Paid advertising can be expensive without proper testing. This skill helps you design and plan A/B tests for your ad campaigns. You get a clear hypothesis framework to structure your experiments.
It includes a statistical significance calculator and a test duration estimator. You can find the right sample size for your baseline conversion rate and desired effect. The skill also provides setup guides for Meta Experiments, Google Experiments, and LinkedIn A/B tests.
Marketers and analysts can run smarter tests with confidence. This saves time and money by avoiding poorly designed experiments.
Global
mkdir -p ~/.claude/skills/ads-testProject
mkdir -p .claude/skills/ads-testSource Repository
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