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| Criterion |  Product Discovery Experiment Canvas |  Decision Making Force Field Analysis |  Product Discovery Fake Door Test |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | 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 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 | Low | Low | Medium | Medium |
Timedifferent | 30-60 min | 45-90 min | 1-5 Tage | 60-90 min |
Participantsdifferent | 1-5 | 3-12 | Nutzertraffic | 3-8 |
Formatdifferent | Workshop + async | Workshop | Async | Workshop |
Outputdifferent | Completed Experiment Canvas, Success Metric | Force Field Map, Change Levers, Risk Notes | Click Data, Interest Signal, Learning Decision | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | ExperimentsValidationDiscoveryHypothesis | ChangeDecisionStrategy | ValidationExperimentsDemandDiscovery | ExperimentsPrioritizationDiscoveryHypothesis |