# AEO for ecommerce: get your products into AI shopping answers

> In short: Shopping answers draw on three things: structured product data (Google Merchant Center, and OpenAI's product feeds for approved merchants), your product and category pages, and the reviews and roundups that compare products. Keep the feeds accurate and current, make product pages state who each product is for in plain words, and earn places on the guides assistants cite for your category.

Guide from Keats, published 2026-11-13, updated 2026-11-13. Canonical: https://getkeats.com/guides/aeo-for-ecommerce

"What's a good waterproof hiking boot under a reasonable budget for wide feet?" Buyers ask assistants questions like that now, and the answers name products, show prices and link to stores. For an online store, AEO is getting your products into those answers, with the right facts attached.

## Where shopping answers come from

Three sources feed most shopping answers:

1. **Structured product data.** Google says Merchant Center feeds and Google Business Profiles "can help your products and services to be visible in both AI responses and other Google Search results". OpenAI runs product feeds for ChatGPT too: its commerce docs say feeds give ChatGPT what it needs to "present accurate product information in shopping experiences", and that onboarding is "currently available to approved partners", with applications at chatgpt.com/merchants.
2. **Product and category pages.** When an assistant looks a product up, it reads the store's pages, and those of other stores selling it.
3. **Comparisons and reviews.** For "which is best for me" questions, assistants lean on buying guides, review sites, forums and videos.

## Step 1: get the product data right

- **Google Merchant Center.** Submit a complete, current feed: titles that say what the product is, accurate prices and stock, the attributes people filter by (size, material, colour, compatibility), good images. Fix disapprovals promptly.
- **OpenAI's product feeds.** If you sell at volume, apply at chatgpt.com/merchants. OpenAI's docs ask approved merchants to send a full catalog snapshot at least once a day and to follow its prohibited products policy.
- **Product structured data.** Product and Offer markup on each product page, matching the visible price and availability. Google says structured data isn't required for its AI features, but it powers rich results, and mismatched markup is a wrong fact stated twice.

## Step 2: write product pages for the question, not the catalog

Most product pages are written for someone who has already chosen the product. Shopping questions come from people who haven't. Add what they ask about:

- **Who it's for, in their words**: "for wide feet", "for beginners", "for small apartments".
- **The specifics that settle a choice**: dimensions, materials, compatibility, what's in the box, care.
- **Honest trade-offs**: "heavier than most trail runners", "runs half a size small". Specifics like these are what answers repeat, and they build trust with the reader too.
- **Facts in text, not images.** A size chart that exists only as a picture isn't readable.

Category pages deserve the same treatment: a short, plain introduction saying what's in the range and how to choose between them often gets quoted when an assistant explains the category.

## Step 3: reviews

Reviews do double duty: they're the specifics assistants repeat ("reviewers say it runs small") and the signal that a product is real and bought. Collect them after delivery, show them on the page in text, answer the critical ones, and never write, buy or gate them.

## Step 4: get into the buying guides

For "best X for Y" questions, assistants cite buying guides from publications and enthusiast sites, Reddit threads and YouTube reviews. Find the ones cited for your categories and earn a place: send the product to the reviewers who cover your niche, correct wrong facts, answer questions where buyers ask them. How to approach each kind of page is in [our roundups, Reddit and reviews guide](https://getkeats.com/guides/third-party-placements).

## Which questions to track

Shopping questions have many variants. Track the ones that match how your buyers choose:

| Type | Example |
|---|---|
| Category plus need | "best rain jacket for cycling commutes" |
| Budget | "good espresso machine for a beginner on a budget" |
| Comparison | "Brand A vs Brand B hiking boots" |
| Compatibility | "phone case that works with MagSafe for the latest model" |
| Your products by name | "is the [your product] waterproof?" |

Keep your brand out of the first four, so you're measuring whether you're recommended, not whether you're known. More on picking them in [which prompts to track](https://getkeats.com/guides/choose-questions-to-track).

## Measuring it

Track named (your store or brand appears), cited (a link to your pages) and, for shopping, which of your products appear. Watch the facts as well: a wrong price or stock status in an answer costs sales directly. Clicks from assistants show up in GA4 if you set up an AI channel, but many shoppers read the answer, then search for the product by name, so a rise in branded search can be the clearer signal.

## Doing the basics first

Before any of this, make sure the assistants' search crawlers can read your product pages and that key facts render in HTML. Many stores block bots at the CDN to stop scrapers, and that can catch AI search crawlers too. Then put the effort where the answers come from: accurate feeds, product pages that answer the buyer's question, and [answer-first writing](https://getkeats.com/guides/answer-first-content) on your category and guide pages.


## Your agent does this

Ask your agent: "For our top shopping questions, which products do the assistants name, from which pages, and which of our products are missing?" It reads `list_answers` and `list_citations` for each question and drafts the product-page changes and outreach notes.

## Sources

- [Google Search Central: Optimizing your website for generative AI features on Google Search](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide), read 2026-11-13
- [OpenAI: Commerce, get started with product feeds](https://developers.openai.com/commerce/guides/get-started), read 2026-11-13
- [Google Search Central: AI features and your website](https://developers.google.com/search/docs/appearance/ai-features), read 2026-11-13