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| Criterion |  Product Strategy ICE Scoring |  Growth Flywheel |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 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 | Low | Medium | Low | High |
Timedifferent | 30-60 min | 60-120 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | ICE Table, Top Idea List | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tags1 shared | PrioritizationScoringGrowthDecision | GrowthRetentionConversion | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |