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 result statistically and practically material?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results. It applies only a precommitted owner-approved action rule; the statistical helper never chooses a business action. Not for producing variants — use ad-creative-builder; not for reading back one shipped change — use paid-measurement-loop. 广告AB测试设计/实验设计/显著性判定/增效测试
Install
Quality Score: 99/100
Skill Content
Details
- Author
- aaron-he-zhu
- Repository
- aaron-he-zhu/aaron-marketing-skills
- Created
- 8 months ago
- Last Updated
- today
- Language
- Python
- License
- Apache-2.0
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
ad-test-designer
Use when the user asks to 'design an A/B test', 'set up a creative/landing test', 'run an incrementality test', or 'is this result statistically and practically material?'; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results.
ab-test-analyzer
Designs and analyzes A/B tests end-to-end — frames a sharp hypothesis, computes required sample size and test duration, runs significance tests (two-proportion z-test, Welch's t-test, chi-square), reports confidence intervals and lift, and flags common pitfalls like peeking, multiple comparisons, and Simpson's paradox. Use this skill when the user mentions A/B testing, split testing, experiment design, conversion-rate experiments, statistical significance, p-values, sample size or power calculations, "did this experiment win", minimum detectable effect (MDE), or asks to interpret experiment results honestly. Includes a runnable stats script (scripts/abtest.py).
a-b-test-designer
Designs statistically valid A/B tests: hypothesis, variants, sample size and success metric. Use when planning a conversion test or checking whether a result is significant. Not for running the experiment log - use experiment-tracker.