google_product_category and product_type: Mapping Shopify Collections
How to map Shopify collections and product types to Google's taxonomy for cleaner Shopping categorization.
Written by Mantas Jurgutis — Founder, Adsify — builds the Google & Meta automation merchants use daily
Editorially reviewed by Adsify Editorial on July 21, 2026 — Reviewed against Shopify, Google Ads and Meta official documentation.
Two different category systems, easily confused
Google Shopping uses two separate category attributes: google_product_category, which must match a value from Google's fixed, official product taxonomy (a long standardized list like 'Apparel & Accessories > Clothing > Shirts & Tops'), and product_type, which is a free-text field you define yourself, usually mirroring your own Shopify collection or navigation structure. Confusing the two — putting your own Shopify collection name into google_product_category — causes the attribute to be rejected or ignored since it won't match anything in Google's taxonomy.
Where these map from in Shopify
Shopify's own Product category field (Products > [product] > Product organization > Product category) is Shopify's built-in attempt at Google-taxonomy alignment, and most feed apps read directly from it for google_product_category. Shopify's Type field, a separate free-text field in the same Organization section, commonly maps to product_type. Collections themselves (manual or automated groupings under Products > Collections) aren't a feed attribute at all by default, but many feed apps let you build custom_label or product_type values from collection membership through mapping rules.
Setting Shopify's Product category correctly
When you start typing in Shopify's Product category field, it offers an autocomplete search against Google's actual taxonomy tree, so use the most specific matching category available rather than a broad parent category — 'Apparel & Accessories > Clothing > Outerwear > Coats & Jackets' rather than stopping at 'Apparel & Accessories > Clothing.' A category that's too broad can reduce how often your listing surfaces for specific, high-intent searches, since Google weighs category specificity in matching.
Building product_type from your collection structure
product_type supports a hierarchy using a '>' separator, similar in style to Google's own taxonomy but entirely custom to you — for example, 'Home > Kitchen > Small Appliances > Blenders' can mirror your actual Shopify collection path even if that exact wording doesn't exist in Google's taxonomy. This is useful for campaign structuring, since Performance Max and standard Shopping campaigns can use product_type values in listing groups to segment budget and bidding by category without relying on Google's fixed taxonomy wording.
A worked example
A Shopify store sells ceramic mugs under the collection 'Kitchen > Drinkware.' The correct google_product_category, chosen from Google's taxonomy autocomplete, would be something like 'Home & Garden > Kitchen & Dining > Tableware > Drinkware.' The product_type field, left as free text, could simply mirror the Shopify collection path: 'Kitchen > Drinkware > Mugs.' These two values look similar but serve different systems — one must match Google's fixed list exactly, the other doesn't need to match anything except your own internal structure.
Auditing category coverage across a catalog
For catalogs where Product category was never filled in on older products, export via Products > Export, filter for blank Product category values, and work through them by collection since products in the same collection usually share the same correct taxonomy value — this is much faster than looking up each product individually, and paired with a well-structured product_type, gives you clean segmentation for both Shopping eligibility and campaign structure, including custom_label-based segmentation for bidding.