google-analytics
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
npx skills add majiayu000/claude-skill-registry --skill google-analytics-jfespanolito-jfespanolito-dev --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Google Analytics Analysis Analyze website performance using Google Analytics data to provide actionable insights and improvement recommendations. ## Quick Start ### 1. Setup Authentication This Skill requires Google Analytics API credentials. Set up environment variables: ```bash export GOOGLE_ANALYTICS_PROPERTY_ID="your-property-id" export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json" ``` Or create a `.env` file in your project root: ```env GOOGLE_ANALYTICS_PROPERTY_ID=123456789 GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json ``` **Never commit credentials to version control.** The service account JSON file should be stored securely outside your repository. ### 2. Install Required Packages ```bash # Option 1: Install from requirements file (recommended) pip install -r cli-tool/components/skills/analytics/google-analytics/requirements.txt # Option 2: Install individually pip install google-analytics-data python-dotenv pandas ``` ### 3. Analyze Your Project Once configured, I can: - Review current traffic and user behavior metrics - Identify top-performing and underperforming pages - Analyze traffic sources and conversion funnels - Compare per
- Quick Start
- 1. Setup Authentication
- 2. Install Required Packages
- 3. Analyze Your Project
- How to Use
- Analysis Workflow
- Common Metrics
- Traffic Metrics
- Engagement Metrics
- Acquisition Metrics
- Conversion Metrics
- Analysis Examples
- Scripts
- Fetch Current Performance
export GOOGLE_ANALYTICS_PROPERTY_ID="your-property-id" export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json" Option 1: Install from requirements file (recommended) pip install -r cli-tool/components/skills/analytics/google-analytics/requirements.txt Option 2: Install individually pip install google-analytics-data python-dotenv pandas python scripts/ga_client.py --days 30 --metrics sessions,users,bounceRate python scripts/analyze.py --period last-30-days --compare previous-period
What does the google-analytics skill do?
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill google-analytics-jfespanolito-jfespanolito-dev --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.