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| Criterion |  Growth A/B Testing |  Product Discovery Fake Door Test |  Architecture LASR (Lightweight Approach for Software Reviews) |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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 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. | LASR helps development teams identify where their software falls short of important quality goals and which improvements to consider. A small group with existing system knowledge can make an initial assessment and investigate open questions in more detail. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 1-5 Tage | 3–4 h for initial assessment; preparation and deeper analysis additional | 30-60 min |
Participantsdifferent | 1-6 | Nutzertraffic | 1 or a small team; particularly suitable for 3–4 people | 1-5 |
Formatdifferent | Async | Async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Lean Mission Statement describing the software’s purpose, Prioritized quality goals and evaluation criteria, Risks and estimated gaps against quality goals, More closely examined findings and open checks | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | ArchitectureQualityRiskAssessmentLean | ExperimentsValidationDiscoveryHypothesis |