whowhatwear.com 63 C
🛡️ SEO 58 🤖 GEO 60 ⚡ Perf 47 🏗️ Arch 100

whowhatwear.com — Global SEODiff Score 63/100

whowhatwear.com
📊

At 70/100, the ACRI for whowhatwear.com indicates strong fundamentals in AI extractability, surpassing the majority of indexed sites. In the infrastructure sector, whowhatwear.com outperforms the average (57), suggesting strong competitive positioning in AI search. Content is delivered server-side, meaning bots and AI agents can parse the full page without executing JavaScript. The bloated 37.0× token ratio highlights an urgent need to clean up non-content markup, scripts, and navigation clutter. With 4 JSON-LD schema blocks, the site provides explicit machine-readable metadata that enhances AI comprehension. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

63
C — Global SEODiff Score
Comprehensive search visibility assessment
Strong foundations, but Performance (47) is your bottleneck.
🎯 Top Fix: Reduce token bloat (37×) → +5–10 pts
🔬 Automated SEODiff Assessment · Snapshot: Mar 21, 2026 · 📋 API
📈 ACRI Trend 8 snapshots
Mar 7 Mar 21
🔔 Recent AI Indexing Activity
🔄 Mar 21 Content change detected
🔄 Mar 20 Content change detected
🔄 Mar 20 Content change detected
🔄 Mar 19 Content change detected
🔄 Mar 18 Content change detected
Does your site score higher than whowhatwear.com?
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)58 × 0.25 = 14.5
🤖 AI Readiness / GEO (40% weight)60 × 0.40 = 24.0
⚡ Performance (20% weight)47 × 0.20 = 9.4
🏗️ Architecture & Trust (15% weight)100 × 0.15 = 15.0
Weighted sum = 14.5 + 24.0 + 9.4 + 15.0
Global SEODiff Score = 63 (C)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
97
Rendering
avg 93
45
Structure
avg 35
8
Schema
avg 9
55
Tech Stack
avg 63
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 1%
Rank #13169
+32 pts
Gap
AI (ACRI)
Top 33%
Score 70/100

whowhatwear.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 whowhatwear.com ranks here

Tech stackExpress
RenderingHybrid
Schema coverage4 blocks
Token bloat37.0×

Fastest improvements

  • 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

58/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

58 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

140 chars
Good length

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✓ Exactly 1 <h1> tag — found 1
  • ✓ Has <h2> headings — found 183
  • ✓ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.whowhatwear.com
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✓ HTML lang attribute → en
  • ✅ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✗ og:title
  • ✗ og:description
  • ✗ 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

60/100 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 →
whowhatwear.com
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 10%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type Hybrid

📊 Structure & Information Density Docs

Structure Grade 45/100 — Fair
Structured Elements 273 elements (273 lists, 0 rows, 0 headers)
Total Words4470
Raw Density6.1%

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks4 blocks

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

42
AI Extractability
High
Crawl Cost
None
Blocklist Risk
Extractability42/100 — AI models can partially extract answers from this page
Crawl CostHigh (95/100) — expensive for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

2%
🗑️ 98%
Useful Content (34.9 KB)Bloat (1256.9 KB)
Token Bloat Ratio37.0× — Bloated

Multimodal Readiness

Visual Context100% Optimized for Vision
Image Alt Coverage183 / 183 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set
💡Your HTML is 1291.8 KB, but only 34.9 KB is text. 2% useful / 98% bloat. AI crawlers have limited context windows (e.g. 128k tokens). This level of bloat (37.0×) 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: 97.3% · SNR: 0.03 · Signal: 8937 / Noise: 321773 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 whowhatwear.com 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
Who What Wear is a digital fashion and beauty destination providing trend reporting, shoppable guides, celebrity style coverage, and expert
Target Audience
Fashion enthusiasts, shoppers, stylists, celebrity stylists, fashion editors, and trend forecasters.
Pricing Model
Not explicitly stated, likely a combination of affiliate marketing and potential premium subscription options in the future.
🔗 Integration Partners
NordstromShopbopNet-a-PorterAmazon
🏆 Competitive Moat
AI-powered trend analysis and personalized content recommendations, combined with a strong editorial team and celebrity collaborations.
📊 Content Depth
8/10
🔄 Programmatic SEO Signals
Integration directory pagesTemplate comparison pages
⚡ Key Pain Points
• Lack of structured FAQ schema
• Thin landing pages for features
Analyzed by SEODiff AI · 2026-03-01

🔧 Tech Stack

FrameworkExpress
AI-Readiness Score55/100
Server
CDN
HTTP Status200
Load Time601 ms
Raw HTML Size1291.8 KB
Visible Text Size34.9 KB

Performance & Speed

47/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

601 ms
Slow — bots may time out or deprioritise

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

📦 Page Weight

2996
DOM nodes
1292 KB
HTML payload
Heavy page — consider reducing DOM complexity

🗄️ Cache & CDN

  • ✓ Cache-Control header → no-store,private
  • ✗ 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

100/100 15 % of Global Score 🟢 High Confidence

🗺️ Sitemap & Robots

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

🔗 Linking

252
internal links
30
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 whowhatwear.com
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/whowhatwear.com" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=whowhatwear.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 137 pages · Deep-10

Homepage ACRI
56
Single-page score
+12
Subpages outperform homepage
Δ delta
Site-Wide ACRI
68
Avg across 137 pages · Range 0–72
Topical Cohesion
8%
Topical Drift
TF-IDF cosine similarity
Total Words
249119
Avg Bloat
139.2×
RAG Fractures [?]
2
⚠️
2 RAG-Chunking Fractures Detected

Poorly formatted tables or pricing grids on 2 pages will be split incorrectly during RAG chunking, causing AI models to hallucinate prices and features.

