methodatlas
Compare

View methods side by side.

Choose up to four methods. Add them using the search and share the comparison by copying its link.

Criterion
Paper illustration for Flywheel.
Growth
Flywheel
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree Analysis
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Purposedifferent
Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.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.For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie.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
MediumHighMediumLow
Timedifferent
60-120 min1-4 Wochen1-3 h1-5 Tage
Participantsdifferent
3-81-62-8Nutzertraffic
Formatdifferent
WorkshopAsyncWorkshopAsync
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogExperiment results, Decision log, Learning summaryCause Tree, Evidence Notes, CountermeasuresInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
GrowthRetentionConversion
ExperimentsGrowthAnalyticsValidation
Root causeTreeIncidentQuality
ValidationExperimentsDemandGrowth
Add more methods