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:

# 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

pip install -r data_sources/requirements.txt

3. Test Data Connections

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

1. Declining Content: Article lost 35% traffic

   /analyze-existing /blog/podcast-equipment-guide
   /rewrite podcast equipment guide