A review of the gemstone rings of a colored-gemstone jewelry retailer — where every ring is described three times on its own page, and the structured specification is the copy most likely to disagree. One of a set of anonymized EKOM analyses — what surfaced, and where it leads.
How EKOM read it. The engine read the retailer's own public product pages — no file, no credentials, no integration — and confirmed each category's count against the total its listing page declares. It read every stone group in its own panel, so an accent stone is never mistaken for the center, and then held each ring's specification against its own name and description. Eleven findings were withdrawn when checking showed the record was right or the finding had misread it, ten folded into findings already counted and six held unconfirmed, and an analyst added three; the headline findings were re-checked live two weeks later. These are findings from an automated review, checked by an analyst — not a merchant-verified defect list.
From diagnosis to channel-ready. Most of the 47 findings point to five upstream patterns, on EKOM's reading of the data (for the retailer's team to confirm): three descriptions of one ring written separately, measurements typed as text with the unit inside, stone groups filled by position rather than role, free text where a list belongs, and some product lines entered with fewer fields. Fixing the findings fixes the findings; fixing the patterns fixes every ring that has already passed through them and every one that will. Then the same intelligence holds the line at intake, so the next ring whose specification disagrees with its page can be caught before it reaches a shopper.