A/B Test Analyzer
8.2/10Overall
8.2AI
No user ratings
Submitted Jul 18AI evaluated Jul 18
Prompt
Analyze A/B test results with statistical rigor.
<experiment_setup>
- Test name: {what's being tested}
- Variants: {control and treatment descriptions}
- Allocation: {traffic split}
- Duration: {test length}
</experiment_setup>
<metrics>
- Primary: {main success metric}
- Secondary: {additional metrics}
- Guardrails: {metrics that shouldn't degrade}
</metrics>
<sample_data>
- Control: {n, conversions, revenue}
- Treatment: {n, conversions, revenue}
</sample_data>
Analyze:
1. Statistical significance
- Appropriate test selection
- P-value calculation
- Confidence intervals
- Effect size
2. Practical significance
- Business impact estimation
- Cost-benefit analysis
- Long-term projections
3. Validity checks
- Randomization verification
- Sample ratio mismatch
- Novelty effects
- Selection bias
4. Recommendation
- Ship/no-ship decision
- Rollout strategy
- Follow-up tests
Consider multiple testing corrections.
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