Audit trading-card catalog data for AI shopping
A catalog checklist based on an archived Izzi’s Gym audit, with careful context for the reported ChatGPT and Shop revenue.
Editorial guide based on archived posts; this is a synthesis, not an original LinkedIn post.
Describe the product rather than the store
Christopher’s archived account says many products used Izzi’s Gym as the brand instead of the actual product brand. Start by checking a sample of listings against the physical items. Keep the store identity in the seller information, and put the real product identity in the catalog fields. For cards, the companion buying-workflow post identifies set, card number, condition, finish, and quantity as details that need to survive from purchase through listing.
Check condition, titles, images, and policies together
The audit account reports used cards marked new and a clothing-oriented return-policy template. Check the condition field against the item, make graded-card titles distinguish the actual card, and describe the image accurately. Write authenticity, return, and fulfillment answers for the products you sell. These checks help people and systems understand the same inventory; they are not evidence of a particular ranking outcome.
Keep the revenue claim in context
The post reports $918.70 from ChatGPT and the Shop app combined before the audit changes. It does not provide a channel breakdown or demonstrate that the fixes caused later sales. This is a founder-reported starting observation, not $918.70 attributable to ChatGPT alone. The guide does not repeat the post’s time-sensitive claims about platform eligibility, fees, or automatic checkout; verify those directly with the relevant platform before acting.