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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Failure Mode and Effects Analysis
Operations
Failure Mode and Effects Analysis
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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.For a process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability.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 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
MediumHighLowHigh
Timedifferent
1-3 h2-6 h1-5 Tage1-4 Wochen
Participantsdifferent
1-53-10Nutzertraffic1-6
Formatdifferent
AsyncWorkshopAsyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesFMEA Table, Risk Priority, Mitigation ActionsInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
RiskQualityOperationsRoot cause
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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