Catalog Analysis · Case Study in BriefEKOM
An outdoor & cycling gear resale retailer.
A full storefront read, one link in, zero manual setup — and the condition field the entire business rests on was carrying internal reservation IDs out to shoppers. One of a set of anonymized EKOM analyses.
The pattern · populated isn't the same as trustworthy
Every field below showed complete on a standard check. Many were wrong.
EKOM ran this retailer's live public storefront through our analysis pipeline exactly as we would a new account's catalog — one link, no hand-built schema, nothing telling the system it was looking at used outdoor gear or what "condition" was supposed to mean. What came back concentrated in exactly the place a graded-resale business can least afford it: the condition field itself, carrying internal reservation IDs out to the customer — alongside a full attribute-set swap between two unrelated products, two products sharing one identifier, and a shipping-weight gap from zero to a physically impossible ten kilograms. None of it required access to the retailer's own systems to find, and none of it would show up on a completeness scan — every affected field was already marked "filled."
What surfaced
Condition field contaminated catalog-wide
The clean condition vocabulary — Pristine, New, Excellent, Good, Worn — carries internal reservation IDs and dedup suffixes on hundreds of items: Excellent_RES######.
A boot specced as a hydration bladder
A Danner women's hiking boot carries a full attribute set belonging to a hydration reservoir — Best Use, capacity, and material all describe the wrong product entirely.
Two products sharing one identifier
A women's merino tee and a men's fishing boot — unrelated products — share one product_id, corrupting page rendering and inventory logic.
A shipping-weight gap that breaks checkout
Sixteen of thirty spot-checked items carry grams = 0; one trail short is logged at a physically impossible 10 kg.
Why it's the harder problem to catch. A completeness check confirms a field is filled; it can't tell that "Excellent_RES004292" isn't a valid condition grade, or that a boot's spec sheet actually describes a hydration bladder. On a graded-resale storefront the condition, price, weight, and identity fields aren't back-office data — they're the whole of what a shopper is trusting when they can't inspect the item first. 115 of the 200 findings here touch fields that were never blank; they were populated and wrong.
Where this leads · diagnosis to channel-ready
This pass read and diagnosed. Correction and enrichment are the natural next phase.
For any graded-resale business selling across dozens of brands, the next step after a read like this is resolving the identity and cross-contamination issues that sit underneath multiple findings at once, completing the attributes that are thin today, and holding that line automatically as new consignment inventory arrives — rather than re-auditing it after the fact.