Experiment Results Interpreter

Interpret the following A/B test results and provide recommendations:

Experiment: {{experiment_name}}
Hypothesis: {{hypothesis}}
Duration: {{duration}}

Results:
{{results_data}}

Analyze systematically:

**Statistical Validity**
- Was sample size sufficient?
- Is the result statistically significant?
- What is the confidence interval?

**Practical Significance**
- Is the effect size meaningful?
- What is the business impact of this change?
- Does it justify the effort?

**Segmentation Analysis**
- Did any segments perform differently?
- Are there winners/losers within the data?
- Should we consider partial rollout?

**Confounding Factors**
- Were there external factors that could have influenced results?
- Did anything unusual happen during the test?
- Are there novelty or selection effects?

**Recommendations**
- Ship as-is
- Ship with modifications
- Iterate and re-test
- Do not ship

**Next Steps**
- Immediate actions
- Follow-up experiments to consider
- Learnings to document