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| Criterion |  Product Discovery Kano Model |  Growth Funnel Analysis |  UX Research HEART Framework |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When features need to be distinguished by their effect on satisfaction, it makes expectations and surprises comparable. It separates basic needs, performance contribution, and delight. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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 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 | Medium | High |
Timedifferent | 1-2 Tage | 1-3 h | 120 min initial, dann laufend | 1-4 Wochen |
Participantsdifferent | 10-50 | 1-5 | 3-6 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Funnel report, Drop-off analysis, Optimization hypotheses | HEART-GSM Table, Dashboard | Experiment results, Decision log, Learning summary |
Tagsno overlap | SatisfactionPrioritizationCustomer | AnalyticsConversionGrowth | MetricsUX researchMeasurementSatisfaction | ExperimentsGrowthAnalyticsValidation |