A B2B linesheet, going into Shopify
Six hundred columns, most of them empty, and a header row written for a human buyer rather than for an importer.
How you recognise it
- A very wide workbook — hundreds of columns — where a single product uses a handful of them.
- Size runs spread across columns rather than down rows, one column per size.
- Columns describing the photograph or the model rather than the product.
What goes wrong
Worst first, and the worst one is nearly always the one that reports nothing.
- Sizes as columns is the opposite layout from the one a store wants. Turning it into variant rows is the whole job, and doing it by hand is where a size run gets dropped.
- A wide header set makes automatic mapping confident and wrong. A column named for a model’s height matched a product-height field in our own engine before the hazard rules were written.
- Money columns repeat — wholesale, recommended retail, and a cost. Mapping the wrong one puts your buying price on your storefront, and no validation rule can catch it, because a cost is a valid price.
What we do about it
- Money fields are a hazard class: two candidates in that class are never resolved automatically, whatever the score gap, and if two columns want one field neither gets it. That is a refusal, not a threshold.
- Content shape is evidence and it is allowed to contradict a header, which is how a column named for something else is caught.
- Every mapping decision is shown with the evidence behind it before anything is exported.
Where this came from
Each of these is a real file in our test corpus, run through the engine on every change. We publish the shape and what it proved, never a cell — these are catalogues with real buying prices in them.
- joor_linesheet_wide.xlsx
- 2,044 rows · 614 columns. A 614-column B2B linesheet, and the source of the model-height false positive that the mapping hazard rules were written against.
What we did not measure. One linesheet, from one platform, in one season. Linesheets are the least standardised shape we hold and the one where a Supplier Profile earns the most, precisely because nothing generalises from a single file.
Other shapes
- An ERP export or a plain price list — Non-Latin headers, a European decimal comma, and identifiers a spreadsheet has already turned into numbers.
- A Shopify export, going back into Shopify — The shape people assume is safe. Two products whose titles slugify to one handle merge into one, and the import reports success.
All export shapes · Import errors, measured · The Shopify product CSV grammar
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