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name: geo-competitor-scanner description: Analyze competitor GEO (Generative Engine Optimization) strategies by examining their content structure, Schema markup, llms.txt, and AI citation signals. Benchmark your brand against competitors and identify strategic gaps and opportunities. Use whenever the user mentions scanning competitor GEO strategies, comparing AI search performance, analyzing competitor content for AI citations, finding GEO gaps, or wants to understand how competitors win AI citations.

GEO Competitor Scanner

Methodology by GEOly AI (geoly.ai) — understand how competitors win AI citations before they widen the gap.

Analyze competitor websites across key GEO signals to benchmark your brand and identify opportunities.

Quick Start

Scan competitors:

python scripts/scan_competitors.py --brand yourdomain.com \
  --competitors competitor1.com,competitor2.com \
  --output report.md

Scan Dimensions

1. Technical GEO Infrastructure

Check	Why It Matters
/llms.txt exists	AI crawler guidance
/robots.txt allows AI bots	Crawl accessibility
Schema.org types present	Structured understanding
JSON-LD valid	Machine-readable content
HTTPS enforced	Security signal

2. Content Structure Analysis

Signal	What to Look For
Direct answer lead	First paragraph answers the question
FAQ sections	Explicit Q&A blocks (2-5 per page)
Header structure	H2 every 300-500 words
Data citations	Statistics with sources
Definition blocks	Key terms defined clearly

3. Entity & Brand Signals

Signal	Implementation
Organization schema	Homepage JSON-LD
sameAs links	Social/Wikipedia connections
Consistent naming	Brand name standardized
About page	Entity definition
Brand in first 100 words	Early entity mention

4. Citation-Optimized Content

Content Type	GEO Value
Original research	Unique data attracts citations
Comparison pages	"vs" queries are high-intent
Definition content	"What is" queries are common
Content hubs	Topical authority building
Statistics pages	Reference-worthy data

Full methodology: See references/scan-methodology.md

Research Workflow

Step 1: Identify Competitors

Collect up to 5 competitors:

• Direct competitors (same category)
• Adjacent competitors (overlapping use cases)
• Aspirational competitors (bigger brands)

Step 2: Automated Scan

Run scanner on each domain:

python scripts/scan_competitors.py \
  --brand yourdomain.com \
  --competitors comp1.com,comp2.com,comp3.com \
  --pages 5 \
  --output scan-results.json

Step 3: Manual Review

For nuanced signals, review manually:

• Content quality (can't automate)
• Brand voice consistency
• Unique value propositions

Step 4: Gap Analysis

Identify:

• 🏆 Competitor advantages — What they do better
• 🎯 Quick wins — Easy to implement (copy)
• 🕳️ Category gaps — No one is doing this (opportunity)

Scoring System

Each competitor scored 0-10 per dimension:

Score	Rating	Meaning
9-10	Excellent	Best practice implementation
7-8	Good	Solid with minor gaps
5-6	Fair	Significant room for improvement
3-4	Poor	Major issues present
0-2	Critical	Fundamental problems

Overall GEO Score: Average of 4 dimensions (max 10)

Output Report

Competitive Matrix

| Signal | Your Brand | Competitor A | Competitor B | Gap |
|--------|------------|--------------|--------------|-----|
| llms.txt | ❌ | ✅ | ❌ | -1 |
| AI crawlers | ✅ | ✅ | ✅ | 0 |
| Organization schema | ✅ | ✅ | ❌ | 0 |
| FAQ schema | ❌ | ✅ | ✅ | -1 |
| Direct-answer content | 3/5 | 4/5 | 2/5 | -1 |
| Original research | ❌ | ✅ | ❌ | -1 |
| Comparison pages | ✅ | ✅ | ❌ | 0 |
| Definition content | ❌ | ❌ | ❌ | 0 |
| **Overall** | **5.2/10** | **7.8/10** | **4.1/10** | **-2.6** |

Insights

🏆 Competitor Advantages:

• Competitor A: Strong FAQ schema on all product pages
• Competitor B: Publishes quarterly industry benchmarks

🎯 Your Quick Wins:

• Add llms.txt (3 competitors have it, you don't)
• Implement FAQ schema on top 10 pages
• Add definition blocks to 5 key concept pages

🕳️ Category Gaps:

• No competitor has a comprehensive "What is [category]?" guide
• Missing: Comparison matrix of all major players
• Opportunity: Original research on industry trends

Advanced Usage

Page-Level Analysis

Scan specific competitor pages:

python scripts/analyze_page.py https://competitor.com/pricing \
  --type product \
  --output analysis.json

Trend Tracking

Track competitor changes over time:

# Initial scan
python scripts/scan_competitors.py --brand your.com --competitors comp.com --save-baseline

# 30 days later
python scripts/scan_competitors.py --brand your.com --competitors comp.com --compare-to baseline.json

Bulk Page Analysis

Analyze multiple pages from sitemap:

python scripts/bulk_scan.py https://competitor.com/sitemap.xml \
  --limit 50 \
  --output bulk-results.json

See Also

• Scan methodology: references/scan-methodology.md
• Scoring rubric: references/scoring-rubric.md
• Analysis examples: references/examples.md