For ecommerce teams
Shoppers are asking before they reach your product page
An assistant now recommends products the way a shop assistant would, in one paragraph, with nothing to browse past it. hyperank reads those answers, shows which retailer pages and threads produced them, and flags the ones describing a product you stopped selling.
What changed
Product discovery used to start in a search box and end in a comparison of tabs. A lot of it now starts with a sentence, something like a rain jacket for commuting that is not too warm, and ends with two or three brands named in a reply. The shopper never sees a category page, never touches a filter, and never meets the merchandising you spent the season arranging.
The failure here is almost always price and inventory. An assistant recommends a colourway you discontinued last season, quotes a figure from a marketplace listing that undercuts your own site, or repeats a returns window you have since changed. The shopper lands on a product page that contradicts what they were told, and the part they remember is that you were dearer than promised.
What your buyers ask
Ecommerce
“best walking shoes for wide feet that are not ugly”
ChatGPTAnswer stored in fullThree brands named, the rest never considered
“are expensive serums actually better than pharmacy ones”
PerplexityAnswer stored in fullReviews and threads set your price perception
“where can i buy a solid wood dining table that ships this month”
GeminiAnswer stored in fullStock and lead time answered from stale pages
“gift ideas for someone who bakes a lot”
Google AI OverviewsAnswer stored in fullGift lists decide a whole season of discovery
Illustration, not a recorded answer
The sources behind the answer
You cannot edit an answer, so you edit what it is built from
Where the answer comes from
Where a shopping answer gets assembled from
- Retailer best of listicles
- Marketplace product listings
- Review videos and roundups
- Buyer threads and forums
- Your product pages and schema
A shopping answer is usually stitched out of pages you do not control and one page you do, which is your own listing. We count each cited domain per engine and record where it sat in the answer, so you can see whether the assistant read your product page at all or built the entire recommendation out of somebody else's roundup.
Watch
See which products get named
Every answer is stored in full with its timestamp and its sources, so you read the exact sentence describing your product rather than a visibility percentage. Sentiment is scored per answer and clustered into themes weekly, which is how a recurring line about sizing or delivery shows up as a pattern instead of an anecdote.
- Full answer text for every tracked question
- Sentiment themes clustered weekly across answers
- Tracked across twenty six countries
Flag
Catch a price that moved
Claim checking tests what an engine said about your products against your approved facts and returns a verdict of correct, incorrect, outdated, unverifiable or misattributed. For a catalogue, outdated is the common one: a retired product, an old price, a returns policy from two seasons back.
- Discontinued products flagged when still recommended
- Root cause names your page or a third party
- Verdicts you can triage rather than a score
Publish
Fill the gaps in coverage
Query fan-out breaks a shopping question into the sub-questions behind it and scores your coverage as covered, partial or gap. Buying guides and comparison pages for the gaps are drafted from your own material, approved by a named person, and published straight to Shopify or whichever CMS you run.
- Gaps scored covered, partial or missing
- Publishes to your store or CMS once approved
- Technical audit covers product schema and crawlability
Nothing publishes on its own
A person on your team approves every word
The approver on an ecommerce account is usually merchandising, because the person who can confirm a price, a size run or a delivery promise is rarely the person writing the page. Drafts route to a named approver and wait there. Nothing reaches a product or guide page until someone who owns the catalogue has read the claim and accepted it.
Find out which products an assistant names when a shopper asks for yours.
Ecommerce questions, answered
We discontinued a product and assistants keep recommending it. Can you see that?
Yes, that is what claim checking is for. The platform pulls the statements made about your products, tests them against the facts you have approved, and marks the ones that are outdated. Where the claim is traceable it names the cause: a page of yours still live, a third party listing, or the model repeating what it learned earlier.
Our prices differ by marketplace. Which one do you check against?
Whichever you tell us is correct. Approved brand facts are yours to set and review, so you decide the reference price, the size run and the returns window the check runs against. The reporting then shows you where an engine quoted something else and which domain it cited, which is normally a marketplace listing or an old roundup.
How do I know an answer you show me is genuine?
Every response is kept as raw text with its timestamp and the exact sources it cited, and any figure in a report opens into the answer behind it. We do not compress an answer into a score and ask you to take our word for it. If something looks wrong, ask and we will show you the stored response it came from.
Do you connect to Shopify?
Yes, for publishing. Once a draft is approved it can go to Shopify, WordPress, WordPress.com, Ghost, Webflow, Wix or a custom API endpoint of your own. The visibility side does not need your store connected at all, since it works from the questions your shoppers ask and the answers the engines return.
Our category spikes twice a year. Does that change how we use this?
Tracked prompts are reanalysed daily with a per-site frequency setting, and brand analysis refreshes weekly, so the run-up to a season is visible while you can still act on it. Seasonal and gift questions tend to be answered out of roundups published months earlier, which argues for writing yours before the season rather than during it.
Does any of this touch our product feed or inventory system?
No. The platform reads what engines say and what they cite, and publishes approved content to your CMS. It does not write to your catalogue, adjust stock, or change a price. If an answer is wrong because a listing is wrong, fixing that listing stays your job, and we will tell you which one it is.
Other industries
- SaaSReview profiles, forum threads and the pricing tier engines still quote.
- FintechRates, fees and licensing, with an evidence trail compliance can read.
- News and mediaWho gets credited for your reporting, and which stories read as current.
- Travel and lifestyleClosed venues, changed entry rules, and the threads answering on your behalf.
Ready when you are
Before your next buyer asks AI about you, ask AI about yourself
One check, four engines, about twenty seconds. We show you the answers before we ask for anything.