Performance Review Command Use this command to analyze content performance data and generate a prioritized queue of content tasks. ## Usage /performance-review [days] ## What This Command Does 1. Fetches data from Google Analytics, Google Search Console, and DataForSEO 2. Analyzes performance trends and opportunities 3. Identifies quick wins, declining content, and growth opportunities 4. Scores and prioritizes all opportunities by ROI 5. Creates actionable task queue with specific next steps 6. Generates comprehensive performance report ## Process ### Data Collection - Google Analytics 4: Traffic, engagement, conversions, and trends - Google Search Console: Rankings, impressions, clicks, CTR by page and keyword - DataForSEO: Competitive rankings, SERP features, keyword metrics ### Opportunity Identification The Performance Agent automatically identifies: Quick Wins (Highest Priority): - Keywords ranking positions 11-20 (page 2) - Closest to page 1 with smallest optimization effort - Calculated opportunity score based on impressions and position Declining Content: - Pages losing traffic month-over-month - Identifies severity and potential causes - Prioritizes by traffic volume at risk Low CTR Opportunities: - Pages with high impressions but low click-through rates - Meta title/description improvements needed - Calculates potential click gains Trending Topics: - Queries showing rising search volume - Early mover advantage opportunities - Content gaps in growing areas Competitor Gaps: - Keywords competitors rank for but your company doesn't - Strategic positioning opportunities - Estimated traffic potential ### Scoring & Prioritization Each opportunity receives a score (0-100) based on: - Impact (50%): Potential traffic gain, conversion value, strategic importance - Effort (30%): Time required, difficulty, resources needed - Confidence (20%): Data quality, historical success rate, trend stability ### Report Generation Creates comprehensive report with: - Executive summary of performance - Priority queue (urgent/high/medium) - Detailed opportunity analysis - Content health dashboard - Keyword portfolio status - Resource allocation recommendations - Week-by-week implementation roadmap ## Prerequisites ### 1. Configure Data Sources Before first use, set up API credentials in data_sources/config/.env: ``bash # Copy example config cp data_sources/config/.env.example data_sources/config/.env # Edit with your credentials nano data_sources/config/.env ` Required credentials: - Google Analytics 4 property ID and service account JSON - Google Search Console site URL and credentials - DataForSEO API login and password See data_sources/README.md for detailed setup instructions. ### 2. Install Python Dependencies `bash pip install -r data_sources/requirements.txt ` ### 3. Test Data Connections `bash python data_sources/modules/google_analytics.py python data_sources/modules/google_search_console.py python data_sources/modules/dataforseo.py ` ## Output Provides a multi-section performance report: ### 1. Executive Summary ` Report Date: 2025-10-15 Analysis Period: Last 30 days Overall Performance: - Total Pageviews: 125,400 - Total Clicks (GSC): 45,200 - Average Position: 12.3 - Total Keywords Ranking: 3,847 Key Trends: - Organic traffic up 8% vs. previous period - 7 articles showing significant decline - 23 keywords moved to page 2 (quick win opportunities) ` ### 2. Priority Queue ` 🔥 URGENT (Do This Week) 1. Optimize for "podcast analytics dashboard" Type: Quick Win Current Position: 12 Monthly Impressions: 5,400 Potential Impact: Move to position 7, gain +450 clicks/month Estimated Effort: 3 hours Action: Update content, improve internal linking, refresh meta Opportunity Score: 87/100 ` ### 3. Detailed Analysis - Quick Win Opportunities table - Declining Content analysis - Low CTR pages with meta recommendations - Trending topics to target - Competitor gap analysis ### 4. Implementation Roadmap Week-by-week task breakdown with specific actions ### 5. Success Metrics Goals and measurement criteria for next review period ## File Management After generating the report, automatically saves to: - **File Location**: research/performance-review-[YYYY-MM-DD].md - **File Format**: Markdown with tables, metrics, and action items - **Naming Convention**: performance-review- + ISO date Example: research/performance-review-2025-10-15.md ## Integration with Other Commands The Performance Agent output directly informs other commands: **From Performance Review → Next Actions**: 1. **Quick Win Identified**: "podcast monetization" at position 13 ` /analyze-existing /blog/podcast-monetization-guide /optimize drafts/podcast-monetization-guide.md ` 2. **Declining Content**: Article lost 35% traffic `` /analyze-existing /blog/podcast-equipment-guide /rewrite podcast equipment guide