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Top Traffic Pages Finder

Use cases

Identifying your most valuable organic content Reporting on content performance Finding pages to protect during migrations Understanding which content types drive traffic

Jupyter notebook that connects to the Google Search Console API via OAuth to rank pages by organic traffic.

Aggregates clicks, impressions, CTR, and average position at the page level.

Automatically categorises pages into traffic ranges (0, 1-100, 101-1000, 1001-5000, 5001-10000, 10001+) and identifies zero-traffic pages for review.

Exports a four-sheet Excel workbook with Plotly visualisations.

Jupyter Notebook GSC Data

Platform

Jupyter Notebook (requires Python environment)

Input

Google OAuth credentials

GSC property and date range

Output

Excel with top pages and traffic analysis

View Source

Features

  • OAuth authentication via google-searchconsole library
  • Traffic range categorisation (0, 1-100, 101-1K, 1K-5K, 5K-10K, 10K+)
  • Zero-traffic page isolation for review
  • Keyword-to-page relationship mapping
  • Four-sheet Excel export with xlsxwriter
  • Plotly interactive traffic distribution charts

How to use

  1. 1 Set up OAuth credentials and authenticate
  2. 2 Enter your GSC property URL and country code
  3. 3 Select date range and search type
  4. 4 Run to aggregate page-level metrics
  5. 5 Review traffic distribution and zero-traffic pages
  6. 6 Download Excel workbook with four analysis sheets

Want me to run this for you?

I offer this as a managed service. You get the insights without touching the tool.

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