View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Growth A/B Testing |  Product Discovery Riskiest Assumption Test |  Agile Affinity Estimation |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-2 Wochen pro Iteration | 30-90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 2-6 | 3-12 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Prioritized Assumption List, Test Plan, Results Report | Affinity Size Map, Grouped Estimates, Unclear Items | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryAssumptions | EstimationBacklogRelative sizing | ValidationExperimentsDemandDiscovery |