS = % of Promoters — % of Detractors

👉 Customer Satisfaction (CSAT)

Metric that measures how satisfied users are with a product or service. It is typically measured through surveys or other feedback mechanisms, and is often expressed as a percentage or score. A higher CSAT score indicates that users are more satisfied with a product or service, while a lower score indicates less satisfied.

CSAT = (Number of satisfied customers / Total number of customers surveyed) x 100%

👉 System Usability Scale (SUS)

This metric is based on a user’s overall experience with your website or application. It is typically measured through a survey or questionnaire and provides valuable insights into areas for improvement.

To calculate SUS, you will need to administer a survey that consists of 10 questions, each with a 5-point Likert scale response option.

The questions are:

1. I think that I would like to use this system frequently.
2. I found the system unnecessarily complex.
3. I thought the system was easy to use.
4. I think that I would need the support of a technical person to be able to use this system.
5. I found the various functions in this system were well integrated.
6. I thought there was too much inconsistency in this system.
7. I would imagine that most people would learn to use this system very quickly.
8. I found the system very cumbersome to use.
9. I felt very confident using the system.
10. I needed to learn a lot of things before I could get going with this system.

For questions 1, 3, 5, 7, and 9, participants should respond using a 5-point scale ranging from “Strongly Agree” to “Strongly Disagree” (with scores of 5, 4, 3, 2, and 1, respectively).

For questions 2, 4, 6, 8, and 10, participants should respond using a 5-point scale ranging from “Strongly Disagree” to “Strongly Agree” (with scores of 1, 2, 3, 4, and 5, respectively).

To calculate the SUS score, add up the scores for all 10 questions and multiply the total by 2.5. The resulting score will be between 0 and 100, with a higher score indicating a more usable system.

SUS Score = (Sum of all scores * 2.5) / 10

👉 User Effort Score (UES)

Measures how much effort a user has to exert to complete a task or achieve a goal within a product or service. It is typically measured through surveys or other feedback mechanisms and is often expressed on a scale from 1 to 5 or 1 to 10. A lower UES score indicates that users perceive a task or goal as easier to accomplish, while a higher score indicates higher perceived effort.

UES = (Total Score / Number of Responses) x 100%

👉 Likert scale ratings

Measure the degree to which users agree or disagree with a statement or question. They typically use a 5-point or 7-point scale, where users can choose a level of agreement or disagreement ranging from “strongly agree” to “strongly disagree.” Likert scale ratings are commonly used in surveys and other feedback mechanisms to measure user opinions and perceptions.

Example:

If a survey question asks users to rate their agreement with a statement on a scale from 1 to 5, where 1 is “strongly disagree” and 5 is “strongly agree,” and 10 users rate the statement: 4, 5, 3, 4, 2, 5, 4, 3, 2, 1 (4 + 5 + 3 + 4 + 2 + 5 + 4 + 3 + 2 + 1) / 10 = 3.5

Likert scale rating for this statement would be 3.5 out of 5

👉 Open-ended feedback

Metric that allows users to provide free-form comments or suggestions about a product or service. It can be collected through surveys, interviews, or other feedback mechanisms. Open-ended feedback provides valuable qualitative data that can help businesses better understand user needs and identify areas for improvement. However, it can also be more challenging to analyze than other metrics, as it requires manual review and categorization of user comments

3. Descriptive Metrics

These metrics provide descriptive information about users and their behavior. They help to create user personas and identify patterns in user behavior. Some examples of descriptive metrics are:

👉 Demographics (age, gender, location, etc.)

Provide information about the characteristics of users, such as age, gender, location, and other relevant factors. By tracking and analyzing demographic metrics, businesses can gain insights into the makeup of their user base and tailor their user experience to meet their target audience’s needs better.

Collect demographic data through:

• Surveys
• Analytics
• User profiles

👉 User roles

The User Roles metric is used to measure the number and type of roles that your audience members assume within your brand or community. This metric can help you understand the level of engagement of your audience members with your brand or products.

Identify the different roles that your audience members can assume. These may include customer, subscriber, follower, contributor, or ambassador. Once you have identified the roles, you can calculate the User Roles metric by dividing the number of audience members in each role by the total number of audience members.

👉 Frequency of use

The Frequency of Use metric is used to measure how often your audience members interact with your brand or products. This metric can help you understand how engaged your audience is and how often they are likely to make purchases or take other actions related to your brand.

Track how often your audience members engage with your brand or products over a specific time period, such as a week or a month.

👉 Time of use

The Time of Use metric is used to measure how long your audience members spend interacting with your brand or products. This metric can help you understand the level of engagement of your audience and how interested they are in your content or products.

Track the amount of time your audience members spend interacting with your brand or products over a specific time period, such as a week or a month

👉 Device type

Device Type metrics are used to measure the types of devices that your audience members use to interact with your brand or products. This metric can help you understand the preferences of your audience members and optimize your marketing campaigns or products accordingly.

Track the types of devices that your audience members use to interact with your brand or products. This can include devices such as desktop computers, laptops, smartphones, or tablets.

👉 Browser type

The Browser Type metric is used to measure the types of web browsers that your audience members use to interact with your brand or products. This metric can help you understand the preferences of your audience members and optimize your website or web-based products accordingly.

Track the types of web browsers that your audience members use to interact with your brand or products. This can include browsers such as Google Chrome, Mozilla Firefox, Safari, or Internet Explorer.

👉 Referral source

The Referral Source metric is used to measure the sources that drive traffic to your website or products. This metric can help you understand the effectiveness of your marketing campaigns and the behavior of your audience members.

Track the sources that drive traffic to your website or products, such as search engines, social media platforms, or referral links from other websites.