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| Criterion |  Agile Bucket System |  Product Discovery Fake Door Test |  Product Discovery Learning Card |  Agile Affinity Estimation |
|---|---|---|---|---|
Purposedifferent | When a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | 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. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. | 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. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 30-90 min | 1-5 Tage | 25-40 min | 30-90 min |
Participantsdifferent | 3-12 | Nutzertraffic | 1-5 | 3-12 |
Formatdifferent | Workshop | Async | Workshop + async | Workshop |
Outputdifferent | Bucketed Backlog, Relative Estimates, Split Candidates | Click Data, Interest Signal, Learning Decision | Learning Card with evidence and next action | Affinity Size Map, Grouped Estimates, Unclear Items |
Tagsno overlap | EstimationBacklogRelative sizing | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryLearning | EstimationBacklogRelative sizing |