Design and run A/B tests for funnel pages and email sequences.
npx skills add https://github.com/jedmamosto/m-and-ms --skill ab-testing-jedmamosto
Please help me install this Agent Skill. Skill: ab-testing Source: https://github.com/jedmamosto/m-and-ms/tree/main/.agents/skills/ab-testing Command: npx skills add https://github.com/jedmamosto/m-and-ms --skill ab-testing-jedmamosto
This Skill helps you design, launch, measure, and interpret A/B tests so you can confidently decide which funnel or email variant improves outcomes without gambling on underpowered results.
Ask the AI to create an A/B test plan for your funnel headline by specifying the current and proposed headline, the primary conversion goal, the guardrail metric, and the traffic source you will split (page traffic or GHL audience).
High-intent search queries and answers about installing and using this skill.
Design an A/B test by specifying a hypothesis, split mechanism, primary and guardrail metrics, and decision rules. Ensure one-variable testing with 50/50 splitting to confidently determine which funnel or email variant improves outcomes.
Yes, you can configure page-level variant splits using Vercel Edge routing and audience-level splits using GHL workflow tags. These mechanisms enable precise 50/50 traffic allocation for your A/B test variants.
Measure A/B test variants by configuring PostHog or GA4 with correct variant attribution tracking. Enforce minimum sample size per variant, 95% confidence thresholds, and guardrail non-regression before calling a winner.
Calling an A/B test winner requires a minimum sample size per variant, 95% confidence level, and verified guardrail non-regression. This prevents gambling on underpowered results and ensures statistical significance.
Avoid A/B testing when you cannot enforce one-variable testing, 50/50 splitting, or minimum sample size requirements. Running tests without these constraints leads to premature conclusions and underpowered results.
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