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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration with architecture components and concrete change tasks for comparison.
Architecture
SAAM (Software Architecture Analysis Method)
Paper illustration: scenarios and architectural decisions are connected to identified risks.
Architecture
ATAM (Architecture Tradeoff Analysis Method)
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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.SAAM helps teams judge an architecture’s suitability for selected tasks and changes. It is particularly useful for examining modifiability and comparing architecture alternatives with clear reasoning.ATAM helps teams weigh architecture decisions when quality goals compete. The team considers business goals, stakeholder expectations, and technical decisions together. The evaluation shows which risks need further investigation.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
HighHighHighLow
Timedifferent
1-4 WochenPreparation, scenario analysis, and findings review; effort depends on scopeSeveral meetings plus preparation and analysis; total effort depends on scope1-5 Tage
Participantsdifferent
1-6Architecture experts and stakeholders for scenarios and weightingEvaluation team, architects, and relevant stakeholdersNutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryDomain functions mapped to components and connections, Quality attributes and evaluation criteria, Typical tasks and their effects on the architecture, Reasoned evaluation or comparison of alternativesPrioritized quality scenarios in a utility tree, Architecture risks with reasoning and assumptions, Sensitivity and trade-off points, Findings report with open investigationsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ArchitectureChangeAnalysisComparisonQuality
ArchitectureQualityRiskTradeoffsStakeholders
ValidationExperimentsDemandGrowth
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