View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Product Discovery Fake Door Test |  UX Research User Interviews |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 1-5 Tage | 30–60 min per interview | 1-4 Wochen | 30-60 min |
Participantsdifferent | Nutzertraffic | 1 participant per interview | 1-6 | 1-5 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Click Data, Interest Signal, Learning Decision | Interview Notes, Themes, Insight Summary | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ValidationExperimentsDemandDiscovery | QualitativeResearchCustomerDiscovery | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |