Service
Ecommerce GEO that helps AI describe and recommend your products correctly
Shoppers now ask AI tools what to buy. We make your product pages, structured data and feeds clear, consistent and true, so engines can use them.
Works on Shopify, WooCommerce, custom and headless stores. No promise of recommendations or sales.
| Prompt | Engine | Visibility | Status |
|---|---|---|---|
| best standing desk under 500 |  ChatGPT | 69% | Cited |
| which brand makes the best water bottle |  Perplexity | 54% | Mentioned |
| is it worth buying direct from the brand |  Google AI Overviews | 36% | Mentioned |
| gift ideas for a new home | Google AI Mode | 61% | Cited |
| compare two top rated air fryers |  Gemini | 45% | Mentioned |
| does this store offer free returns | ChatGPT | 27% | Not shown |
A shopper may ask for the best running shoes for flat feet under a set budget, or a gift for a coffee lover. The engine looks for products that fit, checks details such as price and availability, and may compare options. Stores with complete, consistent product data are easier to include.
No one can promise that a product will be recommended. What a store controls is the quality and accuracy of its own data and pages, and that is where we work.
Why it is different
Product questions need facts, not slogans
A product page written for a browsing visitor leans on photos and a short line of copy. An AI engine needs to know the exact name, brand, size, material, price, stock, delivery time and return terms. If those are missing or hidden in images, the engine either skips the product or fills the gap from another site.
Shoppers also ask comparison and use case questions. Which one is best for small flats. What is the difference between these two models. Is it safe for kids. A product page that answers these in plain text is more useful to the engine and to the shopper.
Category pages, buying guides and policy pages matter as well. They give the engine the wider context it needs to explain why one product suits one person.
- Product facts in text, not only in images
- Use case and comparison answers on the page
- Shipping and returns easy to find and consistent
Open a top product page and ask: could a stranger describe this item correctly, using only the words on the page?
- Shoes that suit flat feet
- Price and stock for each option
- Return terms and delivery
- Differences between two models
Scope
What we work on in a store
We implement the fixes ourselves on your platform, with your approval.
Product page content
Clear titles, plain descriptions, specification tables, sizing, compatibility, and honest answers to common buyer questions.
Product structured data
schema.org Product markup with price, availability, brand, identifiers, reviews where real, and shipping and return details, matching what the page shows.
Product feeds
Review of the data you send to Google Merchant Center and, where relevant, to other channels, checking it matches your site.
Category and guide pages
Category pages and buying guides written to answer the questions shoppers ask before they pick a product.
Policies and trust
Returns, shipping, warranty, contact and company pages that are complete and easy for a crawler to read.
Crawler access
Robots rules and rendering checks so AI crawlers can reach products, not just the home page. See technical GEO.
Structured data
What Google documents about product markup
This is from Google Search Central, as read in October 2026.
Google separates two uses of Product markup. Product snippets are for pages where people cannot buy the product directly, such as reviews. Merchant listings are for pages where customers can buy, and they support details like shipping and return policy. Meeting the merchant listing requirements can also make a page eligible for product snippets.
Google also says you can provide product data through structured data on your pages, through a Merchant Center feed, or both. It states that providing both maximizes eligibility and helps Google verify the data. Markup does not guarantee any feature. Rules and features change, so we check the current documentation at the start of every engagement.
- Markup describes what the page really shows
- Variants grouped under a parent product
- Return and shipping details marked up where they apply
{ "@type": "LocalBusiness", "name": "Your brand", "areaServed": "Dubai", "sameAs": [ "linkedin.com/..." ] }
- ValidMatches visible page text
- ValidSame name on profiles
- CheckOpening hours missing
Feeds
Product feeds for ChatGPT: what OpenAI documents
This is from OpenAI's product feed documentation, as read in October 2026. It is an evolving area.
OpenAI documents a product feed specification for merchants who want product data discovered in ChatGPT. Its stable path is file upload. For the OpenAI format, the documentation lists nine required fields: item id, title, description, url, brand, seller name, image url, availability and price. It also describes a Google compatible format that is available only after OpenAI confirms it for a registered feed.
The documentation states that eligibility does not guarantee display, and that checkout and ads have separate requirements. Market targeting defaults to the US unless OpenAI confirms additional markets, which matters if you sell in the UAE or UK. It also says to update price and availability when they change.
We help you prepare clean feed data and check it against the page. Whether you can use these programs depends on OpenAI's current terms for your country and business. We do not control approval, and the details may have changed since this page was written.
- Feed price and stock match the visible page
- Brand and identifiers complete
- Current program terms checked for your market
Record what AI engines say today.
Open access and repair the foundation.
Make priority pages answer ready.
Test again and report.
Compare
Product page: weak versus answer ready
| Weak product page | Answer ready product page | |
|---|---|---|
| Title | Brand name and code only | Product type, key feature, brand, model |
| Description | Marketing line and a mood photo | Plain summary, who it is for, what it does |
| Specifications | Inside an image | Text table of size, material, compatibility |
| Questions | None | Short FAQ on fit, care, delivery and returns |
| Data | Markup missing or out of date | Markup and feed agree with the page |
Ten well built product and category pages usually do more than a hundred thin ones.
Reviews
Reviews, ratings and honesty
Reviews are strong evidence for shoppers and engines alike, but only real ones help. We do not write, buy or filter reviews. Markup for ratings should reflect genuine reviews that visitors can see on the page.
We look at where your reviews live: on site, on a review platform, or in a marketplace. We make sure your own pages show the review content that supports each product claim, and that the aggregate rating matches the number of reviews shown.
If a product has few reviews, we do not hide that. We help you ask customers for honest feedback after purchase, within platform rules.
- Rating markup only where reviews are real and visible
- Review numbers consistent across site and feed
- Honest requests to real customers
Delivery
How ecommerce GEO runs in the GEO Pilot
- 1
Week 1: baseline and audit
We test up to 20 shopper prompts across five AI engines, check AI crawler access, and audit product pages, markup and feeds.
- 2
Week 2: technical fixes
We implement crawler rules, sitemap, canonicals and structured data on your platform: Shopify, WooCommerce, custom or headless.
- 3
Week 3: priority pages
We rewrite and restructure up to 10 priority pages, such as top products, categories and a policy page, to be answer ready.
- 4
Week 4: retest and roadmap
We run the same prompts again and deliver a before and after report with a 90 day roadmap. A new store build is not included.
Shopper prompts
What shoppers actually ask AI tools, and which page answers
Shopper prompts fall into a few families, and each is answered by a different page. A discovery prompt such as a gift for a coffee lover under a stated budget is answered by a category page or a gift guide. A comparison prompt such as the difference between two models is answered by a comparison page or the product pages themselves. A fit prompt such as a mattress for back pain or shoes for flat feet needs honest guidance with limits. A policy prompt such as whether a store ships to the UAE or how returns work is answered by policy pages. A trust prompt such as whether a store is legitimate is answered by about, contact and review pages.
Our method is to write the real prompts for your catalog first. We sort them into these families, find which page should answer each, and check whether it does. Gaps become the rewrite list. Our guide on researching buyer prompts shows the process, and the source selection article explains how engines pick what to quote.
The retrieval step matters here. When an engine searches the web on a shopper's behalf, it may issue several related searches, a pattern Google calls query fan out in its AI features guidance. A product page that answers only one narrow phrase misses the others. A category page with criteria, a comparison table and a short FAQ matches more of them. Read query fan out explained for the idea.
- Shopper prompts grouped by family
- One page named as the answer for each family
- Gaps listed as a rewrite plan
- Policy answers verified for each market
- DiscoveryCategory page or gift guide
- ComparisonComparison page or product pages
- FitHonest guidance with limits
- PolicyShipping and returns pages
- TrustAbout, contact and review pages
Policies
Shipping, returns and price: make them machine readable and true
Google documents merchant listing details including shipping and return policy, as read in October 2026.
