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:

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