ab-test-calculator
Calculate statistical significance for A/B tests. Sample size estimation, power analysis, and conversion rate comparisons with confidence intervals.
design-of-experiments
Use when optimizing multi-factor systems with limited experimental budget, screening many variables to find the vital few, discovering interactions between parameters, mapping response surfaces for peak performance, validating robustness to noise factors, or when users mention factorial designs, A/B/n testing, parameter tuning, process optimization, or experimental efficiency.
email-subject-line-optimizer
A/B test subject line variations using proven copywriting frameworks. Predict open rates based on historical performance.
cold-email-sequence-generator
Generate personalized cold email sequences (7-14 emails) with A/B test subject lines, follow-up timing recommendations, and integrated social proof. Creates multi-touch campaigns optimized for response rates. Use when users need outbound email campaigns, sales sequences, or lead generation emails.
app-analytics-strategist
Expert digital data analytics consultant for designing and implementing data-driven growth strategies for mobile and digital applications. Use this skill when users need help with app analytics strategy, metrics selection, analytics framework implementation, cohort analysis, user segmentation, A/B testing, customer journey mapping, retention optimization, or choosing analytics tools. Applies to product managers, growth teams, and developers building data-driven applications across all platforms and industries seeking to optimize user engagement, retention, and revenue through analytics.
Statistical Hypothesis Testing
Conduct statistical tests including t-tests, chi-square, ANOVA, and p-value analysis for statistical significance, hypothesis validation, and A/B testing
A/B Test Analysis
Design and analyze A/B tests, calculate statistical significance, and determine sample sizes for conversion optimization and experiment validation