Product Radar — products ChatGPT recommends

ChatGPT increasingly answers shopping-flavored questions with product cards: concrete products, brands, and prices. Product Radar collects every product that surfaced in answers to your tracked prompts, so you can see what the assistant actually sells against your category.

What you see

• KPI cards: products surfaced in ChatGPT answers, unique brands detected, and how many of your tracked prompts produced product results.
• Top brands — who dominates the product recommendations in your prompt set.
• Each product entry shows the brand, product, price as surfaced, and the exact prompt that triggered it — so you can reproduce the answer yourself.
• Search across brands, products, or prompts.

How to use it

1. Check presence. Are your products ever in the cards? If competitors appear and you don't, that's a merchandising-level visibility gap — often a feed or product-data problem rather than a content problem.
2. Check framing. When you do appear: at what price, against whom? Assistants sometimes surface outdated prices or old SKUs — stale product data in public sources shows up here first.
3. Mine the prompts. The triggering prompts tell you which phrasings put ChatGPT into shopping mode for your category. Track more of those in Prompt Lab if commerce matters to you.

Making your products eligible

Product surfacing draws heavily on structured product data. Two Maya tools help:

• Feed Audit (Technical) checks your product feed against the OpenAI Product Feed Spec and flags missing LLM-optimized titles and descriptions.
• Page Audit checks whether product pages are readable to AI crawlers at all.

Notes

• The page fills automatically as ChatGPT surfaces products in your tracked answers — there is nothing to configure.
• A quiet Product Radar can be normal: not every category triggers product cards. Test with explicitly transactional prompts before concluding anything.