ads-test

Design structured A/B tests for Meta, Google, LinkedIn, and TikTok advertising.

58|12|Updated Apr 29, 2026

Search Tags:#analytics #marketing #experimentation #advertising #ab-testing #conversion-rate

Ready to run

npx skills add https://github.com/Hainrixz/claude-ads --skill ads-test-hainrixz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ads-test
Source: https://github.com/Hainrixz/claude-ads/tree/main/skills/ads-test
Command: npx skills add https://github.com/Hainrixz/claude-ads --skill ads-test-hainrixz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill removes the guesswork from paid advertising experiments by providing a structured framework for hypothesis generation, statistical significance, and test duration planning.

Core Features & Use Cases

Hypothesis Framework: Standardizes test design to ensure single-variable isolation and clear success criteria.
Statistical Planning: Calculates required sample sizes and test durations based on baseline conversion rates and minimum detectable effects.
Platform Guides: Provides specific setup instructions for Meta, Google, LinkedIn, and TikTok advertising experiments.

Quick Start

Ask the ads-test skill to design an A/B test plan for a new creative concept on Meta with a 5 percent baseline conversion rate.

Frequently Asked Questions about ads-test

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design an A/B test for paid advertising campaigns?▼

To design an A/B test for paid advertising, you need a structured framework for hypothesis creation, single-variable isolation, and clear success criteria to ensure valid test results.

How do I calculate sample size and test duration for an ad experiment?▼

Calculate sample size and test duration for an ad experiment by inputting your baseline conversion rates and minimum detectable effects to determine exact statistical significance requirements.

Can I set up advertising experiments specifically for Meta, Google, LinkedIn, and TikTok?▼

Yes, you can set up advertising experiments for Meta, Google, LinkedIn, and TikTok by following platform-specific setup guides and success criteria definitions provided for each network.

What is the best way to structure a hypothesis for an A/B test?▼

The best way to structure a hypothesis for an A/B test is to use a standardized framework that ensures single-variable isolation and defines clear success criteria before the experiment begins.

Why does my advertising A/B test need statistical significance calculations?▼

Your advertising A/B test needs statistical significance calculations to remove guesswork, verify that performance changes are not random, and calculate the exact test duration needed based on minimum detectable effects.