DocsShopping
Product detail
One product's shelf performance across the AI shopping carousels it appeared in. Win rate, visibility share, average slot, price versus shelf, and a trend.
Sometimes one product matters most. Your hero SKU, a new launch, the thing you are fighting to get recommended. This page zooms all the way in on it. You see how often it wins the top slot, how much of the shelf it covers, how its price compares to the products around it, and where all of that is heading.
What it does
For one product, the page shows its shelf performance across the AI shopping carousels it appeared in. The metrics say how prominently ChatGPT featured it.
How to use it
The page has these parts:
- Five shelf tiles that sum up the headline metrics.
- Matched placements: a list of up to 100 rows. Each links to its receipt, so you can read the answer the placement came from.
- A price-versus-shelf card comparing your price to the shelf's typical price.
- A trend card.
How it's computed
- Win rate = slot-#1 placements divided by total appearances.
- Visibility share = distinct carousels featuring the product divided by distinct carousels in the window. A product holding two slots of one carousel is not double-counted. The numerator is distinct carousels, not placements.
- Average slot = mean position. It is an em-dash when the product never appeared. There is no average of nothing.
Price handling is honest on purpose:
- When an engine sends a structured price (an exact amount plus currency), it is stored as-is. Otherwise the amount is read once from the engine's verbatim price text. Some engines send only numbers with no display string. The shown price is then built from the stored amount and currency. When the engine sent nothing at all, the price stays null, never guessed.
- Prices that cannot be read cleanly (
Free, percentages, ranges) become null rather than a made-up number. - A product's typical shelf price is the median of per-carousel medians. So a single 12-slot carousel cannot outweigh three 3-slot ones.
- A price-vs-shelf delta is only shown when both sides share a known currency. Otherwise it renders as an em-dash with the exact reason stated. See how MentionFlow handles missing data.
Limits
- The matched-placement list is capped at 100 rows.
- Metrics cover the rolling shopping window across every collecting engine: ChatGPT, Google AI Overviews, Google AI Mode, and Copilot today. See Engine coverage.