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Content Decay Analyser

Use cases

Identifying content that needs refreshing Prioritising content updates by impact Tracking content performance over time Finding pages affected by algorithm updates

Identifies months with sufficient data coverage by comparing actual vs expected days.

Groups clicks by page and month.

Peak = maximum clicks across analysed months.

Clicks Lost = latest month - peak month (negative = decay).

OpenPyXL Excel with conditional formatting, hyperlinked URLs, customisable peak highlight colour.

Streamlit App

Platform

Browser-based (no installation required)

Input

GSC export CSV with dates

UTF-8 or Latin-1 encoding supported

Output

Excel: styled workbook with hyperlinked URLs, peak month highlighted, clicks lost calculated. Info sheet included. CSV export option.

Launch App View Source

Features

  • Complete month detection (actual vs expected days)
  • Peak month calculation per page
  • Clicks lost: latest - peak (negative = decay)
  • Months to analyse slider (3-24, default 12)
  • Minimum peak clicks threshold (0-10,000)
  • OpenPyXL Excel with hyperlinks and conditional formatting

How to use

  1. 1 Export GSC data as CSV
  2. 2 Upload to the tool
  3. 3 Set months to analyse (3-24)
  4. 4 Set minimum peak clicks threshold
  5. 5 Choose peak highlight colour
  6. 6 Download styled Excel or CSV

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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