Outdated prices
A store or comparison site cited with a price that is no longer valid.
AI Shopping
When AI recommends what to buy.
Bring the approved catalogue into buying questions and find out, product by product, whether AI assistants suggest yours, what they report on price and availability and which sources they rely on.
How buying is changing
The shop window becomes an answer.
More and more often, people who need to buy ask an AI assistant which product to choose. The answer suggests a few products, sometimes with price and availability, relying on sources you don’t manage. Being among those few matters as much as being in the shop window.
Three moments in a purchase, read in an online shop and in an assistant’s answer, which suggests a few products and relies on external sources.
| In an online shop | In an AI answer | |
|---|---|---|
| How many products | The whole catalogue, with filters and sorting. | A few products chosen by the assistant for the question. |
| Price and availability | The ones you publish, kept up to date by you. | The ones reported by sources you do not manage. |
| Who decides the order | Your shop, with its own rules. | The assistant, based on what it finds. |
What can go wrong
An old price, a lost sale.
An external source with the old price, a marketplace showing you as sold out, a feature no page states: the answer repeats them to anyone asking the same question.
Wrong availability
“Sold out” or “not sold in Italy” when the product is available.
Missing attributes
A decisive feature missing from the page text and the feed.
How it works
From the catalogue to the buying question.
The starting point is the catalogue your team has approved. Buying questions come from your product titles through fixed phrases, never written by a model, and are saved in the panel through the usual path.
The approved catalogue
From a file, from Merchant Center or from Shopify read-only.
The buying questions
“Where can I buy…?”, “Is … worth buying?”, “What are the best alternatives to … to buy?”, up to 16 products.
The per-product measure
For each product and assistant: answers that name the brand, recommend it and cite the product page, with their base.
Errors and sources
Prices and availability compared with the catalogue, the sources supporting them and the most present competing product.
Every product
Where it appears, what they say, what to do.
Not an average across the brand: every product has its own card, with the questions where it appears, the attributes cited, wrong or missing, the sources used and the products recommended instead of yours. Every gap becomes an intervention in the Action Center.
The sample record of a product from a fictional brand: where it appears, the wrong attribute, the source behind it, the product recommended in its place and the action.
Northstar Aurae 2 · sample record for a fictional brand
- Where it appears
- In “Where can I buy…?” questions, not in those about alternatives.
- Wrong attribute
- A comparison site lists it as out of stock, while it is available.
- Source
- A price comparison site with an outdated listing.
- In its place
- Orbit Audio Studio, recommended in questions about alternatives.
- Action
- An update request to the comparison site, in the Action Center.
Why it matters
Fix the source, not the answer.
Nobody can rewrite an assistant’s answer. But you can find the source of a wrong price, complete a product page or request a correction, and check what changes at the next observation.
Product by product
Every product with its own base of answers, never a summary number.
Sources to contact
The stores, magazines and marketplaces backing a wrong data point.
Verified interventions
Every error becomes a proposal with priority, owner and check.
Frequently asked questions
Questions about AI Shopping.
What AI Shopping is, what we observe of assistants’ carousels and product cards, how buying questions are created and where the catalogue we compare comes from.
What is AI Shopping?
It is the analysis of your products in AI assistants’ answers to buying questions, starting from the catalogue you approved.
Do you measure assistants’ shopping carousels and cards?
No. What is measured is the text answers to the panel questions. The assistants’ shopping surfaces and competitors’ prices are not collected.
How are the buying questions created?
From fixed phrases per language applied to the titles in your approved catalogue. The link between question and product is exact, never by similarity.
Where does the catalogue come from?
From a CSV, JSON or XML file, or from Merchant Center or Shopify read-only. Before measuring, you correct it and approve a version.
Related paths
After “AI Shopping”, the next step.
Each feature answers a specific question. From here you move on to related features, to the methodology behind their measures and to help for using them in everyday work.
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