🚀 SEO Performance Analysis Tool

A comprehensive SEO analytics platform that combines performance analysis, competitor insights, and content evaluation in one powerful tool.

📋 Table of Contents

• Features
• Technologies
• Installation
• Usage
• API Configuration
• Sample Analysis
• Contributing
• License

🌟 Features

• 📊 Lighthouse Performance Analysis
  • Mobile and Desktop performance metrics
  • Accessibility scores
  • Best practices evaluation
  • SEO scoring
  • Comparative radar chart

• 🔍 Competitor Analysis
  • Automatic competitor detection
  • Content comparison
  • SEO strategy recommendations
  • Detailed comparison report

• 📝 Content Analysis
  • Structural analysis
  • SEO optimization suggestions
  • Keyword usage
  • Improvement recommendations

🛠️ Technologies

• Frontend: Streamlit
• Backend: Python
• APIs:
  • Brightdata Scraping Browser
  • Brightdata Web Unlocker
  • Brightdata SERP API
  • Google Gemini AI

Development Tools

• Python 3.12+
• Git (Version Control)
• Virtual Environment

🚀 Installation

1. Clone the repository:

git clone https://github.com/kenancn/seo-analysis-tool.git
cd seo-analysis-tool

2. Create and activate virtual environment:

python -m venv myenv
source myenv/bin/activate  # For Linux/Mac
myenv\\Scripts\\activate  # For Windows

3. Install requirements:

pip install -r requirements.txt

4. Create .env file and add your API keys:

GEMINI_API_KEY="your-gemini-api-key"
BRIGHTDATA_API_KEY="your-brightdata-api-key"
BRIGHTDATA_AUTH="your-brightdata-auth"

5. Run the application:

streamlit run app.py

💡 API Configuration

This tool requires the following API keys:

1. Google Gemini AI API

   • Sign up at Google AI Studio
   • Create an API key
   • Add to .env or Streamlit secrets

2. Brightdata API

   • Register at Brightdata
   • Set up Scraping Browser, Web Unlocker and SERP API
   • Generate API key and authentication token
   • Add to .env or Streamlit secrets

💡 How to Use?

1. Enter URL and keyword
2. Click "Start Analysis" button
3. Review the analysis results:
   • Lighthouse performance metrics
   • Content analysis report
   • Competitor analysis results
4. Download results in CSV format

🌐 Live Demo

Access the live version of the application here

📈 Sample Analysis

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create your feature branch
3. Follow our coding standards:
   • Use type hints
   • Add docstrings
   • Follow PEP 8
4. Submit a pull request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.