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| Criterion |  Growth A/B Testing |  UX Research User Interviews |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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 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 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. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | High | Low | Low | Medium |
Timedifferent | 1-4 Wochen | 30–60 min per interview | 30-60 min | 60-90 min |
Participantsdifferent | 1-6 | 1 participant per interview | 1-5 | 3-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Interview Notes, Themes, Insight Summary | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | QualitativeResearchCustomerDiscovery | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |