How to Get Your Products Recommended by ChatGPT and AI Search

Shoppers increasingly ask AI assistants questions such as “What is the best waterproof walking boot under £150?” or “Which standing desk is most stable for a tall person?”. The answer usually names specific products, with reasons. For ecommerce businesses, being part of that shortlist is becoming a meaningful source of discovery.

The short answer

AI assistants recommend products they can describe accurately and justify. That depends on complete, consistent product information that crawlers can read, genuine reviews, and independent content that compares or mentions your products. There is no shortcut, but most of the work also improves organic search and conversion rates.

Why product recommendations are different

Product questions are usually specific. They include constraints such as budget, size, use case or compatibility. Assistants therefore favour products whose details are explicit and easy to compare. A product page that simply says “premium quality boot” gives the system little to work with; one that lists waterproof rating, weight, sole type, sizes and price does.

1. Make product pages complete and readable

• Write unique descriptions that explain who the product is for and what problem it solves.
• List specifications as HTML text: dimensions, materials, compatibility, capacity, care instructions.
• Show price, stock status, delivery and returns information clearly on the page.
• Answer common pre-purchase questions in a short FAQ on the page.
• Avoid putting key details only in images, tabs that load via scripts, or PDFs.

2. Add accurate structured data

Product structured data using Schema.org vocabulary describes name, brand, price, availability, reviews and identifiers such as GTIN in a machine-readable format. Google's introduction to structured data explains how this helps systems understand page content. Keep it consistent with what is visible on the page.

3. Maintain a high-quality product feed

A well-maintained Google Merchant Center feed with accurate titles, attributes and identifiers supports Google Shopping and Google’s AI experiences. See Google Merchant Center Help for requirements. Other AI platforms are developing merchant programmes; review their current documentation before committing resources.

4. Allow the right crawlers

Check that robots.txt, CDN and bot-protection settings allow search crawlers, including OAI-SearchBot for ChatGPT search as described in OpenAI's crawler documentation. Aggressive bot blocking on ecommerce platforms sometimes stops legitimate crawlers.

5. Build genuine reviews

Reviews give assistants language to describe strengths and weaknesses. Collect them consistently after purchase, respond to criticism, and display them on product pages with review structured data where appropriate. Never incentivise or fabricate reviews; that breaches consumer protection rules and platform policies.

6. Earn independent mentions

Buying guides, comparison articles, specialist forums and trade publications are frequently cited in AI answers. Supplying review samples, accurate specifications and expert commentary to relevant publishers helps your products appear in those sources.

7. Use category and guide content wisely

Category pages that explain how to choose between options, and honest buying guides on your own site, help both shoppers and AI systems match products to needs. Link from guides to the relevant products.

Measuring progress

• Track referral sessions, revenue and conversion rate from AI assistant referrers in analytics.
• Monitor a set of product-led prompts monthly and note which products and sources are named.
• Watch Merchant Center diagnostics for feed errors that could limit visibility.

Our article on Google Search Console and AI search covers measurement in more detail.

A real example

F1 Authentics, a motorsport memorabilia retailer, saw a 238% increase in AI-driven sessions over six months following work on product content, technical SEO and structured data. The full detail is in our F1 Authentics case study.

Key takeaways

• Complete, specific product information is the foundation of AI product visibility.
• Structured data and a clean product feed help systems read your catalogue accurately.
• Genuine reviews and independent coverage give assistants reasons to recommend you.
• Measure AI referrals and track product prompts over time.

We build and optimise ecommerce websites with these principles in mind.

Frequently asked questions

Do I need a product feed for ChatGPT?

Requirements for shopping features in AI assistants are changing quickly. Keeping accurate, crawlable product pages with structured data and a well-maintained Google Merchant Center feed is a sound foundation. Check each platform's current merchant documentation before investing in a specific integration.

Which product details matter most?

The details buyers compare: price, availability, key specifications, dimensions, compatibility, materials, delivery and returns, plus genuine reviews. Present them as text and structured data rather than only in images.

Will AI shopping replace Google Shopping?

Not in the near term. Treat AI assistants as an additional discovery channel. The same product data quality that performs well in Google Shopping and organic search also supports AI visibility.

Want your products to be easier for AI assistants to recommend? If you would like an honest view of where you stand, talk to our team or read more about our AI SEO services.

Sources: OpenAI's crawler documentation; Google's introduction to structured data; Google Merchant Center Help.