How to get your products recommended by ChatGPT and AI shopping assistants

AI shopping assistants recommend products whose data answers the shopper's question. When someone asks ChatGPT, Gemini, Copilot or Google AI Mode for "a wide-fit waterproof hiking boot under $150", the assistant looks for products where width, waterproofing and price are clearly stated. A great product with a vague description loses to an average one with complete details.

Why AI assistants skip good products

• Missing attributes. Your page says "comfortable boot" but never states the width fitting or waterproof rating.
• Inconsistent values. "Blk", "Jet black" and "Black" across variants look like different things.
• Facts hidden in images. Sizing charts and specs inside pictures are hard for crawlers to read.
• No compatibility or use-case data. Shoppers ask what a product fits, who it is for and what it solves.
• Thin trust signals. Few reviews, unclear returns or shipping, and no third-party mentions.

Step 1: fill the attribute gaps

List the 10 to 20 questions shoppers ask in your category, then check how many of your products answer each one. Typical attributes to add:

Put these in your product fields, tags and metafields, not only in the description. Standardise values so every product uses the same words.

Step 2: write product pages that answer questions

• Lead with a one-sentence summary of who the product is for and what it solves.
• Add a short spec table in HTML text: materials, dimensions, compatibility, care.
• Include an FAQ with real questions from customers and support emails.
• Keep titles descriptive: brand, product type, key attribute, variant.

Our product description generator gives you a structured first draft to edit.

Step 3: structured data and product feeds

• Add Product structured data (name, price, availability, brand, GTIN, reviews) that matches what is visible on the page.
• Keep an accurate Google Merchant Center feed. Google lists Merchant Center among the ways to be eligible for richer shopping results in its AI features.
• Fill optional feed fields such as product highlights, material, size and age group; they are extra attributes for matching.
• Check whether your ecommerce platform offers channels that send your catalog to AI shopping assistants, and keep that data in sync with your store.

Step 4: make sure AI can reach your store

Allow AI search crawlers such as OAI-SearchBot, PerplexityBot and Claude-SearchBot in robots.txt, and check that firewall "bot protection" is not blocking them. Our guide to AI crawlers and robots.txt has a ready-made setup.

Step 5: test and track

Run 15 to 20 shopper-style prompts in each assistant, record whether your products appear, and repeat monthly. The full method is in how to check if ChatGPT recommends your brand. Watch revenue too: traffic from AI is only worth chasing if those orders are profitable, so check your margin with the profit margin calculator.

If you run a Shopify store and want to see which shopper questions your catalog cannot answer, ReLUnit offers a free AI-readiness audit. Disclosure: ReLUnit sponsors Trendifico.

FAQ

Can I pay ChatGPT to recommend my products?

Organic recommendations are not for sale. Where ads exist they are labelled separately. Complete, accurate product data is what gets organic recommendations.

Do I need a special file for AI shopping assistants?

Not for Google: it says no special AI files are needed. A good Merchant Center feed and Product structured data cover most needs.

How long does it take to show up?

It depends on how quickly assistants recrawl your pages and feeds. Expect weeks rather than days, and test monthly.

Which attributes matter most?

The ones shoppers put in their questions: fit, compatibility, use case, material, size and price. Start with the attributes that appear in your customer emails and site search.