Google’s New Store_address Attribute Now Required for Local Ads

Google's New Store_address Attribute Now Required for Local Ads

TL;DR Summary:

New Google Requirement: Google Merchant Center now requires the store_address attribute for products in Local inventory ads and Local free listings.

Format Addresses Correctly: Use standard ASCII characters for each physical store address to prevent feed submission failures and listing errors.

Audit Every Location: Missing or inaccurate addresses can break product-to-store links and lead to rejected or removed listings, especially for multi-location retailers.

Do you need to update your product feed for Google Shopping? Google Merchant Center added a new store_address attribute on October 14, 2026, and it’s now required for products submitted to Local inventory ads and Local free listings. If you sell through either of these local shopping tools, this change affects your feed right away.

What the Store_address Attribute Does

The store_address attribute identifies the physical store linked to a product in your feed. Google uses it to standardize location data across local shopping listings. Before this update, merchants had other ways to connect products to store locations. Now Google requires this specific attribute for any submission tied to Local inventory ads or Local free listings.

How to Format the Store_address Attribute Correctly

Google defines the store_address attribute as a string using Unicode characters, a standard way of encoding text so different systems can read it the same way. Your actual address text needs ASCII encoding, which covers standard letters, numbers, and basic punctuation. If you enter special characters or formatting outside this standard, your submission can fail. Check your feed now and confirm each address matches this format before you submit.

Who Must Add the Store_address Attribute

This requirement applies to two groups. First, merchants running Local inventory ads, which are paid listings showing products available at nearby physical stores. Second, merchants using Local free listings, which are unpaid listings that let shoppers find in-store products without an ad spend. If you use either program, you need the store_address attribute on every applicable product submission. There’s no exception based on store size or number of locations.

Risks of Skipping the Store_address Attribute

Missing or incorrectly formatted store_address data creates two problems. First, it breaks the link between your product and the correct store, called product-to-store association. Second, it puts your feed out of compliance with Google’s requirements, which can cause listings to get rejected or removed. If you manage inventory across multiple store locations, these errors multiply fast. A feed with ten locations and incomplete address data risks ten separate points of failure. This is much like how technical SEO problems often go unnoticed until they quietly erode rankings or visibility, which is why tools like Labrika are useful for catching these compliance-breaking errors before they snowball into lost listings or lost traffic.

Reviewing Your Feed for the Store_address Attribute

Google published full documentation for the store_address attribute through its Merchant Center support page. If you run Local inventory ads or Local free listings, go through your feed line by line and confirm every product submission includes a correctly formatted address. Pay close attention to multi-location retailers, since each store needs its own accurate address tied to the right products.

Check your Merchant Center feed this week if you use Local inventory ads or Local free listings. Confirm every product submission includes a properly formatted store_address attribute, especially if you manage more than one store location. Watch for rejected listings or feed errors, since these often signal a missing or incorrectly formatted address. While you’re auditing your feed for formatting issues, it’s worth running a broader technical check too — Labrika’s site audit tool scans for over 200 ranking factors and flags hidden errors like indexing gaps before they cost you traffic.


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