fdot.gov 59 D
🛡️ SEO 14 🤖 GEO 75 ⚡ Perf 74 🏗️ Arch 69

fdot.gov — Global SEODiff Score 59/100

fdot.gov
📊

With a solid 66/100 ACRI, fdot.gov is well-positioned for AI search — better than 57% of sites in the Radar. In the government sector, fdot.gov outperforms the average (57), 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 token bloat ratio sits at a lean 4.1×, meaning the ratio of code to visible content is efficient — crawlers spend their token budget on actual information. No structured data was detected, which means AI systems must infer all entities and relationships from raw HTML alone. All major AI bot user-agents (GPTBot, ClaudeBot, CCBot, Google-Extended) are permitted by robots.txt, ensuring broad AI crawler access.

59
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Traditional SEO (14) has the most room for improvement.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 21, 2026 · 📋 API
📈 ACRI Trend 7 snapshots
Feb 23 Mar 21
🔔 Recent AI Indexing Activity
No recent changes detected by adaptive crawler.
Does your site score higher than fdot.gov?
Run the same 40-signal audit on your own domain — free, instant results.
Scan Your Site Free →
🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)14 × 0.25 = 3.5
🤖 AI Readiness / GEO (40% weight)75 × 0.40 = 30.0
⚡ Performance (20% weight)74 × 0.20 = 14.8
🏗️ Architecture & Trust (15% weight)69 × 0.15 = 10.3
Weighted sum = 3.5 + 30.0 + 14.8 + 10.3
Global SEODiff Score = 59 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
28
Structure
avg 35
0
Schema
avg 9
55
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 8%
Rank #79481
+36 pts
Gap
AI (ACRI)
Top 43%
Score 66/100

fdot.gov 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 fdot.gov ranks here

Tech stackExpress
Industrygovernment
RenderingSSR
Schema coverage0 blocks
Token bloat4.1×

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

14/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

4 chars
Too short

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

215 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 0
  • ✓ Has <h2> headings — found 18
  • ✗ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.fdot.gov
  • ✓ 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 — Home
  • ✓ og:description — Florida Department of Transportation, FDOT, Florida Airport, Florida Bridges, Florida Interstates, Florida Rail, Florida Rest Areas, Florida Seaports, Florida Service Plazas, Florida Welcome Centers, Florida Traffic
  • ✗ og:image
  • ✗ twitter:card
📐 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

75/100 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 government sector, gep.com (ACRI: 83) 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 →
fdot.gov
47
Your ACRI Score
83
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. gep.com has schema coverage of 3 blocks and uses Drupal. 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 28/100 — Low
Structured Elements 24 elements (24 lists, 0 rows, 0 headers)
Total Words1044
Raw Density2.3%
💡Low structure score (28/100). Your content appears as a wall of text with few structured HTML elements. You have 24 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

53
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability53/100 — AI models can partially extract answers from this page
Crawl CostLow (30/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

24%
🗑️ 76%
Useful Content (14.8 KB)Bloat (46.3 KB)
Token Bloat Ratio4.1× — Lean

Multimodal Readiness

Visual Context94% Optimized for Vision
Image Alt Coverage32 / 34 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

23 Entropy
Poor Token Bloat: High
Noise Ratio: 75.8% · SNR: 0.32 · Signal: 3786 / Noise: 11845 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…
🧠

The LLM Interpretation

AI-VERIFIED

SEODiff AI analyzed the extracted content of fdot.gov and produced this structured business intelligence. Fields marked SEMANTIC VOID indicate information the AI could not find — a critical gap in your site’s machine-readability.

Core Offering
FDOT’s NEVI program facilitates EV charging infrastructure deployment across Florida, prioritizing strategic locations and underserved communities.
Target Audience
State transportation officials, federal highway administrators, and EV infrastructure developers.
Pricing Model
⚠ SEMANTIC VOID
🏆 Competitive Moat
Strategic alignment with federal NEVI program priorities and phased implementation approach.
📊 Content Depth
3/10
Analyzed by SEODiff AI · 2026-03-04

🔧 Tech Stack

FrameworkExpress
AI-Readiness Score55/100
ServerMicrosoft-IIS/10.0
CDN
HTTP Status200
Load Time724 ms
Raw HTML Size61.1 KB
Visible Text Size14.8 KB

Performance & Speed

74/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

724 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

460
DOM nodes
61 KB
HTML payload
Lean page — fast for bots and users

🗄️ Cache & CDN

  • ✓ Cache-Control header → no-cache
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
googletagmanager.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

69/100 15 % of Global Score 🟡 Medium Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

47
internal links
13
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 47/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for fdot.gov
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/fdot.gov" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=fdot.gov" 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 58 pages · Deep-10

Homepage ACRI
47
Single-page score
-11
Moderate hidden bloat
Δ delta
Site-Wide ACRI
36
Avg across 58 pages · Range 0–77
🔍
Hidden Bloat Detected

Homepage scores 47, but internal pages average only 36 — a -11-point gap. Blogs, docs, and legacy content are dragging down AI readability site-wide.

