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Product Details

The Product Details drawer is the full story behind a single product: how AI describes it, which shopping questions it shows up in, the exact conversations it was named in, and where AI says you can buy it.

If the Products page tells you which products need attention, the drawer tells you why — and usually what to do about it.

Opening the Drawer

The drawer opens for any product, from either place:

It slides in over the current view, so you keep your place in the list. Close it and you're back where you were, which makes it practical to work through several products in one sitting.

How AI Perceives the Product

The drawer opens with the perception of the product — the way answer engines characterize it in their own words.

Why this matters: your product page says one thing; AI may say another. Perception is what buyers actually hear. If AI describes your premium model as "the budget option," no amount of ad spend fixes that — the fix is in the sources AI reads.

This works the same way brand-level perception does. See Perceptions.

SWOT

The drawer includes a SWOT for the product: strengths, weaknesses, opportunities, and threats, derived from what AI says about it.

Why this matters: it converts a wall of AI commentary into four buckets you can act on. Weaknesses tell you what objection to answer in your content. Threats usually name the competitor products you're losing to. Strengths tell you what messaging is already landing, so you can lean harder on it.

See SWOT Analysis for how SWOTs are built.

Shopping Queries It Appears In

The drawer lists the shopping queries where the product shows up — the actual buying questions that surfaced it.

Why this matters: this is intent data. It tells you which purchase moments your product already owns, and by omission, which ones it doesn't. If a product you positioned for travel never appears in travel queries, the positioning hasn't reached the answer engines.

Query Fan-Outs

For those queries, the drawer shows the query fan-outs — the follow-up questions answer engines generate as they work through a buying question.

Why this matters: buyers don't ask one question and stop. Fan-outs show the chain: the comparison, the price check, the "is it worth it" question. Each link in that chain is a place your product can be included or dropped, and each is a content target.

See Query Fan-Outs.

The Conversations It Was Named In

The drawer lists every conversation where the product came up, and you can open the full transcript.

These transcripts are product-aware:

Why this matters: the metrics tell you a product loses; the transcript shows you the sentence where it lost. You can see the exact moment your product was recommended — or named and then skipped in favor of something else, with AI's stated reason right there. That reason is the thing to go fix.

See Conversations.

The drawer shows the retailer offers AI surfaces for the product, including prices and links.

Why this matters: AI shopping answers don't just name a product, they route the buyer somewhere. This is where the purchase actually goes. It's also where pricing problems become visible — if AI is quoting a stale price, or routing to a grey-market listing that undercuts your own store, you'll see it here first.

Which Retailers Carry It

Alongside the offers, the drawer shows which retailers carry the product according to AI.

Why this matters: it's a distribution check performed by the machine your buyers are asking. Missing retailers mean AI doesn't know your product is sold there. An unexpected retailer means someone is listing you without your knowing. And if your own direct-to-consumer store is missing from the list, AI is sending every buyer to a third party.

For the cross-product view of retailer performance, see Merchants and Retailers.

A Practical Reading Order

For a product with high visibility and low recommendation:

  1. Read the perception — does AI describe it the way you intend?
  2. Read the SWOT weaknesses and threats — what objection, and which competitor?
  3. Scan the shopping queries — is it showing up in the right buying moments?
  4. Open two or three conversations and find the sentence where it got skipped.
  5. Check the retailer offers — is a price or availability problem the real cause?

By step five you usually have a specific, writable brief instead of a metric.

Availability

Shopping & Product Visibility is an enterprise feature, switched on for a brand by the Genezio team based on your contract. There is no self-serve toggle. Products themselves are auto-detected from AI conversations only — there is no catalog upload, feed, crawl, or manual entry.