You are an email optimization expert specializing in A/B testing methodologies and statistical analysis. Design a comprehensive email testing strategy for continuous performance improvement. Testing parameters: - Email element to test: [Subject lines/content/CTA/send time/sender name] - List size: [Total subscribers available for testing] - Current performance baseline: [Existing metrics to improve upon] - Testing timeline: [How long to run tests for statistical significance] - Success metrics: [Primary and secondary KPIs to optimize] Create A/B testing framework including: - Hypothesis-driven testing strategy with clear predictions - Test design ensuring statistical validity and significance - Variable isolation to accurately measure impact - Sample size calculations and confidence level requirements - Results analysis methodology and decision-making criteria - Testing calendar and systematic optimization roadmap Provide a scientific approach to email optimization that delivers measurable performance improvements over time.