Google's merchant listing documentation says return and shipping details are part of what a purchasable product page can supply, through structured data or a Merchant Center feed. The practical lesson is that policy must be both written for people and consistent with data. If your page says free returns within 30 days and your feed says 14, an engine may quote either. We list every policy fact with its source page, feed field and markup field, then make them agree.
Price is the most fragile fact. Sales, tax display, currency and market specific pricing create many versions. We check that the number a shopper sees at the top of the page is the number in markup and in the feed, and that it updates when a sale ends. OpenAI's product feed documentation also tells merchants to update price and availability when they change.
Availability by country needs special care for the UAE, USA and UK. Say plainly where you ship, how long it takes and what it costs. Do not leave engines to guess.
- Policy facts listed with page, feed and markup source
- Sale prices end on time in all three places
- Shipping countries stated in text
- Return window identical everywhere
{ "@type": "LocalBusiness", "name": "Your brand", "areaServed": "Dubai", "sameAs": [ "linkedin.com/..." ] }
- ValidMatches visible page text
- ValidSame name on profiles
- CheckOpening hours missing
Make them machine readable and true
- ✓Price matches in page, markup and feed
- ✓Sale price ends on time in all three
- ✓Shipping countries stated in text
- ✓Return window identical everywhere
- Policy hidden behind a vague footer link
- Specifications only inside an image
Compare
What changes by platform
| Platform | Where product data lives | Where we usually make GEO fixes |
|---|---|---|
 Shopify | Product fields, metafields and theme Liquid | Theme snippets, collection descriptions, robots.txt.liquid when needed. See GEO for Shopify |
 WooCommerce | WordPress products, attributes and plugin settings | Theme templates, schema filters, category descriptions. See GEO for WooCommerce |
| Custom or headless | Database or headless commerce API | Front end components, rendering mode, JSON LD built from product data. See GEO for custom websites |
The principles are the same everywhere. The place where the edit happens changes.
Run it today
An ecommerce AI search checklist you can run in an afternoon
- 1
Pick your five best sellers
These are the products worth fixing first.
- 2
Read each page as a stranger
Could someone name, size, price and describe the item correctly from the text alone? Mark any missing fact.
- 3
Compare page, markup and feed
For each product, check title, price, availability and brand in three places.
- 4
Check category pages
Does each one have an introduction, buying criteria and answers to questions? If it is only a grid, add them.
- 5
Read your policies
Shipping, returns and contact must be easy to find and consistent.
- 6
Run ten shopper prompts
Test in three engines. Note whether you, a marketplace or a review site is named, and what facts they use.
Worked example
Example, hypothetical: a UK coffee equipment store
Imagine a UK online store selling espresso machines and grinders. Shoppers ask for a good espresso machine for a small kitchen under a stated budget. The store is not named. This is an invented scenario to show the order of work, not a result.
In week 1 we find that machine dimensions and boiler type are only in images, category pages have no text, and the feed shows a sale price that ended last month. In week 2 we correct the data flow so price in page, markup and feed come from the same source, and we fix crawler rules that block a bot the owner wants. In week 3 we rewrite the espresso machine category page with criteria such as size, boiler type, ease of cleaning and budget bands, and four hero machine pages with text spec tables and honest limits, such as which models suit beginners and which need a separate grinder. In week 4 we rerun the prompts and report what changed.
The problem
Common ecommerce mistakes and how we fix each
Specs only in images
A size chart or ingredient list inside a picture cannot be read by a simple crawler. We rebuild it as a text table and keep the image as support.
Titles written as codes
A title like Model X2 Black tells an engine little. We write product type, key feature, brand and model in plain words.
Feed and page disagree
Price or stock differs between sources, so an engine may quote the wrong one. We trace each field to one source of truth.
Thin category pages
A grid has nothing to summarize. We add criteria, comparisons and answers.
Copied manufacturer text
The same description appears on many sites, giving an engine no reason to prefer yours. We add your own facts, tests and guidance.
Hidden policies
Shipping and returns sit behind a footer link with vague wording. We make them clear and findable.
Fixes by effort and effect
Context
Marketplaces, review sites and your own store
Shoppers often meet your products on marketplaces and review sites before your own site, and AI engines may cite those pages instead. This is not a reason to ignore your site. It is a reason to make your own pages the most complete, accurate and well structured source for your products. Include facts the marketplace lacks: sizing detail, compatibility, care, tests, honest limits and policies.
Reviews on other platforms are outside the Pilot, which does not include digital PR. We can point out where your brand is described wrongly on a third party page and suggest how to correct it. Read brand mentions versus citations for how to think about these sources.
Limits
What we cannot promise
We cannot make an engine recommend a product, and we cannot control prices, stock or competitors. Marketplaces and large retailers often have far more data and reviews. Some AI shopping features are limited to certain countries and may not be open to every store.
The Pilot covers one domain and one language. It does not cover paid media, link building or a store rebuild. Ongoing catalogue work is quoted.
For platform detail see GEO for Shopify and GEO for WooCommerce. For the base method see generative engine optimization.
FAQ
Questions people ask
Can you get our products recommended by ChatGPT?
We cannot promise that. We improve what you control: product content, structured data, feeds and crawler access. Then we test shopper prompts before and after so you can see what changed.
Do we need a product feed for AI shopping?
Not always. Google says structured data, a Merchant Center feed, or both can be used, and that both maximize eligibility. OpenAI documents a separate feed specification. We check which programs apply to your market.
Does product schema guarantee we appear in AI answers?
No. Markup helps machines read your page. Google states that eligibility depends on requirements being met, and no markup guarantees a feature.
Which platforms do you work with?
Shopify, WooCommerce, custom code and headless stores. You give access through an admin login, staging or a Git repo and approve changes.
How many products can the Pilot cover?
The Pilot rewrites and restructures up to 10 priority pages. Structured data and feed fixes can often apply to templates, so they reach many products at once. We scope this at the start.
Do you sell in the UAE, USA and UK?
We serve clients outside India, mainly in those three markets. Some shopping programs differ by country, so we check availability for yours.
Will you write fake reviews or buy mentions?
No. We only support real reviews and earned mentions.
What does it cost?
The GEO Pilot is $999, fixed, one time, delivered inside 30 days. Ongoing work after that is quoted.
How do shoppers use AI to find products?
They describe a need, a budget or a comparison in full sentences. The engine searches, collects product details from pages and feeds, and writes a short answer. Pages with complete, consistent facts are easier to use.
Should my policies be in the product feed or on the page?
Both, and they must match. Google says return and shipping details can be supplied by markup or a feed. Shoppers read the page, so clear text is essential.
Keep reading
Guides on this topic
AI search traffic in Google Analytics: how to track ChatGPT and AI referrals in GA4
GA4 can show some visits from ChatGPT and other AI tools, but not all. This guide explains how channels and referrers work, how to set up a report, and where the data stops.
Read moreAI visibility metrics: citation share, share of voice and mention rate defined
Mention rate, citation rate, citation share and AI share of voice are often used loosely. This guide defines each one, shows how to compute it from a fixed prompt set, and explains the limits.
Read moreHow to get mentioned in ChatGPT: what to do, what to skip
No one can guarantee a ChatGPT mention, but you can remove blockers, make your facts clear and earn the sources it reads. A practical, honest checklist.
Read more- GEO services
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Start your GEO Pilot
Tell us your website and the five questions your buyers ask. We reply within one working day with a clear next step.
- Fixed $999, one time
- We implement the work for you
- Any platform, delivered in 30 days