What does a Digital Product Passport cost?

The three cost blocks of a DPP project

People who ask “What does a Digital Product Passport cost?” usually mean the software price. In reality, the costs are spread across three blocks - with a weighting that surprises many:

Block 1: Data collection - the real effort

For each article, you need to gather material composition, production locations, certificates and circular-economy information (which data exactly is shown in the DPP guide). The effort depends almost entirely on your starting position:

• Good starting position (data maintained in ERP/PIM, few suppliers): ~15-20 minutes per article.
• Medium starting position (data spread across spreadsheets, emails, supplier documents): ~30-60 minutes per article.
• Difficult starting position (origin data first has to be requested from suppliers): weeks of waiting per supplier round - this is where the notorious time pressure before the deadline arises.

That is why: the earliest cost lever is the start date. Supplier queries that run in the background over months cost almost nothing; the same queries under deadline pressure tie up half the team. You will find the key dates for your sector in the deadline overview.

Block 2: The software

The DPP software handles data capture, validation against the mandatory data of the relevant regulation, hosting of the public DPP pages, and the QR codes. The pricing models are usually subscriptions, tiered by number of articles - with SolveDPP this starts in the low double-digit euro range per month, with unlimited product passports on the Pro plan.

For context: an in-house build (DPP pages, validation logic, versioning, registry connection) quickly runs into a mid five-figure sum in development time - and has to be updated with every change to a delegated act. For the vast majority of brands, the subscription model is therefore the economically clear choice.

Block 3: Ongoing maintenance

The product passport is a living document: material changes, new suppliers, expiring certificates and new collections all require updates. A realistic figure is a few hours per month, provided responsibility is clearly assigned and the software versions changes. Unmaintained passports, by contrast, are a compliance risk - an expired certificate in a published passport is worse than none at all.

Sample calculation: D2C brand with 200 articles

A textile brand with 200 active articles (many of them colour variants of a smaller number of base products), with a “medium” data situation:

Result: a manageable project of a good person-week, spread over a quarter - provided variants are derived from the base article rather than captured individually, and the import from the shop system saves re-entering the master data. It is precisely these two levers (Shopify import, AI pre-fill, variant inheritance) that explain why the software building block massively reduces the collection effort.

Conclusion: predictable - if you start early

DPP costs are no reason to panic: software and maintenance are small and predictable, data collection is the real effort - and it becomes cheaper the earlier and more automated it runs. To see what this looks like in practice, take a look at our annotated DPP example; for smaller teams we have additionally prepared the guide DPP for SMEs.