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| Criterion |  Knowledge Modeling PARA Method |  Growth North Star Metric |  Product Discovery Assumption Mapping |  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. | When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Medium | Medium | Low |
Timedifferent | 1-3 h Setup, laufend | 1-2 h | 45-60 min | 1-5 Tage |
Participantsdifferent | 1 | 3-8 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | North Star metric, Input metric tree, Measurement cadence | Assumption map, Test backlog, Risk ranking | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | KnowledgeProductivityOrganization | GrowthMetricsAlignmentRetention | AssumptionsRiskExperimentsValidation | ValidationExperimentsDemandGrowth |