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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
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.In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures.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.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.
Complexitydifferent
MediumLowHighLow
Timedifferent
1-3 h20–45 min1-4 Wochen1-5 Tage
Participantsdifferent
1-5Small cross-functional group1-6Nutzertraffic
Formatdifferent
AsyncWorkshopAsyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesRisk list, Mitigation plan, Assumption logExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
AnalyticsConversionGrowth
RiskDecisionFailurePlanning
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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