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| Criterion |  Product Discovery Kano Model |  Growth A/B Testing |  Growth Funnel Analysis |
|---|---|---|---|
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 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 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. |
Complexitydifferent | Medium | High | Medium |
Timedifferent | 1-2 Tage | 1-4 Wochen | 1-3 h |
Participantsdifferent | 10-50 | 1-6 | 1-5 |
Formatdifferent | Workshop + async | Async | Async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses |
Tagsno overlap | SatisfactionPrioritizationCustomer | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth |
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