The frame for this comparisonProduct data is a practice, not a project.
ASAP's question is whether a clean, import-safe file exists for a brand a dealer asked for — titles written for a consumer, bullets, a spec block, ACA fitment, images and install docs, re-indexed overnight when the brand pushes a change. Anglera's question is whether every SKU on YOUR item file, the line-card brands and the several hundred numbers that were never on it, carries the bolt pattern, the friction compound, the backspacing and the emissions status that the buyer actually filters on — and whether that listing reads like a shop that knows the vehicle rather than like the same paragraph four thousand storefronts published this morning. One is a delivery, repeated per brand. The other is a practice, repeated every time a supplier reissues, a model year drops, or buyers start asking a question your schema has no field for.
01
Ground it
Mine every spec from every source.
Every value traced to a document you can open. The catalog is only as honest as what it was built from.
02
Align it
Aim the catalog at the buyer who actually buys.
Grounded data still loses if it answers questions nobody asked. Alignment is what turns specs into conversion.
03
Keep it alive
Product data is a practice, not a project.
Markets move, suppliers reissue, buyers change what they ask for. A catalog that is right in March is wrong by August unless something is watching.