content-decay-scan

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Scan content library for decay signals: declining traffic, falling rankings, outdated stats, dropped AI citations. Prioritizes refresh opportunities by business impact. Use when identifying content that needs refreshing, recovering lost traffic, or auditing for stale and underperforming content.

AI & Automation 136 stars 37 forks Updated 3 days ago MIT

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# /digital-marketing-pro:content-decay-scan ## Purpose Scan the entire content library for decay signals and prioritize refreshes by business impact. Content decay is invisible revenue loss — pages that once ranked well and drove conversions silently lose traffic as competitors publish fresher content, search algorithms evolve, statistics become outdated, and AI systems stop citing stale sources. This command detects declining organic traffic, falling keyword positions, outdated content (stale dates, broken links, deprecated information), lost AI citations, and conversion rate drops. It then ranks every piece of content by business impact — traffic multiplied by conversion rate multiplied by revenue per conversion — so you refresh the content that recovers the most revenue first, not just the content that lost the most traffic. ## Input Required The user must provide (or will be prompted for): - **Content library data**: URLs of the content to scan — can be a full sitemap, a specific content directory (e.g., /blog/*, /resources/*), or a curated list of high-value pages. For each URL, the system will pull or needs: current monthly traffic, traffic 3 and 6 months ago for trend analysis, primary keyword rankings (current and historical positions), publish date and last updated date, conversion rate if tracked (form fills, signups, purchases), and revenue attribution if available - **Analytics source**: Where to pull performance data — Google Analytics and Google Search Cons...

Details

Author
indranilbanerjee
Repository
indranilbanerjee/digital-marketing-pro
Created
4 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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