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| Criterion |  Agile Affinity Estimation |  Decision Making Delphi Method |  Product Discovery Fake Door Test |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 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 | High | Medium | Low |
Timedifferent | 30-90 min | 1-4 Wochen | 1-5 Tage | 30-60 min |
Participantsdifferent | 3-12 | 6-30 Experten | Nutzertraffic | 1-5 |
Formatdifferent | Workshop | Async | Async | Workshop + async |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Expert Forecast, Consensus Range, Assumption Notes | Click Data, Interest Signal, Learning Decision | Completed Experiment Canvas, Success Metric |
Tagsno overlap | EstimationBacklogRelative sizing | ForecastingExpertsDecisionStrategy | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryHypothesis |