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| Criterion |  Decision Making Delphi Method |  Growth Flywheel |  Growth Growth Experiment |  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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 | Medium | High |
Timedifferent | 1-4 Wochen | 60-120 min | 1-2 Wochen | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 3-8 | 1-6 | 1-6 |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Experiment card, Result summary, Next bet | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | GrowthRetentionConversion | MarketingGrowthExperimentsLearning | ExperimentsGrowthAnalyticsValidation |