How to use A/B Test Setup in your AI agent

What you'll get

This skill helps you design and run A/B tests (comparing two versions to see which performs better) for websites, emails, ads, or any digital experience. It guides you through forming a hypothesis, calculating how much traffic you need, choosing what to measure, and analyzing results with statistical rigor. You get a structured experimentation process that produces reliable, actionable insights—no guesswork.

Step 1 — Get the skill source URL

The A/B Test Setup skill lives at:

Step 2 — Add it to your AI agent

Copy one of these prompts and paste it into your AI tool. The agent will fetch and install the skill for you.

Add the agent skill from https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup to my project.

Install this agent skill: https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup

Add this skill to .codex/skills/: https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup

Add the skill at https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup to my .gemini/skills/ directory.

Install this agent skill from https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup

Add this skill: https://github.com/coreyhaines31/marketingskills/tree/main/skills/ab-test-setup

Step 3 — Try these prompts

Once the skill is installed, ask your AI things like:

• Launching a new landing page and want to know which headline converts better
• Tweaking email copy or button text and need to measure impact objectively
• Build a growth experimentation program and run tests continuously
• Comparing two design approaches and need statistical confidence before choosing

What this skill does

• Helps you write a clear hypothesis for what you're testing and why
• Calculates how much traffic and time you need for statistically valid results
• Guides you in choosing primary, secondary, and guardrail metrics to track
• Explains how to design test variants that isolate a single meaningful change
• Analyzes results and tells you whether the difference is real or just noise