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| Criterion |  Product Discovery Kano Model |  UX Research Affinity Diagramming |  Operations Causal Factor 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 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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. |
Complexitydifferent | Medium | Low | High |
Timedifferent | 1-2 Tage | 45–90 min | 2-6 h |
Participantsdifferent | 10-50 | 3-10 | 3-10 |
Formatdifferent | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Theme clusters, Insight statements, Opportunity areas | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions |
Tagsno overlap | SatisfactionPrioritizationCustomer | SynthesisQualitativeRoot cause | CausalityIncidentRoot causeTimeline |
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