content-decay-scan

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Scan the content library for decay — declining traffic, falling keyword positions, stale content, broken links, lost AI citations — scoring each URL 0-100 via creative-fatigue-predictor.py and ranking refreshes by recoverable revenue, with actionable refresh briefs and traffic-recovery estimates for top-priority tiers. Triggers on "/digital-marketing-pro:content-decay-scan", "which content is losing traffic", "find stale content to refresh", "our blog traffic keeps dropping", "prioritize content refreshes". Pulls performance data from Google Analytics/Search Console MCPs or exported CSVs; cross-reference causes with /digital-marketing-pro:seo-drift. Reads the brand profile for content strategy context.

AI & Automation 809 stars 134 forks Updated 4 days ago MIT

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Quality Score: 95/100

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100
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License 10%
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Description 5%
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Skill Content

# /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conversions silently lose traffic as competitors publish fresher content, search algorithms evolve, statistics become outdated, and AI systems stop citing stale sources. This command detects declining organic traffic, falling keyword positions, outdated content (stale dates, broken links, deprecated information), lost AI citations, and conversion rate drops.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...

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

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