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| Criterion |  Knowledge Modeling PARA Method |  Product Discovery Pretotyping |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | The PARA Method organizes knowledge into Projects, Areas, Resources, and Archives. It creates order when digital notes, files, and tasks no longer cleanly fit current work. | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 1-3 h Setup, laufend | Stunden bis wenige Tage | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1 | 1-4 | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | KnowledgeProductivityOrganization | ValidationDemandMVP | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |