minneapolisfed.org 60 C
🛡️ SEO 46 🤖 GEO 57 ⚡ Perf 68 🏗️ Arch 79

minneapolisfed.org — Global SEODiff Score 60/100

minneapolisfed.org
📊

With a solid 69/100 ACRI, minneapolisfed.org is well-positioned for AI search — better than 64% of sites in the Radar. Within the finance vertical, this places minneapolisfed.org above the industry average of 57 —, suggesting strong competitive positioning in AI search. Server-side rendering keeps the ghost ratio near zero, giving AI systems direct access to all visible content. A 31.4× token bloat ratio means crawlers must process significantly more tokens to reach the actual content — a drag on extraction efficiency. The complete absence of JSON-LD schema is a missed opportunity: even basic Organization markup would improve how AI crawlers understand this domain. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

60
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (46) is your bottleneck.
🎯 Top Fix: Reduce token bloat (31×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 1, 2026 · 📋 API
Does your site score higher than minneapolisfed.org?
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)46 × 0.25 = 11.5
🤖 AI Readiness / GEO (40% weight)57 × 0.40 = 22.8
⚡ Performance (20% weight)68 × 0.20 = 13.6
🏗️ Architecture & Trust (15% weight)79 × 0.15 = 11.8
Weighted sum = 11.5 + 22.8 + 13.6 + 11.8
Global SEODiff Score = 60 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
34
Structure
avg 36
0
Schema
avg 9
70
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 5%
Rank #51502
+31 pts
Gap
AI (ACRI)
Top 36%
Score 69/100

minneapolisfed.org 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 minneapolisfed.org ranks here

Tech stackNext.js
Industryfinance
RenderingSSR
Schema coverage0 blocks
Token bloat31.4×

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

46/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

35 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

187 chars
Too long

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 4
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✗ Canonical tag present
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — Federal Reserve Bank of Minneapolis
  • ✗ og:description
  • ✓ og:image — preview
  • ✓ twitter:card — summary_large_image
📐 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

57/100 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 finance sector, bbkonline.com (ACRI: 82) 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 →
minneapolisfed.org
42
Your ACRI Score
82
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. bbkonline.com has schema coverage of 1 blocks and uses WordPress. 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 34/100 — Low
Structured Elements 25 elements (25 lists, 0 rows, 0 headers)
Total Words707
Raw Density3.5%
💡Low structure score (34/100). Your content appears as a wall of text with few structured HTML elements. You have 25 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

38
AI Extractability
Medium
Crawl Cost
None
Blocklist Risk
Extractability38/100 — AI models can barely extract answers from this page
Crawl CostMedium (55/100) — moderate for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

3%
🗑️ 97%
Useful Content (5.0 KB)Bloat (151.2 KB)
Token Bloat Ratio31.4× — Bloated

Multimodal Readiness

Visual Context94% Optimized for Vision
Image Alt Coverage33 / 35 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 156.1 KB, but only 5.0 KB is text. 3% useful / 97% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (31.4×) 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: 96.8% · SNR: 0.03 · Signal: 1273 / Noise: 38696 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

A local LLM (mlx-community/gemma-3-4b-it-qat-4bit) analyzed the extracted content of minneapolisfed.org 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
This SaaS platform streamlines project management for distributed teams by providing AI-powered sprint planning and real-time resource optimization, boosting team efficiency and productivity.
Target Audience
Engineering managers, product teams, CTOs, and project managers working in distributed environments.
Pricing Model
Tiered pricing model with a free plan and paid tiers starting at $10/user/month.
🔗 Integration Partners
SlackGitHubJira
🏆 Competitive Moat
AI-powered sprint planning with real-time resource optimization, offering a significant advantage over traditional project management tools.
📊 Content Depth
7/10
🔄 Programmatic SEO Signals
Integration directory pagesTemplate comparison pages
⚡ Key Pain Points
• No structured FAQ schema
• Thin landing pages for features
Model: mlx-community/gemma-3-4b-it-qat-4bit · Analyzed: 2026-03-02 · Data extracted from the site’s main content via strict JSON prompting.

🔧 Tech Stack

FrameworkNext.js
AI-Readiness Score70/100
Server
CDN
HTTP Status200
Load Time869 ms
Raw HTML Size156.1 KB
Visible Text Size5.0 KB

Performance & Speed

68/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

869 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

700
DOM nodes
156 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
  • ✗ CDN detected

🔬 Tracker Tax

0
tracker scripts
0
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
📐 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

79/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

88
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 42/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for minneapolisfed.org
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/minneapolisfed.org" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=minneapolisfed.org" 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 69 pages · Deep-10

Homepage ACRI
42
Single-page score
+4
Consistent readability
Δ delta
Site-Wide ACRI
47
Avg across 69 pages · Range 30–71
Topical Cohesion
11%
Topical Drift
TF-IDF cosine similarity
Total Words
71578
Avg Bloat
48.7×
RAG Fractures [?]
17
⚠️
17 RAG-Chunking Fractures Detected

