SEO to GEO: Why AI Visibility Requires More Than Technical Implementation

Radarly by Contently reported my brand appeared in 0% of AI responses. Dead last among competitors.

The same day, Cloudflare recorded 273 AI crawler requests to my site. That’s 28% of all crawler traffic. My technical setup works.

The paradox reveals the real GEO problem: AI crawlers visit my content, but AI systems don’t recommend my brand.

Technical implementation isn’t enough.

The Crawler-Recommendation Gap

My technical foundation works: markdown endpoints, HTTP headers, content negotiation. Cloudflare confirms 94.1% success rate for AI crawler requests.

But being crawlable doesn’t make you recommendable.

Here’s my 24-hour Cloudflare data:

273 AI requests (28% of crawler traffic)
94.1% success rate
ChatGPT-User: 219 requests
Most crawled: /posts/micro-models (56 requests)

AI crawlers find and access my content successfully. Yet when users ask for personal development recommendations, my brand never appears.

The Data Access Reality

Cloudflare provides real-time AI crawler data. Free shows 24 hours. Paid adds historical analysis, referrer data, and exports.

The advantage: ground truth data about actual AI crawler behavior on your content, not third-party estimates.

Even 24-hour data reveals which AI providers visit your site, which pages they prefer, and success rates. More valuable than vague opportunity scores.

The gap isn’t technical. It’s strategic.

How AI Recommends Brands

AI systems don’t recommend brands like search engines rank pages.

Search Engine Logic: Crawl → Index → Rank by links/keywords → Display results

AI Recommendation Logic: Train → Understand entities → Recommend by authority + context → Synthesize answers

SEO optimizes for search. GEO optimizes for AI.

AI needs three things to recommend your brand:

Entity Recognition: AI identifies you as distinct
Authority Signals: Your brand appears in authoritative contexts
Contextual Relevance: Your content matches user intent

My technical setup nails #1. AI crawlers recognize my content and brand. But #2 and #3 are missing.

The Three-Layer GEO Strategy

Layer 1 is foundation. Layers 2 and 3 make AI recommend you.

Layer 1: Crawler Intelligence (Cloudflare)

Monitor AI crawler activity to confirm technical implementation works.

Track:

AI crawler traffic (target: >25%)
Success rate (target: >95%)
Page-level preferences
Status code health

Cloudflare provides facts about AI interest in your content. No estimation.

Layer 2: Mention Intelligence (CLI Tools)

Track if crawler visits translate to brand recommendations.

Tools:

Gego (Go, comprehensive):

go install github.com/AI2HU/gego/cmd/gego@latest
gego init && gego llm add && gego prompt add && gego run && gego stats keywords

AICW (Node.js, simple):

npx @aichatwatch/aicw ai-visibility yourdomain.com

These measure actual AI recommendations, not just crawler visits.

Why combine tools:

Cloudflare: 24-hour window
CLI tools: Historical tracking, competitive analysis
Combined: Complete picture of visits AND recommendations

Layer 3: Prompt Intelligence (Custom Testing)

Bridge the gap. Test which queries lead AI to mention your brand.

Critical prompt patterns:

‘What companies focus on [industry]?’
‘Who are leading providers of [service]?’
‘Which platforms offer [value proposition]?’
‘What are common tools for [solution]?’

Test systematically across AI models. Document which prompts trigger mentions.

Implementation Roadmap

Step 1: Establish Baseline

Document current state:

Capture Cloudflare metrics: 24h AI crawler activity
Run AICW: npx @aichatwatch/aicw ai-visibility yourdomain.com
Install Gego: go install github.com/AI2HU/gego/cmd/gego@latest

Step 2: Correlate Data

Find gaps:

Cross-reference: Cloudflare top pages vs AICW mentions
Identify disconnects: High visits, low mentions
Test prompts: Use Simonw LLM for query testing

My /posts/micro-models gets 56 AI crawler visits. Do those become brand mentions? AICW answers this.

Step 3: Optimize

Fix what you find:

Technical fixes: Address crawler errors
Content optimization: Improve pages getting attention
Strategic alignment: Match content to mention-generating prompts

Step 4: Measure Progress

Track all three layers:

Technical (Cloudflare):

AI crawler traffic percentage
Success rate improvement
Content preference changes

Mentions (CLI Tools):

Brand mention frequency
Share of voice vs competitors
Position in AI recommendations

Correlation:

Crawler-to-mention conversion rate
Content performance gaps

Why Third-Party Tools Fall Short

Radarly by Contently gave vague opportunity scores and ‘high opportunity prompts’ but never showed real data about my domain.

Cloudflare provides ground truth: actual AI crawler behavior on your content, not industry estimates.

Ground truth vs estimation:

Cloudflare: 273 requests, 94.1% success rate, ChatGPT-User dominance
Third-party: ‘0% visibility score’ with vague methodology

Ground truth wins. Every time.

The GEO Mindset Shift

SEO thinks about rankings. GEO thinks about recommendations.

SEO questions:

What keywords do I rank for?
How do I get to position #1?
How much traffic do I get?

GEO questions:

Does AI recommend my brand at all?
Which prompts trigger my mentions?
How does AI describe my brand to users?

The shift: from being found to being recommended.

Your First GEO Actions

Do these today:

Check Cloudflare: Document 24h crawler metrics
Run AICW: npx @aichatwatch/aicw ai-visibility yourdomain.com
Test one prompt: Use Simonw LLM for key industry query
Install Gego: Set up ongoing mention tracking

This gives your baseline. Everything else builds here.

Common AI Visibility Issues

My technical foundation was solid, but structural issues prevented optimal AI visibility.

Sitemap.xml Structure

Problem: Missing urlset or sitemapindex tags cause AI crawlers to reject sitemaps.

Solution: Create /sitemap.xml redirect to /sitemap-index.xml. Ensure sitemaps are in static routes. AI crawlers need well-formed XML to discover content.

JSON-LD Structured Data

Problem: Invalid JSON-LD blocks (unparseable @graph structures) make structured data unusable.

Solution: Split into separate blocks:

WebSite schema for metadata
Organization schema for brand information
BlogPosting schema for articles

AI systems need proper structured data to understand relationships and context.

RSS Feed Generation

Problem: Dynamic RSS feeds returning HTTP 500 errors prevent Common Crawl indexing.

Solution: Add prerender: true for static RSS at build time. Common Crawl looks for RSS feeds to discover content patterns.

The Platform Validation Gap

Third-party vs Independent:

Radarly by Contently shows 0% compliance with opaque ‘proprietary algorithms’
Independent tools provide specific, actionable fixes
Ground truth (Cloudflare) shows actual AI crawler behavior

Why the discrepancy?

Platforms use black-box methodology. They prioritize vague industry averages over your actual implementation, making it impossible to fix real issues.

Always validate third-party claims with independent testing.

The GEO Advantage

Most brands optimize for SEO. They chase rankings while AI recommendations steal their traffic.

Brands optimizing for GEO win twice:

AI Recommendation Traffic: Direct referrals from AI systems
Search Spill-over: Authority signals from AI mentions boost SEO

The future belongs to brands that AI systems know, trust, and recommend.

Technical implementation gets you in the door. GEO strategy gets you the recommendation.

‘Trust but verify’ doesn’t just apply to crypto. It applies to SEO and GEO too.

Always validate third-party AI visibility claims with independent testing.