Topic
Metrics
Sooner or later, someone wants a number. Metrics turn 'does it work?' Into something you can track and argue with - but only as honest as what they count.
This cluster covers the numbers UX leans on - how long a task takes, how many people make it through - and, just as importantly, what they leave out. A metric ticking upward is not the same as a person who is better off.
Each entry shows the measure being taken and then poked at, so you can see both what it tells you and where it quietly lies.
The metrics entries 12
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metrics
Time on task
Time on task is how long it takes someone to complete a specific task, from start to finish. It’s the most common efficiency metric in usability testing - and one of the easiest to misinterpret.
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metrics
Conversion rate
Conversion rate is the percentage of completed conversions among a clearly defined group - users, sessions, or opportunities - over a specific time period. The denominator must be explicit for the rate to be meaningful.
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metrics
Task success rate
Task success rate is the percentage of users who complete a task - for example, four out of five users finishing it, which equals 80%. It’s the simplest way to see if something works, though it’s easy to overinterpret.
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metrics
Net promoter score
Net promoter score asks one question - "how likely are you to recommend us?" on a 0 to 10 scale - then subtracts the share of detractors (0 to 6) from the share of promoters (9 to 10). The 7s and 8s are "passives" - excluded from the calculation, not a neutral zero. The result runs from -100 to +100.
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metrics
CSAT (customer satisfaction score)
CSAT asks people to rate their satisfaction after an experience. It may be reported as a mean score or as the percentage in specified positive categories, so the scale and calculation should always be stated.
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metrics
Customer effort score (CES)
Customer effort score (CES) asks one simple question after an interaction: how easy was it to get what you needed? Typically a single agree-scale statement - like 'the company made it easy to handle my issue' - it shifts focus from 'are you delighted?' To 'did we get out of your way?' The goal is that reducing effort keeps people more reliably than trying to wow them.
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metrics
Bounce rate
Traditionally (Universal Analytics), bounce rate is the share of visits where someone lands on a page and leaves without any further interaction - one page, no second click. Modern tools have redefined it: GA4 leads with engagement rate instead and treats bounce rate as simply its inverse - the percentage of sessions that were not "engaged", where an engaged session lasts longer than ten seconds, triggers a key event, or has two or more views. Either way it's easy to misread - a high bounce can mean people couldn't find what they wanted, or found it instantly and left satisfied - and it means nothing until you know what the page was for and which definition your analytics platform is using.
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metrics
Error rate
Error rate is how often people make errors while doing a task - mistakes per attempt, or the share of attempts that go wrong. It's a usability signal, not a verdict on users, and it has many causes: design, task complexity, training, environment, unfamiliarity or who you tested. A cluster of the same error is worth investigating, and the type of error hints at the kind of fix.
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metrics
Retention and churn
Retention is the share of users who keep coming back over time; churn is its near-mirror - the share who leave. They're exact opposites only when measured on the same cohort, interval and definitions; otherwise they can drift apart. Together they show whether a product delivers lasting value or just a first impression, and small, steady churn compounds into a large loss - pouring new users into a leaky bucket never fills it.
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metrics
HEART framework
HEART is Google’s framework for measuring user experience across five dimensions: Happiness, Engagement, Adoption, Retention, and Task success. It focuses on experience quality, not just business output. Its core is the Goals-Signals-Metrics process: state the goal, define what user behaviour signals it, then pick the metric. This ensures you decide what success means before choosing what to count.
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metrics
North star metric
A north star metric is the single measure a team rallies around because it best captures the core value the product delivers to users. It's not revenue and it's not a vanity count - it's the number that goes up when users genuinely get what they came for, chosen so that everyone's work points the same way and short-term wins don't come at the expense of real value.
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metrics
System usability scale
The system usability scale is a short questionnaire with ten statements rated from strongly disagree to strongly agree. It turns how usable something feels into a single score from 0 to 100. It’s quick, standardised, and surprisingly comparable across very different products.
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Know these already? Take the metrics quiz, or revise the terms with flashcards.