Connect a design change to product metrics using the HEART framework and the goals, signals and metrics method.
Why it matters
At junior level, designers are judged on the quality of their screens. At mid-level, they are increasingly judged on outcomes: did the redesign help people, and did it help the business? Product managers, engineers and leadership talk in metrics. A designer who can say "this change should reduce failed sign-ups, and here is how we will know" earns a seat in decisions about what gets built.
The core idea: outputs vs outcomes
An output is what the team ships: a new onboarding flow. An outcome is the change it causes: more new users complete set-up and come back next week. Designs are bets on outcomes, and metrics tell you whether the bet paid off.
Product metrics come mostly from analytics (what large numbers of people do in the live product), complementing the usability metrics from small tests (task success, SUS) you met in UX Design Process. Analytics show what and how many; research shows why.
The HEART framework
Google researchers Kerry Rodden, Hilary Hutchinson and Xin Fu published HEART in 2010 as a way to choose user-centred metrics. It has five categories:
| Category | Question | Example metrics |
|---|---|---|
| Happiness | How do people feel about it? | Satisfaction rating, SUS, Net Promoter Score |
| Engagement | How much do people use it? | Sessions per user per week, actions per visit |
| Adoption | Do new people start using it? | % of new users who try a feature in week one |
| Retention | Do people keep coming back? | % of users active again after 30 days |
| Task success | Can people do what they came for? | Completion rate, time to complete, error rate |
You do not need all five for every project. Pick the one or two that match the goal of your change.
Goals, signals, metrics
HEART comes with a simple method to get from a vague aim to a number:
- Goal: what you want to achieve for users, in words. "New users can set up a shared house quickly and without help."
- Signal: what behaviour or attitude would show you are succeeding (or failing). "They finish set-up in one session; few contact support about invites."
- Metric: how you will measure the signal, precisely. "% of new houses that invite at least one housemate within 24 hours; set-up support tickets per 1,000 new houses."
Write a baseline (today's value) and a target before launch, and note any guardrail metrics that must not get worse, such as overall retention or page speed.
Worked example: a redesigned bill-split flow
Design change: replace the "Split equally: Yes/No" radio buttons with a "Change amounts" button and auto-reminders (from usability findings).
| HEART | Goal | Signal | Metric | Baseline | Target |
|---|---|---|---|---|---|
| Task success | People can split a bill unequally without errors | Fewer abandoned splits | % of started splits that are sent | 71% | 85% |
| Happiness | Requesting money feels less awkward | Fewer complaints, better ratings | In-app rating after first split (1 to 5) | 3.6 | 4.0 |
| Retention (guardrail) | The change does not drive people away | Users keep splitting bills | % of houses with a split in the next 30 days | 58% | not lower |
Now the design has a measurable promise. If splits sent rise but ratings fall, the team learns something too. To be confident the change caused the difference, teams often run an A/B test: some users see the old version, some the new, and you compare their metrics over the same period.
Common pitfalls with metrics
- Vanity metrics: page views or downloads that go up without anyone being helped.
- Gaming a metric: optimising "time in app" by making tasks slower.
- Too many metrics: nobody can tell whether the change worked. Choose one primary metric.
- No baseline: without "before", "after" means nothing.
- Ignoring the why: a drop in a metric needs research to explain it.
- Privacy: collect only what you need, follow your organisation's data rules and never track people in ways they would not expect.
Quick recap
- Outputs are what you ship; outcomes are the changes they cause. Metrics measure outcomes.
- HEART: Happiness, Engagement, Adoption, Retention, Task success. Pick the categories that fit the goal.
- Goals, signals, metrics turn an aim into a measurable number; add a baseline, target and guardrails.
- Pair analytics with research: numbers show what, research shows why.
Try it
The Do tab has a quiz on choosing metrics. Afterwards, write a goals-signals-metrics table for one design change in your own project.