View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  UX Research HEART Framework |  Growth Growth Experiment |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | 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. | 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 | 120 min initial, dann laufend | 1-2 Wochen | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-6 | 1-6 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | HEART-GSM Table, Dashboard | Experiment card, Result summary, Next bet | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | MetricsUX researchMeasurementSatisfaction | MarketingGrowthExperimentsLearning | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |