Design smarter: key UX metrics for data-driven design

Designing with data leads to better user experiences and stronger business outcomes. McKinsey Consulting reports that companies prioritizing this approach are twice as likely to outperform their competition. In this piece, we’ll explore key UX metrics in web design and best practices for applying them.

What is data-driven design

In simple terms, a data-driven approach means making design decisions based on actual user data instead of assumptions. It’s about testing, experimenting, and validating your ideas before rolling them out.

For example, if you notice users dropping off halfway through the checkout process, data can help you pinpoint the issue—maybe it’s the cluttered layout or an unclear call-to-action. Once you identify the problem, you can tweak the design, test it again, and see how users respond.

How data empowers you as a web designer  

You can use data to your advantage. Here’s how:

• Get objective insights. Instead of relying on gut feeling, you can use analytics to understand how users are interacting with your design. This removes bias and boosts user satisfaction and retention.
• Reinforce your voice in a company. In a corporate setting, a data-driven approach gives weight to your design choices. It helps you communicate the value of your work to stakeholders, showing that design directly influences business goals.
• Catch issues early and save resources. When you rely on data, you’re more likely to catch issues early and less likely to go through multiple rounds of “trial and error” later in the design process.
• Stay ahead of trends. By tracking user behavior, you can spot emerging trends and adapt your design to meet new user expectations.

Natalia Treskova, a product designer at Vivid Money, explains why designers need to understand how metrics work. Read her insights based on real experience.

Best practices in measuring UX in web design

It’s important to set the right foundation before implementing a data-driven approach. Here’s what you need to do, step by step.

Define measurable data

Identify the key metrics that matter for your project, like task completion or user satisfaction rates. Make sure these metrics are tied to both user experience and your design goals. For example, if your goal is to reduce checkout abandonment, focus on task success rates and bounce rates.

Obtain baseline data

Before making changes, gather baseline data. This gives you a starting point to measure improvements later. If your current task success rate is 60%, you’ll know any improvement that shows progress.

Run UX experiments and tests

A/B testing is a simple way to compare two versions of a design element, like a button or page layout. Use the results to see which version performs better and move forward with data-backed choices.

Iterate and improve

UX measurement is an ongoing process. Use the data to make tweaks and keep refining your designs. Continuously testing and adjusting will help you stay on top of user needs and business goals.

Six UX metrics to track 

These metrics below focus on how users interact with your site, highlight pain points, and make sure your design meets both user needs and business goals.

Task Success Rate (TSR)

TSR shows the percentage of users who successfully complete a specific task on your site, like filling out a form or making a purchase. A low TSR (typically under 70%) could indicate issues with usability or unclear instructions.

How to measure: Divide the number of successful task completions by the total number of attempts, then multiply by 100. For example, if 50 out of 100 users complete the task, the TSR is 50%.

Time on Task

This metric measures how long it takes a user to complete a given task. Too long or too short can both be red flags—long times could indicate a complicated process, while short times might mean the task wasn’t completed properly. 

Typical benchmarks vary depending on task complexity, but you want to aim for a balance that feels natural.

How to measure: Use analytics tools like Google Analytics to track a task’s start and end times. Average these times across users to find the time spent on the task.

Bounce Rate and Exit Rate

Bounce rate shows the percentage of users who leave your site after viewing only one page, while exit rate measures where users leave your site during their journey. 

A high bounce rate (above 40%) or high exit rates on key sections, like product pages, often signal that users aren’t finding what they expect.

How to measure: Use tools like Google Analytics to track these rates. The bounce rate is calculated by dividing single-page sessions by total sessions. Exit rate is the percentage of users who leave from a specific page, calculated by dividing the number of exits by total page views.

Net Promoter Score (NPS)

NPS measures user loyalty and satisfaction by asking users how likely they are to recommend your site to others on a scale from 0 to 10. Scores above 50 are considered good, while anything below 0 is problematic.

How to measure: Send out a simple survey asking users to rate their likelihood of recommending your service. Subtract the percentage of detractors (those who score 0–6) from the percentage of promoters (9–10). The resulting number is your NPS.

Customer Satisfaction (CSAT)

CSAT is a quick measure of user happiness with a specific interaction or feature. Scores vary, but aiming for 80% or higher is generally considered good.

How to measure: After an interaction, such as a purchase, ask users to rate their experience on a scale of 1 to 5. Then, calculate the percentage of users who rate their experience as positive (usually 4 or 5) out of the total number of responses.

Error Rate

The error rate shows how often users encounter issues, such as failed form submissions or broken links. A high error rate can indicate significant usability issues.

How to measure: Track the number of errors visitors face during a specific task, such as filling out a registration form, and divide by the total number of attempts. For example, if 20 errors occur in 100 attempts to complete the form, the error rate is 20%.

While data-driven design is crucial for making smart decisions, there’s much more to mastering UX. Dive into our list of the best books on UX design and four other must-reads to explore the bigger picture.