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| Criterion |  Knowledge Modeling PARA Method |  Decision Making Decision Tree |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
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. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 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 | Low | High |
Timedifferent | 1-3 h Setup, laufend | 30-90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 1 | 1-6 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Decision Tree, Option Map, Assumption List | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | KnowledgeProductivityOrganization | DecisionTreeOptions | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |