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| Criterion |  Product Discovery Kano Model |  UX Research User Interviews |  Operations ALPEN Method |  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. | With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time. | 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 | 10-20 min daily | 60-90 min |
Participantsdifferent | 10-50 | 1 participant per interview | 1 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Interview Notes, Themes, Insight Summary | Daily Plan, Time Estimates, Review Notes | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | SatisfactionPrioritizationCustomer | QualitativeResearchCustomerDiscovery | PlanningTime managementProductivityOperations | ExperimentsPrioritizationDiscoveryHypothesis |