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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of Power-Interest Grid with a method-specific labelled workspace.
Facilitation
Power Interest Grid
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
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.When many stakeholders compete for attention at once, the Power Interest Grid sorts them by influence and stake. It turns individual contributions into a visible selection. The result is captured as a Power Interest Grid and a stakeholder-specific strategy.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
HighLowLowMedium
Timedifferent
1-4 Wochen1-5 Tage30-60 min1-5 Tage
Participantsdifferent
1-6Nutzertraffic2-8Nutzertraffic
Formatdifferent
AsyncAsyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning NotePower Interest Grid, Strategy per StakeholderClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
StakeholdersFacilitationAlignmentPlanning
ValidationExperimentsDemandDiscovery
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