Product Data in Plumbing & Heating (SHK): From the Trade Datasheet to a Customer-Ready Product Page

Few retail sectors are as well organized on the data side as SHK — plumbing, heating and air conditioning. Decades of trade cooperation gave the industry DATANORM, ETIM and Open Datacheck, so a plumber's calculation software can pull an article, its price and its technical features almost anywhere. If your world is faucets, boilers and shower systems, you probably have more structured supplier data than a fashion or furniture retailer could dream of.

And yet the online shop still feels empty. The reason is a mismatch of purpose: the SHK standards are optimized for calculation and ordering by the trade, not for e-commerce content aimed at an end customer. This guide walks the gap — from the standard that describes an article, through the PDF datasheet that hides the real information, to the readable product page a private buyer purchases from — and where a PIM built for retailers takes over.

What is the current state of SHK product data?

Compared to most sectors, SHK is a best case for structured data. Three things dominate the landscape:

• DATANORM: the long-standing exchange format for article number, price, discount groups and basic article data — built so trade software can calculate and order.
• ETIM (with BMEcat as transport): a classification into structured, comparable features — flow rate, connection size, material, energy class — ideal for filtering and comparison.
• Open Datacheck / Open Masterdata: quality and completeness rules plus richer master data, pushing the wholesale channel towards cleaner, more complete records.

The result is real: for the listed core brands you can get consistent article and feature data. The catch is what these formats were designed to carry — and what they were never designed to carry.

Why isn't a trade standard enough for an online shop?

Product data in SHK retail is unusually structured — but structured for the trade, which means article numbers and machine-readable features, not the plain-language content an online customer buys from. A private buyer choosing a bathroom faucet doesn't want a raw feature dump; they want to know it fits their sink, what the finish looks like, whether it saves water and why it's worth the price.

Here's where each standard helps — and where it stops:

Two gaps stack up. First, even for well-covered brands the standard gives you keys and features but no customer-facing content. Second, the standards cover the core assortment of listed brands — accessories, own brands and small suppliers still arrive as Excel or, most often, PDF.

Trade content vs. customer content: what's the difference?

The same product needs two different data layers, and SHK retailers feel this sharply:

• Trade layer (you mostly have it): article number, ETIM class, connection dimensions, flow rate, energy class, price and discount group — enough to calculate an installation and place an order.
• Customer layer (you mostly don't): a readable description, benefit-led bullets ("saves up to X% water"), lifestyle context, compatibility explained in plain words, SEO title and text, and images that show the product in a real bathroom.

Bridging those two layers by hand — copying specs from a datasheet, then writing a description around them, per product, per language — is exactly the manual work that eats your team's week. It's the same consolidate, normalize, enrich and publish problem every multi-supplier retailer has, just with unusually rich source data trapped in the wrong format.

Why is the PDF datasheet the real bottleneck?

Ask any SHK e-commerce team where the information actually lives and the answer is the same: in the PDF datasheet. Dimensions, connection sizes, flow rates, sound levels, energy-efficiency classes, spare-part lists and installation diagrams are all there — rendered for a human to read, not for a system to import. That data is complete and authoritative, and completely stuck.

The traditional fix is a person opening the PDF, reading off the values, and typing them into the shop or PIM field by field, product by product. It doesn't scale past a few dozen items, and it's error-prone precisely where errors hurt — a wrong connection size sells a faucet that doesn't fit. This is why reading product data out of PDF datasheets is the single highest-leverage automation in SHK: the information already exists, it just needs to be liberated into structured fields and readable text.

What sub-segments does SHK cover?

SHK is a broad house, and each sub-segment has its own data quirks — but they share the same core pattern of rich technical source data and a content gap:

• Sanitary objects: WCs, washbasins, shower trays, bathtubs — dimensions and mounting logic dominate.
• Faucets & fittings: flow rate, connection size (G 1/2, G 3/8), finish, water-saving class — variant-heavy.
• Heating: boilers, heat pumps, radiators, controls — energy classes, output data and regulatory labels matter.
• Bath & wellness: shower systems, saunas, accessories — a longtail where own brands and small suppliers dominate.
• Ventilation: ducts, fans, heat-recovery units — technical attributes, often no clean standard feed.
• Pipes & installation: fittings, valves, insulation, seals — massive SKU counts, deep compatibility logic.

How does Productbay help in the SHK trade?

Productbay is built for exactly this shape of problem — rich but trade-oriented source data that has to become customer-ready content, plus a longtail with no standard at all. The job is the same three steps:

• Consolidate: import every source once — DATANORM, ETIM/BMEcat feeds, supplier Excel, FTP, API — and match by article number or EAN so existing products update and new ones are created, with the ETIM features preserved.
• Enrich: AI keeps the structured features, reads specs out of PDF datasheets, writes readable descriptions and benefit bullets, assigns categories, fills gaps from whitelisted sources and translates via DeepL — always with a review queue before publishing.
• 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, features for filters and readable content for the page.

Crucially, Productbay starts where the trade standard ends. If DATANORM and ETIM already feed your listed brands, great — Productbay keeps those features and adds the customer-facing content, the PDF-locked attributes and the own-brand/niche longtail the standards never covered. It's the same pattern across every industry — see the overview for multi-brand retailers — and it's related to sectors like consumer electronics and the DIY & hardware world that share the ETIM/eCl@ss backbone. Productbay is built for specialist retailers running multi-supplier, multi-channel catalogs, from mid-sized operations to large filialists.

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