freshstore.app 71 B
🛡️ SEO 57 🤖 GEO 80 ⚡ Perf 62 🏗️ Arch 80

freshstore.app — Global SEODiff Score 71/100

freshstore.app
📊

freshstore.app achieves a 68/100 on the AI-Crawler Reality Index, reflecting above-average readiness for AI-driven discovery. In the infrastructure sector, freshstore.app outperforms the average (58), 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 tight 3.8× token bloat ratio reflects disciplined markup: minimal noise between the crawler and the content it needs. Minimal structured data (1 block) limits the site's ability to communicate entity relationships to AI systems. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

71
B — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Traditional SEO (57) is your bottleneck.
🎯 Top Fix: Add HSTS header → +2 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than freshstore.app?
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)57 × 0.25 = 14.2
🤖 AI Readiness / GEO (40% weight)80 × 0.40 = 32.0
⚡ Performance (20% weight)62 × 0.20 = 12.4
🏗️ Architecture & Trust (15% weight)80 × 0.15 = 12.0
Weighted sum = 14.2 + 32.0 + 12.4 + 12.0
Global SEODiff Score = 71 (B)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
99
Rendering
avg 93
38
Structure
avg 36
2
Schema
avg 9
55
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 21%
Rank #206529
+19 pts
Gap
AI (ACRI)
Top 39%
Score 68/100

freshstore.app 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 freshstore.app ranks here

Tech stackExpress
RenderingSSR
Schema coverage1 blocks
Token bloat3.8×

Fastest improvements

  • You’re already in decent shape — the next moat is monitoring drift over time.
  • 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

57/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

43 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

182 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://www.freshstore.com
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✓ og:title — FreshStore - The AI Affiliate Store Builder
  • ✓ og:description — Create powerful affiliate stores with artificial intelligence using the FreshStore affiliate store builder platform. Integrated with Amazon, eBay, Etsy, Walmart, AliExpress and more.
  • ✓ 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

80/100 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 infrastructure sector, safely.co.jp (ACRI: 90) 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 →
freshstore.app
56
Your ACRI Score
90
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. safely.co.jp has schema coverage of 3 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 38/100 — Low
Structured Elements 38 elements (38 lists, 0 rows, 0 headers)
Total Words860
Raw Density4.4%
💡Low structure score (38/100). Your content appears as a wall of text with few structured HTML elements. You have 38 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 Blocks1 block(s) — Basic (low value for AI)

Schema Coverage Map

1/7 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.

📐 AI Efficiency Metrics Docs

57
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability57/100 — 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

26%
🗑️ 74%
Useful Content (20.3 KB)Bloat (56.8 KB)
Token Bloat Ratio3.8× — Lean

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage19 / 19 images have alt text

TDM Rights

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

🔥 Structural Entropy Check Research

30 Entropy
Poor Token Bloat: High
Noise Ratio: 73.6% · SNR: 0.36 · Signal: 5208 / Noise: 14539 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/Qwen2.5-7B-Instruct-4bit) analyzed the extracted content of freshstore.app 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
Create automatic affiliate stores with AI
Target Audience
Entrepreneurs looking for easy online stores
Pricing Model
Not specified
🔗 Integration Partners
AmazoneBayEtsyWalmartAliExpress
Model: mlx-community/Qwen2.5-7B-Instruct-4bit · Analyzed: 2026-02-25 · Data extracted from the site’s main content via strict JSON prompting.

🔧 Tech Stack

FrameworkExpress
AI-Readiness Score55/100
ServerBunnyCDN-CA1-1025
CDN
HTTP Status200
Load Time1468 ms
Raw HTML Size77.1 KB
Visible Text Size20.3 KB

Performance & Speed

62/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1468 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

546
DOM nodes
77 KB
HTML payload
Lean page — fast for bots and users

🗄️ Cache & CDN

  • ✓ Cache-Control header → public, max-age=604800
  • ✗ 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

80/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

  • ✓ Sitemap declared in robots.txt → https://www.freshstore.com/sitemap.xml
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

39
internal links
33
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 56/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for freshstore.app
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/freshstore.app" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=freshstore.app" 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.

🔗 Similar infrastructure Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
freshstore.app (this site) 56 68 Express 3.8× 1
elektramat.nl 81 87 Express 3.7× 2 Compare →
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teteamodeler.com 81 85 Express 1.9× 2 Compare →
bureau-vallee.fr 81 85 Express 2.3× 3 Compare →
cn.ca 81 87 Express 1.7× 3 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to freshstore.app. 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": "Freshstore",
  "url": "https://freshstore.app",
  "logo": "https://freshstore.app/apple-touch-icon.png",
  "sameAs": []
}
</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 Freshstore?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Freshstore does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Freshstore work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Freshstore."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for freshstore.app:

Current Score
68
Projected Score
77
Improvement
+9 pts
Add Organization schema +6 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

🧠 AI Citation Graph

How this domain is cited across the machine-readable web

2.6
AI-Trust
#1093
Global Rank
39%
Percentile
2
Inbound AI Links
0
Outbound AI Links
56
Avg Inbound ACRI
Top AI Referrers
Domain ACRI AI-Trust Direction
pushchairsandprams.uk 59 0.0 ← cites you
exercisebikesonline.uk 52 0.0 ← cites you
View Full AI-Trust Leaderboard →