Research Performance Command Categorize all content by traffic and rankings to prioritize optimization. ## Usage /research-performance ## What This Command Does Analyzes ALL your blog content and categorizes into 4 performance quadrants: 1. ⭐ Stars - High traffic + Good rankings → Maintain & expand 2. 🚀 Overperformers - High traffic + Poor rankings → Learn why, improve SEO 3. ⚠️ Underperformers - Low traffic + Good rankings → Fix CTR (title/meta) 4. 📉 Declining - Low traffic + Poor rankings → Refresh or redirect For each piece: - Traffic trends (rising/stable/declining) - Expected vs actual traffic - Specific action recommendations - Priority level ## Process Execute the performance matrix analysis: ``bash python3 research_performance_matrix.py ` This will: 1. Fetch all pages from GA4 (last 90 days) 2. Filter to content pages only 3. Enrich with GSC ranking data 4. Calculate traffic trends (180-day comparison) 5. Categorize into performance quadrants 6. Generate report: research/performance-matrix-YYYY-MM-DD.md ## Output The report includes: - Distribution across 4 quadrants - Top performers in each category - Specific action steps per article - Expected traffic calculations - Priority recommendations ## Key Insights **Stars**: Your best content - keep fresh, expand with clusters **Underperformers**: QUICK WINS - rewrite titles/meta for better CTR **Declining**: Content losing traction - needs refresh or redirect **Overperformers**: Getting traffic despite poor rankings - improve SEO ## Integration After running /research-performance: - Use /analyze-existing [URL]` for detailed content analysis - Fix underperformer titles/meta first (low effort, high impact) - Refresh declining stars to prevent traffic loss ## Time & Requirements Time: 2-4 minutes Requirements: GA4 required, GSC recommended Cost: Free ## When to Run - Monthly: Monitor content health - After major updates: Track impact - When traffic drops: Identify declining content