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| Criterion |  Delivery Monte Carlo Forecasting |  Product Discovery Fake Door Test |
|---|---|---|
Purposedifferent | Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication. | 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. |
Complexitydifferent | High | Medium |
Timedifferent | 30-90 min Setup, danach laufend | 1-5 Tage |
Participantsdifferent | 1-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ForecastingFlowDelivery | ValidationExperimentsDemandDiscovery |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
