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| Criterion |  Decision Making Delphi Method |  Domain Modeling Context Map |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | When several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries. | 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 | High | Medium | Low | High |
Timedifferent | 1-4 Wochen | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Context Map, Integration Patterns, Boundary Notes | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | Domain-Driven DesignBoundariesStrategy | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |