Email A/B Testing

Helps you design and analyze statistically meaningful A/B tests for email campaigns.

Usage

Ask for help designing tests, calculating sample sizes, or interpreting results from email experiments.

Examples

• "Design an A/B test for my welcome email subject line"
• "How large should my test sample be for significant results?"
• "Analyze these open rate results and tell me the winner"

Guidelines

• Test only one variable at a time for clear results
• Ensure sample sizes are large enough for statistical significance
• Run tests for at least 24-48 hours to account for time zone differences
• Use a 95% confidence level before declaring a winner
• Document all test results to build institutional knowledge