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| Criterion |  UX Research Affinity Diagramming |  Product Discovery Opportunity Scoring |  Product Discovery Kano Model |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | 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 hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Low | Medium | Medium | Medium |
Timedifferent | 45–90 min | 60-120 min | 1-2 Tage | 60-90 min |
Participantsdifferent | 3-10 | 3-6 | 10-50 | 3-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Opportunity Score Table, Top Outcomes | Kano Matrix, Feature Classes, Priority Themes | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | SynthesisQualitativeRoot cause | PrioritizationDiscoveryOutcomesNeeds | SatisfactionPrioritizationCustomer | ExperimentsPrioritizationDiscoveryHypothesis |