UX metrics: what to measure, the HEART framework and a worked redesign

Design reviews often end in opinions. UX metrics replace them with numbers: whether people complete the task, how long it takes, how many mistakes they make and how it feels. This guide lists the useful metrics, explains Google’s HEART framework, and walks through a checkout redesign measured with both behavior and survey data.

What are UX metrics?

UX metrics are quantitative measures of how well a product's user experience works: whether people can complete tasks, how long it takes, how many mistakes they make, how they feel about it, and whether they keep using it. They let design teams compare versions, set targets and show the effect of design work in numbers rather than opinions.

UX metrics fall into two families:

• Behavioral metrics measure what people do: task success, time on task, errors, abandonment, frustration clicks.
• Attitudinal metrics measure what people say: satisfaction, perceived ease, likelihood to recommend.

Both are needed. Users who succeed slowly and grudgingly may still churn; users who say they love a feature but never use it are not evidence of value.

The most useful UX metrics

On SUS, a score of about 68 is the commonly cited average across many studies, so a score above 68 is above average and one below it signals usability problems.

Frameworks: Google HEART and goals–signals–metrics

Google researchers Kerry Rodden, Hilary Hutchinson and Xin Fu proposed the HEART framework for measuring user experience at scale:

For each dimension you choose a goal (what the experience should achieve), the signals that show progress, and the metrics that turn signals into numbers. Not every project needs all five dimensions; a checkout redesign might focus on task success and happiness, a new feature on adoption and retention.

Pick a goal, signals and metrics for each dimension you use.

Worked example: measuring a checkout redesign

An online store redesigned its checkout: one page instead of three, address autocomplete and clearer error messages. The team defined HEART metrics before launch and compared four weeks before and after (sample figures):

The completion lift of 6 points on 40,000 checkout starts a month means about 2,400 more orders. The team was careful about what not to claim: the repeat-purchase change (21% → 22%) was within normal month-to-month variation, so it was reported as "no detectable change," not as a win.

The behavioral data also found one problem the usability test had missed: rage clicks clustered on the "Apply discount" link, which collapsed the field instead of opening it on some Android browsers. It was fixed in the following week.

How to choose UX metrics

1. Start from the user goal of the flow you are changing, not from the metrics available.
2. Pick one primary metric per project and two or three supporting ones.
3. Combine behavioral and attitudinal measures: one tells you what happened, the other how it felt.
4. Add a guardrail that should not get worse, such as error rate or support tickets.
5. Set the baseline before you ship and agree on what change would count as success.
6. Check significance before claiming small differences, especially on small usability tests.

Common mistakes

• Using NPS as a usability metric. It measures loyalty, which depends on price, support and brand too.
• Reporting averages for time on task. Times are skewed; use the median.
• Ten-person tests as precise numbers. 7 of 10 vs 9 of 10 is a signal, not a precise rate.
• Measuring after launch only. Without a baseline there is no comparison.
• Too many metrics. A dashboard with 30 UX metrics leads to none being acted on.

Measuring UX in TapCub

TapCub covers the behavioral side from live traffic. Funnels give completion and drop-off for any flow (Build a funnel, Read funnel drop-off). Monitoring › Errors lists rage clicks (at least 3 clicks on the same element within 500 ms) and error clicks (a script error within 1 second of a click) per page. Heatmaps show where people click and scroll (Create a heatmap), and form tracking shows which fields cause abandonment (Track form submissions). Collect attitudinal scores such as SUS or CSAT with your survey tool and send them as event properties to compare them with behavior. Related reading: UX analytics, User friction and How to read a heatmap.

See also: Dead clicks.

See also: UX audit, UX optimization.

See also: What is product experience (PX)? Definition, metrics and examples.

Sources

• Rodden, Hutchinson and Fu, Measuring the user experience on a large scale: user-centered metrics for web applications (Google, CHI 2010).
• MeasuringU, Measuring usability with the System Usability Scale (SUS).