AI Shopping
Whether your products are recommended when a shopper asks an AI assistant. Two surfaces, product-level rather than brand-level, with honest denominators.
AI Shopping answers a different question from AI Visibility: not "is our brand named" but "do our products get recommended". It asks shopping prompts on two consumer shopping surfaces, records which product cards were shown, and matches them against your catalogue.
It is product-level, and that is why it is its own section rather than a fold of AI Visibility. Every AI-visibility item is brand-level; this is a table of products with its own catalogue, its own cadence, its own allowance and its own competitor set.
The four screens
| Screen | The question it answers |
|---|---|
| Shopping Overview | Do our products appear at all, per surface |
| Products | Which of our products appear, on which questions |
| Merchants | Whose products appear instead of ours |
| Ads | Where advertising is observable, and where it is not |
Two surfaces, and they are not equivalent
RankX AI observes ChatGPT Shopping and Google AI Mode. They differ in ways that change what a number means, and shopping surfaces sets out the detail. The one difference to carry everywhere: only one of the two exposes whether a result was an advertisement. A zero in the ads column on the other surface means "not observable here", never "no advertisers here".
Shopping prompts are a separate allowance
A shopping prompt is a shopper's question, and it is a different object from an AI-visibility prompt:
| AI visibility prompt | AI Shopping prompt | |
|---|---|---|
| Asked on | The five AI assistants | The two shopping surfaces |
| Measures | Whether your brand is named | Whether your products are recommended |
| Charged | Per prompt, per assistant, per run | Per prompt, per surface, per run |
| Plan allowance | Its own cap | Its own separate cap |
The two allowances do not draw on each other. Using all your AI-visibility prompts does not reduce what you can track here. Figures are in plans and limits.
The denominators, which decide what every figure means
Shopping visibility divides by answers that showed products at all, not by checks run. An answer that returned no product carousel has no opinion about your catalogue, so counting it against you would be inventing a loss.
Every check therefore falls into one of several states, and the screens keep them apart:
- Checks run, the total.
- Checks that produced an answer.
- Checks that showed products, which is the denominator.
- Checks that could not run.
- Answers that included your products, which is the numerator.
A blank visibility figure means nothing showed a carousel in the window, so there is no denominator. It is never rendered as zero. See null is not zero.
An incomplete catalogue reads as a loss
The one measurement error that is yours rather than RankX AI's.
Matching works by comparing the product cards a surface showed against the catalogue RankX AI holds for your Website. A product missing from that catalogue cannot be matched, so an answer that recommended it is recorded as an answer that recommended somebody else.
Two consequences: your visibility reads lower than it is, and Merchants reads higher, because unmatched cards are what that list is built from.
Before drawing a conclusion from a low number, check the product catalogue.
Cadence and cost
Shopping checks are charged per shopping prompt, per surface, per run, so your bill is:
shopping prompts x 2 surfaces x runs per month
The cadence floor is your plan's, or 7 days while on trial, whichever is slower, on the same basis as every other check family.
Prices are on the credit cost reference.
Where to go next
- Shopping surfaces, for what each surface can and cannot tell you.
- Products, including why the catalogue matters more than it looks.
- Merchants, for who wins the slots you do not.
- Ads, and the zero that means "not observable".
AI Overview Citations
The domains and pages Google's AI Overviews cited for your tracked keywords, ranked by how often. What it is good for, and what it is not.
Shopping surfaces
The two AI shopping surfaces RankX AI observes, how they differ in what they expose, and the one difference that changes how every ads figure must be read.