Google Search Console Data Analysis

This tool analyzes Google Search Console data across multiple domains to provide insights, summary statistics, and visualizations, helping you understand your website's search performance.

Features

• Analyzes multiple domains from Google Search Console data.
• Provides time series analysis of clicks and impressions.
• Analyzes traffic by country, device, pages, and search queries.
• Generates detailed statistical analysis including percentiles and outlier detection.
• Creates beautiful HTML reports with Tailwind CSS styling.

Data Structure

The tool expects the data to be organized in the following structure within the data/ directory:

• data/
  • domain1-com-Performance-on-Search-YYYY-MM-DD/
    • Countries.csv
    • Dates.csv
    • Devices.csv
    • Filters.csv (If applicable/available)
    • Pages.csv
    • Search appearance.csv (If applicable/available)
    • Queries.csv
  • domain2-net-Performance-on-Search-YYYY-MM-DD/
    • Countries.csv
    • Dates.csv
    • Devices.csv
    • Filters.csv (If applicable/available)
    • Pages.csv
    • Search appearance.csv (If applicable/available)
    • Queries.csv
  • ... (and so on for each domain)

Explanation:

1. data/ directory: All Google Search Console data should be placed within this directory.
2. Domain Folders: Each domain's data should be in its own separate folder. The folder name should follow the pattern: domain-name.com-Performance-on-Search-YYYY-MM-DD. Replace domain-name.com with the actual domain (e.g., example-com) and YYYY-MM-DD with the date of the data export. Use hyphens instead of periods in the domain name portion.
3. CSV Files: Within each domain folder, place the CSV files exported from Google Search Console. Ensure they are named exactly as listed above (case-sensitive). Filters.csv and Search appearance.csv are optional and the script should handle their absence gracefully.

Installation

1. Clone the repository:

   git clone https://github.com/matija2209/search-console-analyser  # Replace <repository_url> with the actual URL
   cd search-console-analyser     # Replace <repository_name> with the cloned directory name

2. Create a virtual environment:

   python3 -m venv venv

3. Activate the virtual environment:

   • macOS/Linux:

     source venv/bin/activate

   • Windows:

     venv\Scripts\activate

4. Install dependencies:

   pip install -r requirements.txt

Usage

1. Place Data: Place your exported Google Search Console data in the data/ directory, following the structure described above.

2. Run Analysis: Execute the main analysis script:

   python main.py

3. View Report: The generated HTML report will be saved in the reports/ directory. Open the HTML file in your web browser to view the analysis and visualizations.

Output

The tool provides the following outputs:

• Console Output: Summary statistics and progress information are printed to the console during script execution.
• HTML Report: A detailed HTML report is generated in the reports/ directory, containing:
  • Aggregated statistics across all domains.
  • Domain-specific analysis, including time series charts, tables, and outlier detection.
  • Visualizations for clicks, impressions, country, device, page, and query data.

Requirements

• Python 3.8+
• pandas
• matplotlib
• numpy
• (Other dependencies listed in requirements.txt)

License

This project is licensed under the MIT License

One-liner to create a new repository and push the code to it:

git init
git add .
git commit -m "Initial commit"
git branch -M main
gh repo create search-console-analyser --public --source=. --remote=origin
git push -u origin main