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| Criterion |  Product Discovery Kano Model |  UX Research User Interviews |  Facilitation Dot Voting |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
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 teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | When a workshop has produced too many options and the group needs to condense quickly, dot voting makes preferences visible in a short time. It bundles individual votes into a solid signal for the next selection. | 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 | Medium | Low | Low | Medium |
Timedifferent | 1-2 Tage | 30–60 min per interview | 5-15 min | 60-90 min |
Participantsdifferent | 10-50 | 1 participant per interview | 3-20 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Interview Notes, Themes, Insight Summary | Ranked list, Consensus signal, Shortlist | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | SatisfactionPrioritizationCustomer | QualitativeResearchCustomerDiscovery | FacilitationVotingConsensusPrioritization | ExperimentsPrioritizationDiscoveryHypothesis |