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| Criterion |  Growth A/B Testing |  Product Discovery Fake Door Test |  Operations Ivy Lee Method |  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 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. | With a restless workday full of too many open items, the method creates radical simplicity. It directs attention to a short sequence instead of a broad, still-open field. | 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 | Medium | Low | Medium |
Timedifferent | 1-4 Wochen | 1-5 Tage | 5-10 min daily | 60-90 min |
Participantsdifferent | 1-6 | Nutzertraffic | 1 | 3-8 |
Formatdifferent | Async | Async | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Daily Priority List, Completion Notes | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | PrioritizationProductivityExecution | ExperimentsPrioritizationDiscoveryHypothesis |