gagosian.com 57 D
🛡️ SEO 39 🤖 GEO 56 ⚡ Perf 68 🏗️ Arch 78

gagosian.com — Global SEODiff Score 57/100

gagosian.com
📊

At 67/100, the ACRI for gagosian.com indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. Compared to other education sites (avg score: 57), gagosian.com performs above the benchmark, suggesting strong competitive positioning in AI search. The low ghost ratio (5%) confirms that what crawlers see matches what users see — a hallmark of strong SSR implementation. The bloated 40.7× token ratio highlights an urgent need to clean up non-content markup, scripts, and navigation clutter. No structured data was detected, which means AI systems must infer all entities and relationships from raw HTML alone. Robots.txt grants unrestricted access to the key AI user-agents, which is the strongest starting position for AI visibility.

57
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Traditional SEO (39) has the most room for improvement.
🎯 Top Fix: Reduce token bloat (41×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 21, 2026 · 📋 API
📈 ACRI Trend 9 snapshots
Feb 23 Mar 21
🔔 Recent AI Indexing Activity
📈 Mar 21 ACRI +1 (39→40)
🔄 Mar 19 Content change detected
🔄 Mar 17 Content change detected
🔄 Mar 12 Content change detected
Does your site score higher than gagosian.com?
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)39 × 0.25 = 9.8
🤖 AI Readiness / GEO (40% weight)56 × 0.40 = 22.4
⚡ Performance (20% weight)68 × 0.20 = 13.6
🏗️ Architecture & Trust (15% weight)78 × 0.15 = 11.7
Weighted sum = 9.8 + 22.4 + 13.6 + 11.7
Global SEODiff Score = 57 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
24
Structure
avg 35
0
Schema
avg 9
70
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 6%
Rank #60814
+35 pts
Gap
AI (ACRI)
Top 41%
Score 67/100

gagosian.com punches above its weight in AI — AI visibility exceeds Google ranking. This is a competitive moat worth protecting. ACRI measures technical crawler readiness. Read the methodology →

Why gagosian.com ranks here

Tech stackNext.js
Industryeducation
RenderingSSR
Schema coverage0 blocks
Token bloat40.7×

Fastest improvements

  • Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt →
  • Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

39/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

8 chars
Too short

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

210 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 5
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://gagosian.com/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ➖ Hreflang tags — N/A (single language site)
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Gagosian
  • ✓ og:description — Gagosian is a global network of art galleries specializing in modern and contemporary art with eighteen exhibition spaces across New York, Los Angeles, London, Paris, Basel, Gstaad, Rome, Athens, and Hong Kong.
  • ✓ og:image — preview
  • ✓ twitter:card — summary
📐 How the SEO Pillar score is calculated

SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)

Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.

🤖

AI Readiness / GEO

56/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the education sector, melbourneschool.com (ACRI: 86) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
gagosian.com
40
Your ACRI Score
86
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. melbourneschool.com has schema coverage of 4 blocks and uses Custom / Proprietary. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 5%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 24/100 — Low
Structured Elements 17 elements (17 lists, 0 rows, 0 headers)
Total Words978
Raw Density1.7%
💡Low structure score (24/100). Your content appears as a wall of text with few structured HTML elements. You have 17 list items, 0 table rows, 0 table headers. Convert features into <ul> lists and data into <table> elements to help AI models extract structured information.

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

34
AI Extractability
High
Crawl Cost
None
Blocklist Risk
Extractability34/100 — AI models can barely extract answers from this page
Crawl CostHigh (80/100) — expensive for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

2%
🗑️ 98%
Useful Content (6.4 KB)Bloat (252.2 KB)
Token Bloat Ratio40.7× — Bloated

Multimodal Readiness

Visual Context92% Optimized for Vision
Image Alt Coverage23 / 25 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 258.5 KB, but only 6.4 KB is text. 2% useful / 98% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (40.7×) risks context-window truncation by ChatGPT, Claude, and Gemini. Reduce inline scripts, CSS, hydration payloads, and tracking code.

