geo-competitor-scanner

# 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: ```bash 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](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: ```bash 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 ```markdown | 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: ```bash python scripts/analyze_page.py https://competitor.com/pricing \ --type product \ --output analysis.json ``` ### Trend Tracking Track competitor changes over time: ```bash # 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: ```bash python scripts/bulk_scan.py https://competitor.com/sitemap.xml \ --limit 50 \ --output bulk-results.json ``` ## See Also - Scan methodology: [references/scan-methodology.md](references/scan-methodology.md) - Scoring rubric: [references/scoring-rubric.md](references/scoring-rubric.md) - Analysis examples: [references/examples.md](references/examples.md)