Hypothesis
Scientific Reasoning
Formulate hypotheses, design experiments, analyze results. Apply the scientific method.
The Transformation
Before scenario
(Coming soon)
After transformation
(Coming soon)
See It In Action
Scenario: “Do users actually prefer the new checkout flow? Let's test it.”
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.
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.
A/B randomized controlled trial with 50/50 traffic split between new checkout flow (treatment) and legacy checkout (control)
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.
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
When to Use Hypothesis
- 1Validating assumptions before building
- 2A/B testing strategy and analysis
- 3User behavior research
- 4Proving or disproving theories
- 5Data-driven decision making
Works Well With
Pro tip: Chain Hypothesis with Trace → Reflect for comprehensive analysis.
Ready to use Hypothesis?
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npx @anthropic-ai/claude-code mcp add think-mcp