ads-test

仓库创建 2026年7月6日最近提交 21 天前SkillHot 收录 20 天前

▸ 精选理由

把统计计算与平台设置结合，降低实验设计错误概率。

这个 Skill 做什么

为广告实验提供假设构建、样本量计算与平台专项设定指南。

为付费广告做 A/B 测试设计：把假设结构化、算出样本量与测试时长，并给出 Meta、Google、LinkedIn 等平台的设置建议。用在要验证创意、受众、出价或着陆页效果时，一步到位把统计和平台操作细节算清楚。

▸ 展开 SKILL.md 英文原文

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.

研究检索A/B 测试样本量计算统计显著性通用

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帮我安装这个 skill：https://raw.githubusercontent.com/incuca/incuca-ads/main/skills/ads-test/SKILL.md

或 curl 直取 SKILL.md

curl -fsSL "https://raw.githubusercontent.com/incuca/incuca-ads/main/skills/ads-test/SKILL.md"

SKILL.MD 节选查看完整文件 ↗

# A/B Test Design & Experiment Planning

<!-- Created: 2026-04-13 | v1.5 -->
<!-- Source: OpenClaudia/openclaudia-skills (ab-test-setup concept) -->

## Process

1. Understand what the user wants to test (creative, audience, bidding, landing page)
2. Build structured hypothesis using the framework below
3. Calculate required sample size and estimated duration
4. Recommend platform-specific test setup
5. Define success criteria and measurement plan

## Hypothesis Framework

Every test must start with a structured hypothesis:

```
IF we [change/action]
THEN [metric] will [increase/decrease] by [estimated %]
BECAUSE [reasoning based on data or insight]

Example:
IF we replace polished product s

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