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| Criterion |  UX Research User Interviews |  Product Discovery Opportunity Solution Tree |  Operations ALPEN Method |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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 discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Low | Medium | Low | Low |
Timedifferent | 30–60 min per interview | 1-2 h Setup, laufend | 10-20 min daily | 30-60 min |
Participantsdifferent | 1 participant per interview | 2-6 | 1 | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Interview Notes, Themes, Insight Summary | Opportunity Solution Tree, Experiment Backlog, Learning Log | Daily Plan, Time Estimates, Review Notes | Completed Experiment Canvas, Success Metric |
Tagsno overlap | QualitativeResearchCustomerDiscovery | DiscoveryOutcomesExperimentsOpportunity | PlanningTime managementProductivityOperations | ExperimentsValidationDiscoveryHypothesis |