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| Criterion |  Product Strategy Lean Canvas |  UX Research Surveys |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Medium | Medium | Medium | High |
Timedifferent | 45-90 min | 3-14 Tage | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-6 | 50+ | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Lean Canvas, Core Assumptions, Experiment Backlog | Survey Results, Charts, Segment Insights | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | StartupLeanAssumptionsBusiness model | QuantitativeResearchValidation | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |