View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion | ![]() Engineering Failure Scenario Analysis | ![]() Product Discovery Fake Door Test | ![]() Product Discovery Smoke Test | ![]() Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | 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. | 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 | Medium | Low | High |
Timedifferent | 1-3 h | 1-5 Tage | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | Nutzertraffic | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Async | Async | Async |
Outputdifferent | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Click Data, Interest Signal, Learning Decision | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | FailureResilienceRisk | ValidationExperimentsDemandDiscovery | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |



