Compare a store’s range with what shoppers actually buy. Find what to add, the keywords each product lacks, and the searches that disappoint.
What to add, from the example report for a fictional outdoor store.
Kinds of products shoppers look at alongside yours that you don’t carry, with the styles they pick and a price range.
Words shoppers use for products like yours that don’t find them in your own search today.
Your share of the range per product area, next to that area’s share of what shoppers buy.
Your key searches run against your own catalog, with the weak ones flagged.
The lightest available route is used first. Every request follows robots.txt and identifies itself.
git clone https://github.com/Jenspalmborg/catalog-xray.git && cd catalog-xray uv sync && cp .env.example .env # add your UNBOXAI_API_KEY uv run xray-web # paste a URL or upload an export
Runs on your machine with your own key from unboxai.com/behaviorgpt. Needs Python 3.11+ and uv. A first scan takes a few minutes.