For Squarespace
Can AI shopping assistants find your Squarespace store?
ChatGPT, Perplexity, Claude, and Gemini recommend products now. This page covers what they read on a Squarespace store and where most stores fall short.
Last updated 2026-06-02
Score your Squarespace store →Shoppers have started asking AI which product to buy. 41% of US shoppers now use AI assistants to research what they buy, according to the IBM and NRF study from January 2026. When ChatGPT or Perplexity answers one of those questions, it names specific stores. A lot of those stores run on Squarespace, and their owners are now finding out whether an assistant can actually read them.
Here is the part that surprises people. The product pages are usually in good shape. Of the 14 Squarespace stores we scanned, 13 carried Product structured data an assistant can read, and 13 named a brand in it. For the stores we scanned, the product page was rarely the weak point. What trips these stores up sits next to it, in the trust signals a shopper and an assistant both look for: a shipping policy, a returns policy, and a clear way to make contact.
What AI actually sees on a Squarespace store
The Squarespace stores we scanned were not invisible to AI. Of the 14 we scanned in 2026, 13 carried Product structured data an assistant could read, and 13 named a brand inside it. The product layer was the strong part of nearly every store in the sample.
The common gap was trust. 7 of the 14 stores were weakest on trust signals: a shipping policy, a returns policy, and a contact path an assistant can find. A separate, smaller fix is product codes, since none of the 14 stores carried a GTIN. The product page is rarely the problem. The pages around it are.
Where Squarespace stores lose points
Missing trust signals: shipping, returns, contact
This was the single most common weak spot. Of the 14 Squarespace stores we scanned, 7 were weakest on trust signals: a clear shipping policy, a clear returns policy, and a way to make contact. These are pages a merchant publishes, and most of the stores we scanned simply had not published them yet. Before an assistant puts your store in front of a shopper, it checks that you are a real, safe place to buy from. With no shipping terms, no returns terms, and no contact path, it has little to go on.
No clear business identity or contact path
An assistant wants to know who you are, not just what you sell. A homepage that states the business name, what it sells, and how to reach you helps the AI connect your products to a real seller. Entity and brand identity was among the weaker dimensions in the sample, even on stores whose product page already named a brand. Stating who you are and how to reach you, in plain words on the homepage, pulls the whole score up.
Product codes are the one thing missing
The product markup was the strong part of the sample. Of the 14 stores we scanned, 13 carried a brand an assistant can match against a catalog. The one piece that was consistently absent was a product code: none of the 14 stores carried a GTIN. A brand plus a code like a GTIN, UPC, or MPN lets an assistant tie your product to a real catalog entry. This is a secondary fix, smaller than the trust gap, but worth doing once the policies are in place.
The trust gap: strong product pages, missing policies
On Squarespace, the question is rarely whether your product page can be read. In the stores we scanned, the product markup was usually solid. What was missing sat next to it: the trust pages a shopper and an assistant both look for before deciding your store is a safe place to buy. There are three the check looks for, and all three are pages you publish yourself. If you want the plain-language background, see what AEO means.
A page that says where you ship, how long it takes, and what it costs. Publish it as a page and link it in the footer so an assistant can find it from anywhere on the site.
A page that spells out your window, the condition you accept items in, and who pays return shipping. A clear returns page is one of the strongest trust signals you can publish.
A visible way to reach you: a contact page, an email, or a form. An assistant treats a reachable seller as a real one. Link it in the header or footer so it is easy to find.
This is the gap we measured across real Squarespace stores. Of the 14 stores we scanned, 13 carried Product structured data, so the product page was rarely the issue. But 7 of the 14 were weakest on trust signals. Publishing the three pages above and linking them clearly is the highest-impact thing most of these stores can do.
Based on the checks we ran across real Squarespace stores. Run the free check to see your own.
How to close the gap
Publish a shipping policy
Add a page that says where you ship, how long it takes, and what it costs, then link it in your footer. This was part of the most common weak spot across the stores we scanned, and it is one of the first things an assistant checks.
Publish a returns policy
Add a page that spells out your returns window, the condition you accept items in, and who pays return shipping. A clear returns page is one of the strongest trust signals you can give a shopper and an assistant.
Add a contact page or email
Make sure there is a visible way to reach you, a contact page, an email, or a form, linked in the header or footer. A reachable seller reads as a real one, and it is part of the trust layer an assistant checks.
Add a product code to each product
A smaller, secondary fix once the policies are in place. Fill in a code like a GTIN, UPC, or MPN on each product. Across the 14 stores we scanned, none carried a GTIN, and adding one lets an assistant tie your product to a real catalog entry.
What we found across real Squarespace stores
of the 14 Squarespace stores we scanned emitted Product structured data an assistant can read. In this sample, the product page was not the blocker.
Squarespace stores we scanned, 2026
of the 14 were weakest on trust signals: a shipping policy, a returns policy, and a contact path. That is the most common gap.
Squarespace stores we scanned, 2026
median AI-visibility score out of 100. The product layer is strong; trust signals are what hold most stores back.
Squarespace stores we scanned, 2026
One anonymized store from that scan. The trust pages are the gap; the product page itself is already strong:
Questions
Is Squarespace bad for AI or SEO?
- No. Of the 14 Squarespace stores we scanned, 13 carried Product structured data an assistant can read, and 13 named a brand in it. The product pages were the strong part of nearly every store. What holds most stores back is trust signals, not the platform.
What trust pages do AI assistants check?
- Three in particular: a shipping policy, a returns policy, and a clear contact path. Before an assistant recommends a store, it looks for proof you are a real, safe place to buy from. Publishing those three pages and linking them in the footer is the highest-impact thing most Squarespace stores can do.
Does Squarespace support policy and contact pages?
- Yes. These are standard pages you publish and link yourself. In the stores we scanned, the gap was that the pages had not been published, so adding them and linking them in the header or footer is the highest-impact fix.
Why is my product schema fine but my score low?
- Because the score weighs more than the product page. In our sample the product markup was usually strong, but 7 of the 14 stores were weakest on trust signals, and none carried a product code like a GTIN. Add the shipping, returns, and contact pages first, then a product code on each item, and the score moves.
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Score your Squarespace store →See exactly how we score, on the methodology page, or compare AI visibility across platforms.