Page Type ACRI Token Bloat Words Status
https://www.whowhatwear.com/promo-codes/outcast-clothing
Clothing Promo Codes for March 2026
other 72 23.5× 9984
https://whowhatwear.com/about
Who What Wear About Us | Who What Wear
pricing 69 50.3× 4255 💰 Pricing
https://www.whowhatwear.com/features
Guides, Interviews and in-Depth Stories | Who What Wear
pricing 69 261.7× 783 💰 Pricing
https://whowhatwear.com/features
Guides, Interviews and in-Depth Stories | Who What Wear
pricing 69 268.8× 763 💰 Pricing
https://whowhatwear.com/blog
The 11 Best Blogger Halloween Costumes of All Time | Who What Wear
blog 69 217.9× 970
https://www.whowhatwear.com/living/career/second-life-podcast-jamie-haller
Second Life Podcast: Jamie Haller | Who What Wear
careers 69 188.8× 1097
https://www.whowhatwear.com/living/career/second-life-podcast-claudia-sulewski
Second Life Podcast: Claudia Sulewski | Who What Wear
careers 69 201.9× 1025
https://www.whowhatwear.com/living/career/second-life-podcast-erica-malbon
Second Life Podcast: Erica Malbon | Who What Wear
careers 69 191.8× 1121
https://www.whowhatwear.com/living/career/second-life-podcast-melanie-bender
Second Life Podcast: Melanie Bender | Who What Wear
careers 69 198.3× 1038
https://www.whowhatwear.com/living/career/second-life-podcast-celia-munoz
Second Life Podcast: Celia Muñoz | Who What Wear
careers 69 187.7× 1103
https://www.whowhatwear.com/living/career/second-life-podcast-toni-chapman
Second Life Podcast: Toni Chapman | Who What Wear
careers 69 198.7× 1032
https://www.whowhatwear.com/living/career/second-life-podcast-carla-rockmore
Second Life Podcast: Carla Rockmore | Who What Wear
careers 69 197.0× 1028
https://www.whowhatwear.com/living/career/second-life-podcast-brynn-putnam
Second Life Podcast: Brynn Putnam | Who What Wear
careers 69 209.4× 971
https://www.whowhatwear.com/living/career/second-life-podcast-melissa-morris
Second Life Podcast: Melissa Morris | Who What Wear
careers 69 189.8× 1105
https://www.whowhatwear.com/living/career/second-life-podcast-jenee-naylor
Second Life Podcast: Jenee Naylor | Who What Wear
careers 69 201.7× 1046
https://www.whowhatwear.com/living/career/second-life-podcast-gregg-renfrew
Second Life Podcast: Gregg Renfrew | Who What Wear
careers 69 181.8× 1143
https://www.whowhatwear.com/living/career
Career Tools and Tips to Succeed at Work | Who What Wear
pricing 69 328.8× 625 💰 Pricing
https://www.whowhatwear.com/living/career/second-life-podcast-alison-roman-2026
Second Life Podcast: Alison Roman | Who What Wear
careers 69 200.8× 1013
https://www.whowhatwear.com/living/career/second-life-podcast-elyse-myers
Second Life Podcast: Elyse Myers | Who What Wear
pricing 69 205.8× 990 💰 Pricing
https://www.whowhatwear.com/living/career/second-life-podcast-leslie-tessler
Second Life Podcast: Leslie Tessler | Who What Wear
careers 69 208.3× 1019
Showing 20 of 100 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
/promo-codes/ 74 69 0% 109.0× High JS Bloat
/fashion/ 32 69 0% 172.8× High JS Bloat
/living/ 19 69 0% 197.4× High JS Bloat
/beauty/ 6 69 0% 154.0× High JS Bloat
/features/ 2 69 0% 265.2× High JS Bloat
/about/ 1 69 0% 50.3× High JS Bloat
/blog/ 1 69 0% 217.9× High JS Bloat
/products/ 1 0 0% 0.0× Low AI Readiness
/docs/ 1 0 0% 0.0× Low AI Readiness
🔗
Outbound External Citations
0 unique external domains cited across 137 pages
facebook.com ×135
google.com ×135
go.future-advertising.com ×135
instagram.com ×135
twitter.com ×135
futureplc.com ×135
podcasts.apple.com ×135
pinterest.com ×135
🔄 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/whowhatwear.com

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

🔗 Similar infrastructure Sites

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

Domain ACRI AI Score Tech Stack Token Bloat Schema
whowhatwear.com (this site) 56 70 Express 37.0× 4
wholesaleweddingsuperstore.com.au 81 87 Express 5.1× 3 Compare →
bureau-vallee.gf 81 86 Express 2.1× 3 Compare →
platinumshop.hu 81 87 Express 2.8× 2 Compare →
puuilo.fi 81 87 Express 4.1× 2 Compare →
yenny-elateneo.com 81 89 Express 5.7× 127 Compare →
Compare All 5 Similar Sites →

📊 Semantic Share of Voice

How often would an AI cite whowhatwear.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 whowhatwear.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": "Whowhatwear",
  "url": "https://whowhatwear.com",
  "logo": "https://cdn.mos.cms.futurecdn.net/flexiimages/qzgqdurjen1667467717.png",
  "sameAs": []
}
</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 Whowhatwear?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Whowhatwear does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Whowhatwear work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Whowhatwear."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

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

Current Score
70
Projected Score
84
Improvement
+14 pts
Add Organization schema +6 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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