Poorly formatted tables or pricing grids on 17 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://minneapolisfed.org/article/2009/risks-and-realities-of-the-contract-for-deed
Risks and realities of the contract for deed | Federal Reserve Bank of Minneapolis
pricing 71 9.4× 3599 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/omg-like-where-are-all-the-teen-workers
OMG! Like, where are all the teen workers? | Federal Reserve Bank of Minneapolis
pricing 71 8.5× 4510 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/raising-the-credit-bar-or-getting-clubbed-by-it
Raising the credit bar, or getting clubbed by it? | Federal Reserve Bank of Minneapolis
pricing 71 8.6× 4092 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/run-over-by-gas
Run over by gas | Federal Reserve Bank of MinneapolisRun over by gas | fedgazette March 2009 | Federal Reserve Bank of Minneapolis
pricing 71 9.8× 2741 💰 Pricing
https://minneapolisfed.org/article/2009/campus-of-dreams-bill-it-and-they-will-come
Campus of dreams: Bill it, and they will come? | Federal Reserve Bank of Minneapolis
pricing 70 7.4× 5994 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/driving-a-hard-bargain
Driving a hard bargain | Federal Reserve Bank of Minneapolis
pricing 61 11.0× 2314 💰 Pricing
https://minneapolisfed.org/article/2009/overcoming-startup-barriers-nativeowned-food-business-serves-up-lessons-learned
Overcoming start-up barriers: Native-owned food business serves up lessons learned | Federal Reserve Bank of Minneapolis
blog 61 12.4× 2060
https://minneapolisfed.org/article/2009/blending-psychology-and-economics
Blending Psychology and Economics | Federal Reserve Bank of Minneapolis
pricing 61 10.7× 2632 💰 Pricing
https://minneapolisfed.org/article/2009/did-the-cra-cause-the-mortgage-market-meltdown
Did the CRA cause the mortgage market meltdown? | Federal Reserve Bank of Minneapolis
pricing 61 10.9× 2780 💰 Pricing
https://minneapolisfed.org/article/2009/gender-and-financial-literacy-a-conversation-with-annamaria-lusardi-of-dartmouth-college
Gender and financial literacy: A conversation with Annamaria Lusardi of Dartmouth College | Federal Reserve Bank of Minneapolis
pricing 61 11.4× 2408 💰 Pricing
https://minneapolisfed.org/article/2009/quiet-summer-at-the-lake
Quiet summer at the lake | Federal Reserve Bank of Minneapolis
blog 61 12.5× 2009
https://minneapolisfed.org/article/2009/lessons-learned-from-22-years-of-debt-mediation
Lessons learned from 22 years of debt mediation | Federal Reserve Bank of Minneapolis
pricing 61 10.5× 2628 💰 Pricing
https://minneapolisfed.org/article/2009/new-markets-mortgage-program-broadens-homeownership-opportunities-in-minnesota
New Markets Mortgage program broadens homeownership opportunities in Minnesota | Federal Reserve Bank of Minneapolis
pricing 61 10.9× 2566 💰 Pricing
https://minneapolisfed.org/article/2009/revisiting-the-placebased-cdc-model-a-conversation-with-brian-miller-of-seward-redesign
Revisiting the place-based CDC model: A conversation with Brian Miller of Seward Redesign | Federal Reserve Bank of Minneapolis
pricing 61 10.7× 2837 💰 Pricing
https://minneapolisfed.org/article/2009/home-to-roost
Home to roost | Federal Reserve Bank of Minneapolis
pricing 61 12.4× 2072 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/ninth-district-economy-slips-into-recession
Ninth District economy slips into recession | Federal Reserve Bank of Minneapolis
pricing 58 15.3× 1739 ⚠️ RAG Fracture
https://minneapolisfed.org/article/2009/not-your-fathers-farm
Not your father’s farm | Federal Reserve Bank of MinneapolisUntitled Document
blog 58 16.2× 1396
https://minneapolisfed.org/article/2009/remote-sellers-the-tax-man-cometh
Remote sellers: The tax man cometh? | Federal Reserve Bank of Minneapolis
blog 58 13.5× 1721
https://minneapolisfed.org/article/2009/recession-persists-modest-recovery-in-view
Recession persists; modest recovery in view | Federal Reserve Bank of Minneapolis
pricing 58 14.7× 1718 💰 Pricing
https://minneapolisfed.org/article/2009/giving-credit-its-due
Giving Credit Its Due | Federal Reserve Bank of Minneapolis
blog 58 17.6× 1220
Showing 20 of 69 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
/article/ 69 47 1% 48.7× Bot Blocked
🔗
Outbound External Citations
0 unique external domains cited across 69 pages
threads.net ×69
twitter.com ×69
facebook.com ×69
instagram.com ×69
linkedin.com ×69
federalreserve.gov ×4
doh.sd.gov ×1
prattcenter.net ×1
🔄 Re-Crawl & Update 📡 Track this Domain

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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/minneapolisfed.org

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

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minneapolisfed.org (this site) 42 69 Next.js 31.4× 0
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📊 Semantic Share of Voice

How often would an AI cite minneapolisfed.org 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 minneapolisfed.org. 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": "Minneapolisfed",
  "url": "https://minneapolisfed.org",
  "logo": "https://minneapolisfed.org/favicon-32x32.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": "Minneapolisfed",
  "url": "https://minneapolisfed.org",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://minneapolisfed.org/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Reduce Token Bloat
Medium Impact ⏱ 1–2 hrs
Only 3% 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 Minneapolisfed?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Minneapolisfed does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Minneapolisfed work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Minneapolisfed."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for minneapolisfed.org:

Current Score
69
Projected Score
87
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