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Selected:A/B TestingHEART Framework
Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of HEART Framework with its method-specific working model.
UX Research
HEART Framework
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.Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard.
Complexitydifferent
HighMedium
Timedifferent
1-4 Wochen120 min initial, dann laufend
Participantsdifferent
1-63-6
Formatdifferent
AsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryHEART-GSM Table, Dashboard
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
MetricsUX researchMeasurementSatisfaction
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration of Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
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A paper-based illustration representing Pirate Metrics (AARRR) with its core stages and visible working result.
Growth
Pirate Metrics AARRR
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Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
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