Heating is a technical-figures business: output, efficiency and ErP class decide the sale, and most of it hides in PDF datasheets. Here's where the SHK standards help, where they stop, and how to turn datasheets into structured data.
A heat pump is not sold on a nice photo. It is sold on its output at a given flow temperature, its SCOP, its ErP energy class and its sound power level. A radiator is chosen by its heat output in watts at a defined temperature spread. A controller only matters if it talks to the boiler it sits next to. Heating is a category where the product is its technical figures — and where those figures decide whether a customer, an installer or a planner even considers the article.
Product data for heating is performance data plus compatibility: kW output, efficiency, ErP label and the relationships between components. That is the whole challenge of this article. Heating is a sub-branch of the broader plumbing & heating (SHK) world, and it inherits that world's standards — but it adds a layer of technical depth that a plain classification never carries.
The core reason is where the data lives. For most consumer goods, a supplier feed carries the attributes that matter. For heating, the attributes that matter are locked in a PDF datasheet:
Do this manually across dozens of suppliers and it does not scale. The route out is the same as for any multi-supplier catalog: consolidate, normalize, enrich and publish — but here the enrichment step has to reach into datasheets.
Heating does not float free; it sits inside the SHK trade's data landscape. Several standards apply, each covering one layer and stopping at the next:
| Data layer | What the standards deliver | Where it stops |
|---|---|---|
| Core master data | DATANORM, IDS/UGL formats carry number, price, base data | No deep performance figures or datasheet detail |
| Technical classification | ETIM groups articles and defines attribute sets | Attribute values often empty — the class exists, the data doesn't |
| Energy figures | ErP / energy label mandates efficiency & class | Delivered as a label PDF, not always as structured fields |
| Compatibility | Fitting tables, sometimes in manufacturer docs | Rarely machine-readable; lives in PDFs and reps' heads |
| Sales content | Not the job of a data standard | Descriptions, benefit copy, images absent |
In short: DATANORM, IDS/UGL and ETIM give you a clean skeleton — a number, a price, a class — and the ErP rules tell you which figures must exist. What none of them reliably delivers is the filled-in spec depth of a datasheet, a machine-readable compatibility matrix, or ready-to-publish content. That is exactly the layer heating retail has to build itself.
The throughline is a three-step job, aimed squarely at the PDF problem — and that is what Productbay is built for:
Crucially, Productbay starts where the standards end: it takes the datasheet the ETIM class never filled, the compatibility that lived in a PDF table, and the content no standard provides, and turns them into filterable product data. Productbay is built for specialist retailers running multi-supplier, multi-channel catalogs — from mid-sized shops to large chains.
Output figures, ErP classes and compatibility buried in PDF datasheets — heating is exactly the case Productbay is built for. See how it reads datasheets into structured attributes and models component compatibility in a 30-minute walkthrough.
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