Product Data for Sanitary Ware: Get Dimensions and Variants Exactly Right

Toilets, basins and tubs get built into fixed building fabric — so their data has to be dimensionally exact and variant-clean. Where DATANORM and ETIM help, and where they stop.

Jakob Feinböck, ProductbayJuly 4, 20267 min read
☝️Key takeaways
  • Sanitary ware is a dimension-and-variant business: toilets, basins and tubs get built into fixed fabric, so width, projection, mounting height and drain position have to be exact to the millimetre.
  • One model line explodes into variants — drain side, overflow, tap holes, colour, coating — and a wrong or missing attribute means a returned part.
  • DATANORM and ETIM carry the branded plumbing core, but stay transactional and feature-thin: no deep specs, no sales content, and they fade in the accessory and spare-part longtail.
  • Productbay models dimensions and variant matrices in one consistent structure and uses AI to read specs out of datasheets exactly where the standard stops.

A wall-hung toilet is not really a product until you know its rough-in dimensions. Neither is a basin until you know its width, projection and tap-hole configuration, or a bathtub until you know whether it fits the alcove and which end the drain sits on. In sanitary ware, the article number tells you almost nothing — the measurements and the variant are the product.

Product data for sanitary ware is, above all, dimensional and variant data. Everything hangs on getting the width, projection, mounting height, drain position and variant matrix exactly right — because these objects are built into fixed building fabric, and a millimetre error becomes a returned pallet. This is a sub-area of the broader plumbing & heating challenge, sitting alongside fittings, heating and pipework.

Why are dimensions and variants so hard to get right?

Sanitary objects are unusually unforgiving, because they meet the building at fixed points. The data problem has three layers:

  • Dimensional precision: a wall-hung WC has to match the carrier-frame rough-in; a countertop basin has to match the vanity cut-out; a tub has to fit the alcove. Width, depth, projection, mounting height and drain position all have to be exact — and each is a separate, cleanly typed attribute, not a line in a description.
  • Variant explosion: one model line fans out into drain-left / drain-right, with / without overflow, one / two / three tap holes, colour, and coated / uncoated glaze. Miss one axis and the customer orders a part that does not physically fit.
  • Set logic: a bathroom is sold as bundles — bowl plus seat plus cistern plus mounting frame — each sub-article with its own dimensions and variants, all of which must stay consistent with each other.

Do this in a spreadsheet and it doesn't scale — one supplier's overflow column is another's free-text note. The fix is the same as everywhere: consolidate, normalise, enrich and publish — but here the normalisation step carries unusual weight, because a wrong dimension is worse than a blank one.

Which standards apply — and where do they stop?

The plumbing trade does have connecting standards. DATANORM is the long-established data-exchange format of the German building-supply chain, and ETIM classifies articles into feature-based classes. For the branded core assortment of the big sanitary manufacturers, they work. But it pays to be honest about the boundaries:

Data layerWhat DATANORM / ETIM deliverWhere it stops
Transactional master dataDATANORM: article number, price, EAN/GTINThin on rich attributes and marketing content
Feature classificationETIM class + feature skeletonNot every dimension is a mandatory feature; gaps stay
Dimensions & drawingsPartial, manufacturer-dependentFull spec often only in the PDF datasheet
Sales contentNot the job of an exchange formatDescriptions, SEO text, benefit copy absent
Accessories & sparesWeak coverage, small brands & importsLongtail arrives as Excel / PDF

In short: DATANORM and ETIM give you a clean transactional and classification skeleton for the branded core. What they don't reliably give you is the full dimensional spec, the drawings, the sales content, or anything in the accessory and spare-part longtail. That gap is exactly where the manual work — and the millimetre errors — live.

How does Productbay structure sanitary-ware data?

The throughline is a three-step job, tuned for dimensional and variant precision — and that's what Productbay is built for:

  • Consolidate: import every source once — DATANORM export, supplier CSV, Excel, feed URL, FTP, API — and match by article number or EAN/GTIN so existing products update and new ones are created. Dimensions, variant matrices and set relationships land in one structure.
  • Enrich: AI reads dimensions and technical attributes out of PDF datasheets and drawings, normalises variant matrices (drain side, overflow, tap holes) into a consistent shape, writes benefit-driven descriptions, assigns ETIM-aligned categories and translates via DeepL — always with a review queue before anything publishes. Product images and drawings are managed alongside in the DAM.
  • Publish: two-way sync to Shopify and Shopware, ERP connections (Xentral, weclapp), and feed exports for Amazon, OTTO and Kaufland — each with per-channel transformations, and set bundles kept intact.

Crucially, Productbay starts where DATANORM and ETIM end. If your branded core already arrives clean, great — Productbay takes over the dimensional depth the exchange format never carried, the variant normalisation, and the accessory longtail no standard covers. Built for specialist retailers running multi-supplier, multi-channel catalogues — from mid-sized shops to large chains.

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Dimensions to the millimetre, variant matrices that actually hold, spec sheets pulled out of PDFs — sanitary ware demands precision. See how Productbay consolidates, enriches and publishes your sanitary catalogue in a 30-minute walkthrough.

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