Growth audit

Allbirds

allbirds.com

Run 30 July 2026, 1 day ago

What we measured

Four separate checks. There is no single overall score, because these measure different things and averaging them would hide which one needs work.

Agent readability: 50/100
Tracking hygiene: 65/100
Landing page: 88/100
AI visibility: Not measured

The headline

137 of 291 product listings (47%) are unbuyable in any size or variant, yet they remain published and crawlable. This creates a dead end for shoppers and AI agents recommending your products.

What is costing you right now

Unbuyable Products: 47% of your product listings cannot be purchased in any size or variant. This frustrates potential buyers and AI agents, leading to lost sales opportunities.
Missing Schema Markup: No Product or Organization schema detected. This prevents AI agents from understanding your product data and brand identity, hindering visibility in AI-driven shopping experiences.
Multiple GTM Containers: Multiple Google Tag Manager containers detected. This can lead to tracking inconsistencies and data discrepancies, affecting marketing insights.
Lack of Audience Declaration: Your site does not specify who your products are for. This omission limits AI agents' ability to match your products to demographic-specific queries, reducing potential reach.
Visual Accessibility Issues: 3 of 43 images lack alt text. This can impede accessibility and SEO, impacting user experience and search engine rankings.

Fix this week

Remove Dead Listings: Unpublish the 137 unbuyable product listings to prevent dead-end experiences for users and AI agents.
Add Alt Text: Provide alt text for the 3 images currently missing it to improve accessibility and SEO.
Consolidate GTM Containers: Review and consolidate your Google Tag Manager containers to ensure consistent and accurate tracking.

Fix this quarter

Implement Schema Markup: Add Product and Organization schema to your site to enhance AI agents' ability to parse your product data and brand identity.
Declare Audience: Update your title, meta description, and structured data to include audience declarations, enabling better demographic targeting by AI assistants.

How AI assistants see you

Partial coverage

Only chatgpt answered (4 of 16 probes), below our threshold of 2 assistants and 4 answers, so we are not reporting a visibility score. Not reached: claude, perplexity, gemini.

We only report a visibility score when at least 2 assistants and 4 answers come back. This run did not reach that, so the gap is in our measurement, not a finding about your brand.

claude: 400 {"type":"error","error":{"type":"invalid_request_error","message":"Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits."},"request_id":"req_011CdYccT8isKynwQkbpMH9z"}
perplexity: HTTP 401
gemini: HTTP 429

This could not be fully measured on this run. Only chatgpt answered (4 of 16 probes), below our threshold of 2 assistants and 4 answers, so we are not reporting a visibility score. Not reached: claude, perplexity, gemini. To make this measurable, ensure coverage by multiple AI platforms.

What we could not check

Live Ads: The Meta Ad Library API did not return a usable response (token scope, rate limit, or upstream error).

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Every check, in full

AI Readiness

Dex

50/100

0 of 12 schema types present, llms.txt present

No Product schema — AI agents cannot parse your product data
No Organization schema — AI agents don't know who you are
No BreadcrumbList — AI agents can't understand your site hierarchy

Paste-ready fixes (12)

Product schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Your Product Name",
  "description": "Product description here",
  "image": "https://yoursite.com/product-image.jpg",
  "brand": { "@type": "Brand", "name": "Your Brand" },
  "offers": {
    "@type": "Offer",
    "price": "29.99",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "url": "https://yoursite.com/product"
  }
}
</script>

Organization schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company Name",
  "url": "https://yoursite.com",
  "logo": "https://yoursite.com/logo.png",
  "sameAs": ["https://twitter.com/yourhandle", "https://linkedin.com/company/yourcompany"]
}
</script>

WebSite schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Your Site Name",
  "url": "https://yoursite.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://yoursite.com/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>

BreadcrumbList schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://yoursite.com" },
    { "@type": "ListItem", "position": 2, "name": "Products", "item": "https://yoursite.com/products" }
  ]
}
</script>

FAQPage schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "Your question here?",
      "acceptedAnswer": { "@type": "Answer", "text": "Your answer here." }
    }
  ]
}
</script>

Review schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Review",
  "reviewRating": { "@type": "Rating", "ratingValue": "5", "bestRating": "5" },
  "author": { "@type": "Person", "name": "Customer Name" },
  "reviewBody": "Review text here"
}
</script>

AggregateRating schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Product Name",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.5",
    "reviewCount": "127"
  }
}
</script>

Offer schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Offer",
  "price": "29.99",
  "priceCurrency": "USD",
  "availability": "https://schema.org/InStock",
  "itemCondition": "https://schema.org/NewCondition"
}
</script>

