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| Criterion |  Product Discovery Smoke Test |  Decision Making Constraint Analysis |  Product Discovery Experiment Canvas |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Low | Low | Low | High |
Timedifferent | 1-5 Tage | 30-90 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 2-8 | 1-5 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | ConstraintsDecisionPlanningOptions | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |