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| Criterion |  Knowledge Modeling PARA Method |  Growth North Star Metric |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
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 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. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 1-3 h Setup, laufend | 1-2 h | 30-60 min | 60-90 min |
Participantsdifferent | 1 | 3-8 | 1-5 | 3-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | North Star metric, Input metric tree, Measurement cadence | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | KnowledgeProductivityOrganization | GrowthMetricsAlignmentRetention | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |