Case study: GenzOutfit, 9 product-page defects and 1,471 catalog keywords sorted
By Kai · Updated Oct 19, 2026 · 2 min read
On my store GenzOutfit I found 9 defects in one product-page template and rebuilt it on one JSON data block. I also sorted 1,471 Pinterest catalog keywords into 482 to keep and 989 to exclude with a Python classifier.
The 9 defects
They included the wrong template, placeholder text on the page, duplicate content, a broken size guide and an off-brand button. The page was rebuilt on one JSON data block, so one template serves every product.
The keyword sort
1,471 Pinterest Catalog Sales keywords were classified by a Python script: 482 keep and 989 exclude. The same pipeline builds 15 pins per URL with UTM tagging and a bulk-CSV schema.
Why it matters for Merchant Center
Many feed issues start on the page: placeholder text, duplicate descriptions and broken variants. A single clean template removes them for every product at once. See apparel attributes for the feed side.
This is my own store, not a client result.
Questions people ask
Is this a client result?
No. It is my own store, GenzOutfit.
Why a single template?
So one fix applies to every product, and a new product starts correct.
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