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| Criterion |  Growth A/B Testing |  Innovation Design Sprint |  UX Research Affinity Diagramming |  Innovation Design Thinking |
|---|---|---|---|---|
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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. |
Complexitydifferent | High | High | Low | High |
Timedifferent | 1-4 Wochen | 4-5 Tage | 45–90 min | 1 Tag bis mehrere Wochen |
Participantsdifferent | 1-6 | 5-8 | 3-10 | 4-10 |
Formatdifferent | Async | Workshop | Workshop | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Prototype, Test Findings, Decision Rationale | Theme clusters, Insight statements, Opportunity areas | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Design sprintPrototypeValidationInnovation | SynthesisQualitativeRoot cause | InnovationPrototypeResearch |