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ads-testing

Generate prioritized A/B test plans and 90-day calendars for Meta, Google, and LinkedIn ads.

Updated Apr 19, 2026
Search Tags:#calendar#hypotheses#ab-testing#ads#sample-size#campaign-planning
One-click install
npx skills add https://github.com/tapanshah/ai-ads-claude --skill ads-testing-tapanshah
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ads-testing
Source: https://github.com/tapanshah/ai-ads-claude/tree/main/skills/ads-testing
Command: npx skills add https://github.com/tapanshah/ai-ads-claude --skill ads-testing-tapanshah

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the design and scheduling of structured A/B tests across Meta, Google, and LinkedIn to optimize ad performance, reducing manual planning and accelerating insights.

Core Features & Use Cases

  • Prioritized test matrix based on impact and effort for ad campaigns.
  • 90-day testing calendar with weekly phases and KPI targets.
  • Platform-specific testing guidance for Meta, Google, and LinkedIn, including winner criteria and duration rules.
  • Output-ready ADS-TESTING-PLAN.md documents and templates for hypotheses, sample sizes, and testing trackers.

Quick Start

Describe your campaign goals and traffic, then invoke the skill to generate ADS-TESTING-PLAN.md.

Frequently Asked Questions about ads-testing

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

FAQPage Schema
How do I plan structured A/B tests for ad campaigns across Meta, Google, and LinkedIn?▼

Structured ad A/B testing requires a prioritized matrix based on impact and effort, platform-specific winner criteria, and a 90-day calendar. This generates an ADS-TESTING-PLAN.md document with hypotheses, sample size calculations, and testing trackers.

What is the best way to calculate sample size and test duration for digital ads?▼

The best way to calculate ad test sample size and duration is using a structured testing plan that factors campaign traffic and budget. It applies platform-specific duration rules to output accurate sample size templates and timing schedules.

Can I use a single A/B testing framework for different ad platforms like Meta and Google?▼

Yes, a unified A/B testing framework supports Meta, Google, and LinkedIn. It delivers platform-specific testing guidance, including distinct winner criteria and duration rules tailored to each ad platform's environment.

How do I generate a 90-day testing calendar for my marketing campaigns?▼

Generating a 90-day ad testing calendar involves inputting campaign goals and traffic parameters. The process outputs a weekly phase schedule with KPI targets, prioritized hypotheses, and sample size trackers in a production-ready markdown document.

Do I need prior testing hypotheses before starting A/B testing on ad campaigns?▼

You do not need pre-formed hypotheses. The ad A/B testing workflow provides templates to formulate structured hypotheses and prioritizes them based on potential impact and required effort before generating the test schedule.

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