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| Criterion | ![]() UX Research Personas | ![]() Decision Making Constraint Analysis | ![]() Product Discovery Smoke Test | ![]() Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When target groups stay too vague and teams talk about the same people differently, personas create a shared, solid picture of usage. Condensed profiles make needs, contexts, and differences tangible enough for decisions. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 | Medium | Low | Low | High |
Timedifferent | 1-3 Tage | 30-90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | Internes Team | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Persona Profiles, Needs Summary, Scenario Notes | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ResearchCustomerSynthesis | ConstraintsDecisionPlanningOptions | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |



