For Scientists

Hypothesis

Scientific Reasoning

Formulate hypotheses, design experiments, analyze results. Apply the scientific method.

The Transformation

Before scenario
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After transformation
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See It In Action

Scenario: Do users actually prefer the new checkout flow? Let's test it.

Conclusion
Supported
Confidence:
72%
ID: checkout-flow-preference-001
Iteration: 3

Checkout abandonment rate increased from 32% to 41% after the last release. Exit surveys mention 'too many steps'. Average checkout time increased by 23 seconds, with mobile devices showing 48% abandonment.

Statement

Users who experience the new streamlined single-page checkout flow will show higher completion rates and satisfaction scores compared to the legacy multi-step checkout process.

Domain
UX/E-commerce
Alternative ToH-checkout-baseline
Variables
VariableTypeOperationalization
checkout_flow_versionindependentBinary assignment: new single-page flow vs. legacy multi-step flow
completion_ratedependentPercentage of users who complete purchase after adding to cart
satisfaction_scoredependentPost-purchase NPS score on 0-10 scale
device_typecontrolledDesktop vs. mobile, kept equal distribution across groups
user_experience_levelconfoundingNew vs. returning users - may affect results independently

Design

A/B randomized controlled trial with 50/50 traffic split between new checkout flow (treatment) and legacy checkout (control)

Methodology

Random assignment at user level with 14-day test duration. Measure completion rates, time-to-checkout, and post-purchase NPS scores. Statistical significance threshold: p < 0.05 with 95% statistical power.

Predictions
IFUsers prefer the new checkout flow
THENCompletion rates will increase by at least 5% with statistical significance
ELSENo significant difference or decrease in completion rates
IFThe new flow reduces cognitive load
THENAverage checkout time will decrease by at least 15%
IFUser satisfaction improves
THENNPS scores will increase by at least 0.5 points

Hypothesis SUPPORTED. Single-page checkout significantly reduces abandonment (12pp reduction vs. 8pp threshold). Recommend immediate full rollout to mobile users with 30-day monitoring period. The unexpected 8% cart value increase warrants further investigation as a potential secondary benefit.

  • -Roll out to 100% of mobile users immediately
  • -Monitor for 30 days post-rollout for regression
  • -Plan follow-up test: express checkout for returning users
  • -Investigate unexpected cart value increase
Scientific MethodHypothesis Supported
Complete

When to Use Hypothesis

  • 1
    Validating assumptions before building
  • 2
    A/B testing strategy and analysis
  • 3
    User behavior research
  • 4
    Proving or disproving theories
  • 5
    Data-driven decision making

Works Well With

Pro tip: Chain Hypothesis with TraceReflect for comprehensive analysis.

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