Brand schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Brand",
  "name": "Your Brand Name",
  "logo": "https://yoursite.com/brand-logo.png"
}
</script>

LocalBusiness schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "Your Business",
  "address": { "@type": "PostalAddress", "streetAddress": "123 Main St", "addressLocality": "City", "addressRegion": "State", "postalCode": "12345" },
  "telephone": "+1-555-555-5555"
}
</script>

HowTo schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to do something",
  "step": [
    { "@type": "HowToStep", "name": "Step 1", "text": "Do this first" },
    { "@type": "HowToStep", "name": "Step 2", "text": "Then do this" }
  ]
}
</script>

Article schema

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Article Title",
  "author": { "@type": "Person", "name": "Author Name" },
  "datePublished": "2024-01-01",
  "image": "https://yoursite.com/article-image.jpg"
}
</script>

Tracking & Pixels
Dex
65/100
0 of 3 pixels visible in page source, 5 issues
This check reads static HTML only. A GTM container is present (GTM-TH8KRSBJ, gtm-suite). A consent platform is present (OneTrust). Server-side tagging signals are present (Segment / CDP loader; Shopify Web Pixels (sandboxed); Elevar / Stape server-side). Any pixel not listed as detected may still be firing through one of those, so we have not scored it as missing.
- Meta Pixel not visible in static HTML
- Google Ads / GA4 not visible in static HTML
- TikTok Pixel not visible in static HTML
- Multiple GTM containers detected
- No tracking pixels detected on page
Catalogue
Parker
291 products, 2829 variants, 250 collections
Listed price range 3 to 160, median 91 (store currency)
- 1 products have a description under 100 characters. That is below what agent product matching needs to disambiguate a SKU.
- 137 of 291 product listings (47%) cannot be bought in any size or variant, yet they are still published and crawlable. An assistant that recommends one sends the shopper to a dead end.
- 57% of variants carry a compare-at price, so most of the catalogue reads as permanently discounted.
Landing Page
Dex
88/100
2 h1, 1 calls to action, 1 trust signals
The screenshot service could not load this page (the site refuses automated browsers). HTML-level findings below are unaffected.
- 2 <h1> elements. Multiple top-level headings dilute what the page is about.
- 3 of 43 images have no alt text.
Live Ads
Maya
Not measured
The Meta Ad Library API did not return a usable response (token scope, rate limit, or upstream error).
AI Visibility
Maya
Partial coverage
Only chatgpt answered (4 of 16 probes), below our threshold of 2 assistants and 4 answers, so we are not reporting a visibility score. Not reached: claude, perplexity, gemini.
We only report a visibility score when at least 2 assistants and 4 answers come back. This run did not reach that, so the gap is in our measurement, not a finding about your brand.
- claude: 400 {"type":"error","error":{"type":"invalid_request_error","message":"Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits."},"request_id":"req_011CdYccT8isKynwQkbpMH9z"}
- perplexity: HTTP 401
- gemini: HTTP 429
The 4 questions we asked
- “What are the best wool sneakers?”
- “Best sneakers for everyday wear”
- “Which brands make carbon neutral sneakers?”
- “Best sneakers for hot weather”
These questions were built from your own catalogue: product types, product titles, tags and your median price. None of them name your brand, so a mention means an assistant surfaced you unprompted.
Also recommended: Giesswein Merino Runners, Baabuk Urban Wooler, Nike Air Max 270, Adidas Ultraboost, New Balance 990v5, Vans Old Skool
- Only chatgpt answered (4 of 16 probes), below our threshold of 2 assistants and 4 answers, so we are not reporting a visibility score. Not reached: claude, perplexity, gemini.
- Allbirds did appear in 4 of the 4 answers we did get, so it is not invisible; we just cannot score it from this run.
- claude could not be queried (400 {"type":"error","error":{"type":"invalid_request_error","message":"Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits."},"request_id":"req_011CdYccT8isKynwQkbpMH9z"}), so it is excluded from the measurement rather than counted as a miss.
- perplexity could not be queried (HTTP 401), so it is excluded from the measurement rather than counted as a miss.
- gemini could not be queried (HTTP 429), so it is excluded from the measurement rather than counted as a miss.
- Your site never states who your products are for. We found no audience declaration in your title, meta description, og:description or structured data. Assistants cannot match you to demographic queries like "best face moisturizer for men", which are among the most common shopping questions in personal care and apparel.

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This report contains no revenue forecast, no spend recommendation and no dollar projection.

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Allbirds

What we measured

The headline

What is costing you right now

Fix this week

Fix this quarter

How AI assistants see you

What we could not check

Every check, in full

AI Readiness

Tracking & Pixels

Catalogue

Landing Page

Live Ads

AI Visibility