Getting a DTC Brand Ready for AI Shopping Agents

A DTC brand can get ready for AI shopping agents in this order.

1. Audit the AI channels the store is already in.
2. Fill in product data so an agent can compare products without guessing.
3. Publish return, shipping and support policies where agents and platforms can read them.
4. Add the optional attributes Google offers for conversational answers.
5. Check that structured data matches the page.
6. Measure monthly, by channel.

Each step below explains what to do in Shopify and Merchant Center, and what it does and does not achieve. Platform details are as of 20 October 2026.

What should a DTC brand do first to get ready for AI shopping agents?

A DTC brand should first find out which AI shopping channels it is already selling through, because Shopify turns Agentic Storefronts on by default for eligible stores.

Shopify's Agentic Storefronts are active by default for eligible stores across ChatGPT, Google AI Mode and Gemini, Microsoft Copilot and Meta. The settings sit under Sales channels, then Agentic, and a single product can be kept out by marking it unlisted.

Write down which channels are on, whether checkout inside the chat is allowed on Google, Copilot and Meta, and which products are excluded. In our estimate, this audit takes under an hour, and it prevents orders arriving from a channel nobody is tracking. The trade-offs of in-chat checkout are covered in agentic checkout, what DTC brands gain and lose.

Fill in the product data agents compare

The common thread across Shopify, Google and OpenAI is complete product data, because an agent can only compare what the catalog states.

The minimum is set by eligibility. To be listed in Shopify Catalog, a product must have a title, an image and a price and ship to the US or Canada, according to Shopify's agentic commerce guide, which also puts auditing and enriching product data first in its own steps.

The useful standard is higher. OpenAI's product feed specification requires nine fields, including brand, availability and price, and lists optional fields such as GTIN, color, size, material, shipping, return deadline, review count and star rating. It also states that eligibility does not guarantee display.

Shopify merchants do not need to build that feed, since Shopify Catalog supplies ChatGPT. The fields still show what an agent looks for, so use them as a checklist for Shopify product data.

• Write descriptions that state materials, fit, dimensions and use cases in plain words. Shopify's advice on agentic shopping starts with writing product descriptions for AI discovery.
• Fill variant attributes such as size and color consistently across products.
• Keep price and stock in sync with the store, since a recommendation for an out-of-stock item loses the sale.
• Add GTIN or MPN where products have them.

Publish policies agents can read

Return, shipping and support policies are required for some channels, not just helpful.

Shopify requires a store's terms of service, privacy policy and return and refund policy to be completed before it can sell on ChatGPT. For merchants integrating directly, Google's checkout requires return policies with cost, window and link, plus at least one customer support contact, in Merchant Center. Shopify merchants connect through Shopify, but the same policy details help.

Write policies as dedicated pages with clear headings and plain language, as Shopify's guide advises. An agent answering "can I return this if it does not fit" quotes whatever the page says.

Add Google's conversational attributes

Google offers optional attributes that help conversational answers, and they are low risk to add.

Merchant Center's conversational attributes include questions and answers, related products, item group titles and variant options. Google calls them completely optional, says they do not affect approval status, and recommends submitting them through a supplemental data source.

Start with questions and answers for hero products, using the questions customer service hears most. Do not repeat the product description in these fields, as Google asks.

Check structured data for accuracy

Google says there is no special schema.org structured data to add for AI Overviews or AI Mode, and no extra requirement beyond being indexed. Structured data still matters for accuracy, because Google asks that it match the visible text on the page.

Keep Product and Offer markup correct for price and availability, and consider a store-wide return policy under Organization markup. For return and shipping policies, settings in Merchant Center take precedence over on-page markup, so fix them there first when the two disagree.

Measure monthly by channel

Readiness only counts if it shows up in answers and orders. Search for your main products in ChatGPT, Google AI Mode, Gemini and Copilot the way a customer would, and record which products appear and what is said about them.

Read AI channel orders in the Shopify admin each month and compare them with the product data changes you made. Whether AI recommends Amazon over DTC brands covers how reviews and outside mentions also shape which products agents pick.

Frequently asked questions

Do we need an OpenAI product feed if we use Shopify?

No. Shopify Catalog supplies ChatGPT for eligible Shopify stores. OpenAI's feed specification is still a useful checklist for the fields an agent reads.

Will adding schema markup get our products into AI Overviews?

Schema alone will not do it. Google says no special schema is needed for AI features. Markup that matches the page keeps product details accurate across Google's surfaces.

How long does getting ready take?

In our estimate, the channel audit takes under an hour and policies a day or two. Product data work scales with the number of products, so most brands start with their best sellers and work outward.