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| Criterion |  Growth Growth Experiment |  Systems Thinking Intervention Mapping |  Systems Thinking Future Reality Tree |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | Intervention Mapping translates a need for change into a planned, evaluable program. The method connects target group, determinants, actions, and measurement into a traceable chain. | A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation. | 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 | Medium | High | High | High |
Timedifferent | 1-2 Wochen | 1-5 Tage | 2-4 h | 1-4 Wochen |
Participantsdifferent | 1-6 | 4-12 | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Logic Model, Change Objectives, Intervention Components, Evaluation Plan | Future Reality Tree, Negative Branches, Assumption List, Improved Injections | Experiment results, Decision log, Learning summary |
Tagsno overlap | MarketingGrowthExperimentsLearning | ChangeSystems thinkingCapability | Theory of ConstraintsSystems thinkingChange | ExperimentsGrowthAnalyticsValidation |