The shopping question
Ask the exact question a shopper might ask about a brand, category, comparison, use case, deal, shipping, or where to buy.
See when AI shopping leaves your products out.
Beseam asks the same shopping questions across AI assistants and keeps each answer with the products and competitors it mentions. When your product is missing, Beseam checks the product and store details you can change, then prepares the strongest change for your approval.
You see the actual answer and the facts behind it, not a vague visibility score or a guess about how the AI ranks products.
What Beseam sees here
The evidence this page contributes to the wider Beseam system.
Who appeared
See the answer, the products it named, and whether your product appeared instead of hiding everything behind one score.
Competitors and sources
See which competing products appeared and which sources the assistant showed, when those sources are available.
What you can change
Check the product page, catalog, structured data, and feed for things you can improve, then prepare the change for approval.
01
Start with the actual answer.
You need to know what happened on a specific shopping question: what the assistant said, which products it recommended, and whether your product was described correctly. Beseam keeps that answer visible instead of turning it into a single grade.
- Keep the original question and observed answer together.
- Record the products and merchants named in that answer.
- Separate incorrect product facts from simple absence.
02
See what you can change.
Beseam cannot see an assistant's hidden ranking rules. It compares the answer with your product and store data to find missing or different information you can actually change.
- Inspect titles, descriptions, attributes, availability and structured product evidence.
- Keep competitor sightings attached to the exact question where they appeared.
- Treat a likely cause as a hypothesis unless the evidence can establish more.
03
Change it, then ask again.
After you approve a product-data change, Beseam can apply it where the store connection supports that change. Then it asks the same shopping question again so you can compare the new answer with the old one.
- Keep approval and the previous product value attached to the change.
- Re-run the same question instead of substituting a new prompt.
- Do not treat one changed answer as proof of guaranteed future placement.
Current product boundary
What Beseam does not claim
- AI answers are point-in-time observations and can change between runs.
- Beseam cannot see or control an assistant's hidden ranking logic.
- A competitor appearing, a source being cited, or a product-data difference does not prove why the AI chose one product over another.
- No recommendation, ranking, traffic or revenue outcome is guaranteed.
FAQ
Questions about ai shopping discovery
What does Beseam actually measure in an AI answer?
Beseam keeps the shopping question with the observed answer, the products and merchants named, and the sources or citations the surface exposes. It treats the result as a dated observation rather than a hidden ranking score.
Which AI assistants and shopping surfaces can Beseam check?
Configured targets can include surfaces such as ChatGPT, Gemini, Claude, Perplexity, Microsoft Copilot, Google AI experiences, and traditional search. Available coverage depends on the configured monitoring setup.
Can Beseam tell me exactly why another product was recommended?
Not from hidden model logic. Beseam records what was observed, compares it with product and store evidence you control, and separates supported facts from likely causes and hypotheses.
What happens when my product is missing from an answer?
Beseam can inspect the relevant product, page, catalog, structured data, availability, claims, and other connected evidence to find gaps you can actually change. The original question stays attached to the investigation.
Can Beseam make a change and test the same question again?
Yes, where the connected system supports the change. Beseam can prepare it for approval, apply supported changes after approval, and then ask the same shopping question again so the before-and-after answers stay together.
How is this different from a traditional AI visibility tracker?
AI visibility tracking is one part of Beseam. Beseam can carry a missed shopping question into product and store evidence, shopper behavior, an approved change, and the relevant outcome afterward instead of stopping at the visibility report.
Keep exploring
Related pages
Keep the loop moving after the first finding.
Beseam keeps finding what to improve, prepares the change, gets your approval, applies it, and checks the same things again afterward.