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| Criterion |  Knowledge Modeling PARA Method |  Product Discovery Smoke Test |  Growth Pirate Metrics AARRR |  Product Discovery Fake Door 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | For products with complex usage paths, overall growth alone is too coarse to reveal bottlenecks. Pirate Metrics breaks the relationship with the product into consecutive stages and shows where the funnel actually leaks. | 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. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | 1-3 h Setup, laufend | 1-5 Tage | 1-2 h Setup, laufend | 1-5 Tage |
Participantsdifferent | 1 | Nutzertraffic | 2-8 | Nutzertraffic |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Interest Metrics, Conversion Signal, Learning Note | AARRR funnel, Metric baseline, Experiment backlog | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | KnowledgeProductivityOrganization | ValidationExperimentsDemandGrowth | GrowthMetricsExperiments | ValidationExperimentsDemandDiscovery |