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 97.5% · SNR: 0.03 · Signal: 1627 / Noise: 64561 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…

🔧 Tech Stack

FrameworkNext.js
AI-Readiness Score70/100
Servercloudflare
CDNcloudflare
HTTP Status200
Load Time591 ms
Raw HTML Size258.5 KB
Visible Text Size6.4 KB

Performance & Speed

68/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

591 ms
Acceptable — room for improvement

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

536
DOM nodes
258 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✓ Cache-Control header → private, no-cache, no-store, max-age=0, must-revalidate
  • ✓ CDN cache status → DYNAMIC
  • ✓ CDN detected → cloudflare

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
googlesyndication.com
📐 How the Performance Pillar score is calculated

Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)

TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.

🏗️

Architecture & Trust

78/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✗ Sitemap declared in robots.txt
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

47
internal links
10
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✓ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✓ HTML lang attribute → en
  • ✓ Meta viewport for mobile
  • ✓ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated

Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)

Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.

🏅 AI-Verified Trust Badge

Your site scores 40/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for gagosian.com
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/gagosian.com" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=gagosian.com" alt="AI-Verified by SEODiff" width="280" height="52"></a>

💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.

� Deep Crawl Analysis 70 pages · Deep-10

Homepage ACRI
40
Single-page score
+3
Consistent readability
Δ delta
Site-Wide ACRI
44
Avg across 70 pages · Range 0–64
Topical Cohesion
14%
Topical Drift
TF-IDF cosine similarity
Total Words
65061
Avg Bloat
43.5×
Page Type ACRI Token Bloat Words Status
https://gagosian.com/about
About the Gallery | About | Gagosian
about 64 12.8× 549
https://gagosian.com/about/
About the Gallery | About | Gagosian
about 64 12.8× 549
https://gagosian.com/about/about-larry-gagosian/
About Larry Gagosian | About | Gagosian
about 64 12.2× 616
https://gagosian.com/about/about-gallery/
About the Gallery | About | Gagosian
about 64 12.8× 549
https://gagosian.com/exhibitions/2025/the-omnipotence-of-dreams/
The Omnipotence of Dreams, Gstaad, December 19, 2025–January 25, 2026 | Gagosian
other 50 31.5× 1967
https://gagosian.com/exhibitions/2026/irving-penn/
Irving Penn, Gstaad, February 14–April 6, 2026 | Gagosian
other 50 58.6× 718
https://gagosian.com/exhibitions/2025/rick-lowe-harbour-fragments/
Rick Lowe: Harbour Fragments, Hong Kong, September 11–November 1, 2025 | Gagosian
pricing 50 51.9× 1161 💰 Pricing
https://gagosian.com/exhibitions/2025/paul-mccartney-rearview-mirror-liverpool-london-paris/
Paul McCartney: Rearview Mirror: Liverpool–London–Paris, Davies Street, London, August 28–October 4, 2025 | Gagosian
pricing 50 40.8× 1466 💰 Pricing
https://gagosian.com/exhibitions/2025/ed-ruscha-talking-doorways/
Ed Ruscha: Talking Doorways, rue de Castiglione, Paris, October 22–December 3, 2025 | Gagosian
pricing 50 50.9× 1071 💰 Pricing
https://gagosian.com/exhibitions/2025/brice-marden-etched-letters/
Brice Marden: Etched Letters, Burlington Arcade, London, October 10–November 29, 2025 | Gagosian
pricing 50 46.6× 990 💰 Pricing
https://gagosian.com/exhibitions/2025/spencer-sweeney-paint/
Spencer Sweeney: Paint, Hong Kong, November 19, 2025–February 28, 2026 | Gagosian
other 50 62.1× 891
https://gagosian.com/exhibitions/2026/mirrored-fiction/
Mirrored Fiction, Rome, February 11–April 11, 2026 | Gagosian
other 50 39.5× 1639
https://gagosian.com/exhibitions/2026/roe-ethridge-rude-in-the-good-way/
Roe Ethridge: Rude in the Good Way, Athens, January 22–March 7, 2026 | Gagosian
other 50 61.7× 1041
https://gagosian.com/exhibitions/2026/helen-frankenthaler-the-moment-and-the-distance/
Helen Frankenthaler: The Moment and the Distance, West 21st Street, New York, April 30–July 2, 2026 | Gagosian
pricing 50 43.6× 1120 💰 Pricing
https://gagosian.com/exhibitions/2026/roy-lichtenstein-painting-with-scattered-brushstrokes/
Roy Lichtenstein: Painting with Scattered Brushstrokes, 541 West 24th Street, New York, March 19–April 25, 2026 | Gagosian
pricing 50 45.2× 1023 💰 Pricing
https://gagosian.com/exhibitions/2026/jonas-wood/
Jonas Wood, Beverly Hills, March 12–April 25, 2026 | Gagosian
pricing 50 50.2× 661 💰 Pricing
https://gagosian.com/exhibitions/2026/sarah-sze-feel-free/
Sarah Sze: Feel Free, Beverly Hills, January 29–February 28, 2026 | Gagosian
pricing 50 54.0× 1346 💰 Pricing
https://gagosian.com/exhibitions/2026/jasper-johns-between-the-clock-and-the-bed/
Jasper Johns: Between the Clock and the Bed, 980 Madison Avenue, New York, January 22–March 14, 2026 | Gagosian
pricing 50 43.5× 1474 💰 Pricing
https://gagosian.com/exhibitions/2026/richard-avedon-facing-west/
Richard Avedon: Facing West, Grosvenor Hill, London, January 15–April 11, 2026 | Gagosian
other 50 58.0× 968
https://gagosian.com/exhibitions/2026/james-turrell-after-glow/
James Turrell: After Glow, Burlington Arcade, London, January 14–March 14, 2026 | Gagosian
pricing 50 38.8× 1238 💰 Pricing
Showing 20 of 70 pages. Unlock full subpage table →
📂
Health by Sub-Directory
Average ACRI and top issues aggregated by URL path prefix
Path Pages Avg ACRI Ghost % Bloat Top Issue
/exhibitions/ 55 50 1% 50.8× Bot Blocked
/about/ 4 64 0% 12.7× High JS Bloat
/docs/ 1 0 0% 0.0× Low AI Readiness
/press/ 1 33 1% 60.4× Bot Blocked
/features/ 1 0 0% 0.0× Low AI Readiness
/blog/ 1 0 0% 0.0× Low AI Readiness
/faq/ 1 0 0% 0.0× Low AI Readiness
/case-studies/ 1 0 0% 0.0× Low AI Readiness
/integrations/ 1 0 0% 0.0× Low AI Readiness
/jobs/ 1 23 1% 134.2× Bot Blocked
/pricing/ 1 0 0% 0.0× Low AI Readiness
/products/ 1 0 0% 0.0× Low AI Readiness
/contact/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 70 pages
tiktok.com ×61
facebook.com ×61
x.com ×61
youtube.com ×61
instagram.com ×61
artsy.net ×61
gagosianshop.com ×61
pinterest.com ×61
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🔌 API Access

Pull this data programmatically. All sub-page metrics are available via our public API.

curl https://seodiff.io/api/v1/deep10/domain/gagosian.com

Get your free API key — 100 requests/month included.

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📊 Semantic Share of Voice

How often would an AI cite gagosian.com when users ask about topics in this domain's niche? We run entity queries through our 188k-page search index and measure citation probability.

Analyzing citation landscape…

🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to gagosian.com. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Gagosian",
  "url": "https://gagosian.com",
  "logo": "https://gagosian.com/image/gagosian-next.ico",
  "sameAs": []
}
</script>
Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Gagosian",
  "url": "https://gagosian.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://gagosian.com/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 2% of your HTML is useful content. AI crawlers waste context window tokens on bloat.
html
<!-- Move inline CSS to external stylesheets -->
<link rel="stylesheet" href="/css/main.css">

<!-- Move inline scripts to external files with defer -->
<script src="/js/app.js" defer></script>

<!-- Remove duplicate navigation blocks -->
<!-- Keep only ONE <nav> in the <header> -->

<!-- Ensure <main> wraps your primary content -->
<main>
  <!-- Your content here — this is what AI sees first -->
</main>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Gagosian?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Gagosian does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Gagosian work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Gagosian."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for gagosian.com:

Current Score
67
Projected Score
85
Improvement
+18 pts
Add Organization schema +6 pts
Add WebSite schema +4 pts
Reduce token bloat +5 pts
Add FAQ schema +3 pts

*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.

📋 Data Export

Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).

All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).

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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history
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