Ad feed health
Google Shopping & Meta catalogs1 of 21 sampled products have an issue that gets items disapproved or throttled in Google Shopping — roughly 7 products across the 147.
Published audit · 16 October 2026
How Google Shopping and AI shopping agents read www.deathwishcoffee.com
We read Death Wish Coffee's storefront the way Google's crawler and agents like ChatGPT, Perplexity and Google AI Mode do — no login, no app install — and checked 21 flagship products of 147 against Merchant Center's rules and agent readability.
1 of 21 sampled products have an issue that gets items disapproved or throttled in Google Shopping — roughly 7 products across the 147.
7 of 21 are hard for AI shopping agents to read: key buying facts are missing or locked in prose and images — roughly 49 products catalog-wide.
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The lowest-scoring products from the sample, rebuilt into complete structured data, Shopify metafields and Google feed rows.
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What we found
Most severe first, with how many of the 21 sampled products each one affects.
Agents filter on facts ("merino, under 300g, machine-washable"). With none, the product can't match those queries.
How to fix Add the facts shoppers filter on — material, dimensions, weight, care — to the description and, better, to metafields published in the JSON-LD as additionalProperty.
Merchant Center rejects invalid GTINs ("Invalid value [gtin]"); the item is disapproved until fixed.
How to fix Correct the barcode in Shopify admin (product → variant → Barcode) to the 8-, 12-, 13- or 14-digit GTIN from the manufacturer or your GS1 record. If the product has no GTIN, clear the field rather than entering a SKU.
These are the attributes Google and AI agents filter on; they're absent from the machine-readable layer.
How to fix Publish color, material and pattern in the JSON-LD (the Product properties of the same names), filled from variant options or metafields.
Branded products without GTINs get "limited performance" in Shopping and can't be matched to the same product across sellers by agents.
How to fix Add the manufacturer's GTIN to each variant's Barcode field. For your own brand, license GTINs from GS1; for custom or handmade items without one, submit identifier_exists = no.
Facts exist in paragraphs but not as attributes; agents and feeds have to guess, and usually drop them.
How to fix Move specs out of paragraphs into product metafields and publish them as additionalProperty name/value pairs in the JSON-LD.
Google requires these for apparel in key markets (US, UK, DE, FR, JP, BR), and agents filter on them. If they only live in app metafields, no crawler or agent can see them.
How to fix Publish color and size as variant options, and gender and age group as product metafields that both your JSON-LD and your feed read (Shopify's Google & YouTube app uses the mm-google-shopping namespace).
Google shows shipping and returns annotations only when they're marked up; agents compare stores on exactly this.
How to fix Add hasMerchantReturnPolicy and shippingDetails to the Offers in your JSON-LD, or configure return and shipping policies in Merchant Center.
Feed titles that include brand, product type and key attribute get more impressions.
How to fix Lengthen the feed title to brand + product type + key attribute, e.g. "Acme Women's Merino Crew Sweater – Navy".
Crawlers and agents that don't run vision read nothing from the images.
How to fix Add alt text to product images in Shopify admin, describing the product, its color and the view.
Product by product
Scores out of 100, worst first. Open a product to see what's wrong with it.
Store-wide
Enter your store and get both scores, every issue, and your five worst products rebuilt from your own photos and copy — free, in about a minute.
Audit your store free →Everything here comes from public storefront data: /products.json, the storefront Ajax API, each product page's JSON-LD, robots.txt and policy pages. Checks follow Google Merchant Center's product data specification and schema.org's Product vocabulary — see every check. Attributes kept only in app metafields or a separate feed aren't visible publicly — for AI agents, that's the same as missing.
AI enrichment was not used for this report; the fixes shown are built deterministically from the store's Shopify data. Sample: 21 products — homepage picks first, then spread across product types. Generated 2026-10-16T09:05:22.569Z.