Topical Cohesion
18%
Topical Drift
TF-IDF cosine similarity
Total Words
12948
Avg Bloat
211.2×
RAG Fractures [?]
1
⚠️
1 RAG-Chunking Fracture Detected

Poorly formatted tables or pricing grids on 1 page will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://www.fdot.gov/forecasting/fl-transportation-forecasting-resource-hub/resources
Resources
pricing 77 7.5× 1737 💰 Pricing
https://www.fdot.gov/Safety/resources/faq.shtm
Frequently Asked Questions
pricing 77 6.4× 1324 💰 Pricing
https://www.fdot.gov/emergingtechnology/articles/2023-fav
2023-FAV
pricing 67 12.5× 676 💰 Pricing
https://www.fdot.gov/planning/plans/default.shtm
Plans and Studies
pricing 67 13.5× 678 💰 Pricing
https://www.fdot.gov/emergingtechnology/articles/plugfest
plugfest
pricing 67 11.6× 717 💰 Pricing
https://www.fdot.gov/designsupport/districts/d4lap/resources
D4 LAP Resources
pricing 56 32.7× 580 ⚠️ RAG Fracture
https://www.fdot.gov/Safety/resources/crosswalk-safety/crosswalksafety.shtm
Crosswalk Safety Tips for Road Users
pricing 54 19.8× 375 💰 Pricing
https://www.fdot.gov/construction/training/selfstudy/tutorial/tutorialprogram.shtm
Tutorial Program
pricing 54 18.3× 407 💰 Pricing
https://www.fdot.gov/it/docs/dispfilesold.shtm
PDM Archive Templates
pricing 49 39.8× 230 💰 Pricing
https://www.fdot.gov/it/docs/pdm.shtm
Project Delivery Methodology
pricing 49 26.7× 275 💰 Pricing
https://www.fdot.gov/rail/plans/railplan
Rail System Plan
pricing 49 27.7× 306 💰 Pricing
https://www.fdot.gov/rail/plans/mcplan.shtm
Motor Carrier System Plan
pricing 49 35.8× 212 💰 Pricing
https://www.fdot.gov/rail/plans/railplan/listening-sessions
Rail-Transit Listening Sessions
pricing 49 30.2× 249 💰 Pricing
https://www.fdot.gov/Safety/resources/trafficsafetytips.shtm
Traffic Safety Tips
pricing 49 20.7× 339 💰 Pricing
https://www.fdot.gov/materials/administration/resources/contacts/mac.shtm
MAC Contact Information
pricing 49 30.8× 327 💰 Pricing
https://www.fdot.gov/projects/floridasrts/resources/florida-safe-routes-to-school-tool-kit
Florida Safe Routes to School Tool Kit
pricing 49 29.2× 271 💰 Pricing
https://www.fdot.gov/projects/floridasrts/resources/resources
Resources
pricing 49 20.6× 424 💰 Pricing
https://www.fdot.gov/materials/administration/resources/contacts/materialengineers.shtm
Materials Engineers
pricing 49 28.0× 258 💰 Pricing
https://www.fdot.gov/emergingtechnology/home/evprogram/about
About FDOT's Electric Vehicle Charging Infrastructure Program
pricing 49 29.1× 280 💰 Pricing
https://www.fdot.gov/Safety/resources/crosswalk-safety/crosswalksafetyillustrated.shtm
Crosswalk Safety
pricing 49 25.2× 295 💰 Pricing
Showing 20 of 58 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
/materials/ 10 38 0% 88.5× High JS Bloat
/projects/ 7 41 0% 250.2× High JS Bloat
/it/ 5 37 0% 413.8× High JS Bloat
/Safety/ 4 57 0% 18.0× High JS Bloat
/rail/ 4 46 0% 43.8× High JS Bloat
/emergingtechnology/ 4 52 0% 355.0× High JS Bloat
/traffic/ 3 41 0% 73.3× High JS Bloat
/forecasting/ 2 63 0% 21.4× High JS Bloat
/planning/ 2 46 0% 95.4× High JS Bloat
/nwflroads/ 2 39 0% 46.7× High JS Bloat
/pricing/ 1 0 0% 0.0× Low AI Readiness
/features/ 1 0 0% 0.0× Low AI Readiness
/about/ 1 0 0% 0.0× Low AI Readiness
/construction/ 1 54 0% 18.3× High JS Bloat
/integrations/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 58 pages
twitter.com ×47
facebook.com ×47
myflorida.com ×47
instagram.com ×47
performance-data-integration-space-fdot.hub.arcgis.com ×47
youtube.com ×47
fdotwww.blob.core.windows.net ×18
fhwa.dot.gov ×4
🔄 Re-Crawl & Update 📡 Track this Domain

Scores update automatically each month. Create a free account for on-demand re-crawls (3/month free).

🔌 API Access

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

curl https://seodiff.io/api/v1/deep10/domain/fdot.gov

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

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Domains with a similar tech stack, industry, and AI readiness profile to fdot.gov. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
fdot.gov (this site) 47 66 Express 4.1× 0
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📊 Semantic Share of Voice

How often would an AI cite fdot.gov 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 fdot.gov. 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": "Fdot",
  "url": "https://fdot.gov",
  "logo": "https://fdot.gov/logo.png",
  "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": "Fdot",
  "url": "https://fdot.gov",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://fdot.gov/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
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 Fdot?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Fdot does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Fdot work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Fdot."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for fdot.gov:

Current Score
66
Projected Score
82
Improvement
+16 pts
Add Organization schema +6 pts
Add WebSite schema +4 pts
Reduce token bloat +3 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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