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Selected:Hypothesis-Driven TroubleshootingFake Door TestHypothesis Prioritization CanvasExperiment Canvas
| Criterion | ![]() Engineering Hypothesis-Driven Troubleshooting | ![]() Product Discovery Fake Door Test | ![]() Product Discovery Hypothesis Prioritization Canvas | ![]() Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable. | 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. | 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 | Medium | Medium | Low |
Timedifferent | 30-240 min | 1-5 Tage | 60-90 min | 30-60 min |
Participantsdifferent | 1-6 | Nutzertraffic | 3-8 | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop | Workshop + async |
Outputdifferent | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary | Click Data, Interest Signal, Learning Decision | Prioritization Canvas, Hypothesis Backlog | Completed Experiment Canvas, Success Metric |
Tagsno overlap | TroubleshootingProblem solvingDiagnosis | ValidationExperimentsDemandDiscovery | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsValidationDiscoveryHypothesis |



