ad-test-designer
FeaturedUse when the user asks to "design an A/B test", "set up a creative/landing test", "run an incrementality test", or "is this test significant — promote or kill?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, a documented significance read, and a promote/kill decision on your own exported results. Not for producing the variants — use ad-creative-builder; not for reading back one shipped change vs a control — use paid-measurement-loop; not for cross-channel reporting — use performance-analyzer. 广告AB测试设计/实验设计/显著性判定/增效测试
Install
Quality Score: 98/100
Skill Content
Details
- Author
- aaron-he-zhu
- Repository
- aaron-he-zhu/aaron-marketing-skills
- Created
- 6 months ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Bundled in these plugins
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ads-test
A/B test design and experiment planning for paid advertising. Structured hypothesis framework, statistical significance calculator, test duration estimator, sample size calculator, and platform-specific experiment setup guides (Meta Experiments, Google Experiments, LinkedIn A/B). Use when user says A/B test, split test, experiment design, test hypothesis, statistical significance, sample size, or test duration.
experiment-designer
Design statistically rigorous A/B tests and interpret experiment results. Use when asked to design an experiment, run an A/B test, calculate sample size, interpret test results, or assess whether an experiment was successful. Produces a complete experiment design with hypothesis, sample size, run time, success criteria, and risk flags — or a results interpretation with ship/iterate/kill recommendation.