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| Criterion |  Delivery Monte Carlo Forecasting |  Product Discovery Smoke Test |  Growth Funnel Analysis |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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 | High | Low | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | 1-5 Tage | 1-3 h | 30-60 min |
Participantsdifferent | 1-8 | Nutzertraffic | 1-5 | 1-5 |
Formatdifferent | Workshop + async | Async | Async | Workshop + async |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Interest Metrics, Conversion Signal, Learning Note | Funnel report, Drop-off analysis, Optimization hypotheses | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ForecastingFlowDelivery | ValidationExperimentsDemandGrowth | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryHypothesis |