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| Criterion |  Growth A/B Testing |  Product Strategy ICE Scoring |  Growth Growth Experiment |  Delivery Cost of Delay |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | 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. | Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence. |
Complexitydifferent | High | Low | Medium | High |
Timedifferent | 1-4 Wochen | 30-60 min | 1-2 Wochen | 90-180 min |
Participantsdifferent | 1-6 | 2-8 | 1-6 | 3-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | ICE Table, Top Idea List | Experiment card, Result summary, Next bet | CoD Table, Prioritization Sequence |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | PrioritizationScoringGrowthDecision | MarketingGrowthExperimentsLearning | PrioritizationDeliveryEconomicsDecision |