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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Empathy Mapping
UX Research
Empathy Mapping
Paper illustration of two people facing each other, speech bubbles and an open interview notebook.
UX Research
User Interviews
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Purposedifferent
When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.When a lot is assumed about a target group but little is seen jointly, empathy mapping makes knowledge and gaps directly comparable. The picture also shows which assumptions hold up and where evidence is missing.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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.
Complexitydifferent
HighLowLowMedium
Timedifferent
1-4 Wochen30–60 min30–60 min per interview45-75 min
Participantsdifferent
1-64-81 participant per interview2-8
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop
Outputdifferent
Experiment results, Decision log, Learning summaryEmpathy Map, Assumptions List, Research GapsInterview Notes, Themes, Insight SummaryTest Matrix, Test Plan
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
SynthesisQualitativeWorkshop
QualitativeResearchCustomerDiscovery
ExperimentsValidationDiscoveryOptions
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