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| Criterion |  Decision Making Impact Filter |  UX Research Surveys |  Growth A/B Testing |
|---|---|---|---|
Purposedifferent | With new ideas or requests, the conversation often turns to solutions too early and to effect too little. An Impact Filter forces the initiative into an effect perspective and checks whether it creates a relevant difference. | When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | 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 | Low | Medium | High |
Timedifferent | 20-45 min | 3-14 Tage | 1-4 Wochen |
Participantsdifferent | 1-6 | 50+ | 1-6 |
Formatdifferent | Workshop + async | Async | Async |
Outputdifferent | Impact Filter, Success Criteria, Next Step | Survey Results, Charts, Segment Insights | Experiment results, Decision log, Learning summary |
Tagsno overlap | ImpactOutcomesFramingDecision | QuantitativeResearchValidation | ExperimentsGrowthAnalyticsValidation |
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