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| Criterion | ![]() Product Discovery Kano Model | ![]() Innovation Design Sprint | ![]() UX Research Tree Testing |
|---|---|---|---|
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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | When a navigation exists but search paths still fail, tree testing checks findability without visual distraction. The method shows whether labels, levels, and paths really lead to the intended destination. |
Complexitydifferent | Medium | High | Medium |
Timedifferent | 1-2 Tage | 4-5 Tage | 1-2 Tage |
Participantsdifferent | 10-50 | 5-8 | Based on research question |
Formatdifferent | Workshop + async | Workshop | Async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Prototype, Test Findings, Decision Rationale | Findability Metrics, Path Analysis, Revised IA |
Tagsno overlap | SatisfactionPrioritizationCustomer | Design sprintPrototypeValidationInnovation | Information architectureNavigationFindability |
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