DPP Might Be the Key to AI Search
But Only If Your Data’s Not a Mess
The conversation around Digital Product Passports (DPPs) has been dominated by sustainability teams, compliance checklists, and EU regulation timelines. All important stuff. But there's a much bigger shift underway that hasn't quite hit the mainstream yet:
DPPs might decide whether or not your products show up in the AI-driven search results of the future.
It sounds like a leap, but it isn't. As the web shifts from keyword-based SEO to AI-native discovery experiences (think: ChatGPT, Perplexity, Google SGE), the brands that win will be those that make their data legible, structured, and query-ready.
And most brands? They’re not ready.
What a DPP Actually Is
Let’s quickly strip away the acronym. A Digital Product Passport is a structured digital record of a product’s origin, materials, production, and certifications. Think fibre compositions, supply chain traceability, manufacturing sites, circularity instructions, certifications, recycling info - all stored in one place and accessible to regulators, partners, and customers.
In theory, that information helps brands meet upcoming regulation. In practice, it forces them to clean up their house. And that cleanup opens up possibilities far beyond compliance.
Because once that data is centralised and structured? It's no longer just useful for sustainability audits. It becomes fuel for AI-powered discovery.
AI Discovery Needs Structured Data (And You're Probably Not Feeding It Any)
Search is changing. People aren’t just typing “linen shirt UK” into Google anymore. They’re asking:
"Find me a summer dress made with certified organic cotton, under £80, produced in Europe."
When you ask that in ChatGPT, it doesn’t look for keywords. It looks for meaningful data.
Which products get surfaced depends on whether platforms can read your product data and make sense of it. That means:
Are your fibre compositions machine-readable?
Do you differentiate between “cotton” and “organic cotton”?
Is your production location tagged or buried in a supplier PDF?
Is your care and circularity info surfaced on your PDP or hidden behind a QR code?
Without structured, accessible data, AI tools don’t know how to rank or recommend your products. You’re invisible.
Why Most Brands Aren’t Ready
If you’ve worked in PLM or product operations, you already know the answer to this: the data is a mess.
Fibre compositions vary by spelling, formatting, and structure ("polyester" vs "Poly.", "100% cotton" vs "Cotton 100%").
Sizing data, care instructions, certifications - all live in different systems, usually siloed.
The spreadsheet that buying uses doesn’t match what garment tech updates. And no one wants to be the person cleaning it all up.
Even when brands launch DPPs, it’s often with partial or retrofitted data. Trying to backfill accurate compositions six months after orders are placed is a headache. Teams end up uploading whatever's on a spreadsheet just to meet the deadline, and the whole thing collapses under its own weight.
In theory, the DPP should reflect verified, certified product data. In practice, many brands are uploading what they think is true, not what they can prove.
That won’t hold up under scrutiny. And it certainly won’t make your products more discoverable.
Discovery Starts Before the QR Code
A lot of DPP rollouts are focused on the QR experience: a customer buys a product, scans the label, and gets access to the digital passport. Great for post-purchase engagement.
But what about pre-purchase?
If your data lives only behind a QR code, it’s not helping you get found. Especially not in an AI-driven world where product discovery starts with a typed (or spoken) question.
To be useful for AI discovery, that information needs to be:
On the product page
Structured (not just in paragraph copy)
Consistent across your PDPs, PLM, ERP, and frontend CMS
And ideally, it’s data you’ve validated - not guessed.
You Can’t Fake Structured Data
Most brands treat product data like decoration. A nice-to-have. Something you wrap around photography and pricing.
But structured data isn’t fluff. It’s infrastructure. And as AI search gets smarter, it’ll reward brands who:
Align internal definitions (e.g. what counts as “recycled”?)
Validate data at the point of entry (not six months later)
Assign ownership of product attributes (is it garment tech, buying, or compliance?)
Push structured attributes to the PDP - not just hidden tabs or PDFs
This isn’t about chasing buzzwords. It’s about preparing your brand to show up where the next generation of customers are looking.
The Brands That Win Will Treat DPP as a Growth Lever
Most brands will treat DPP as a checkbox. A regulation to meet. A cost centre.
A few will recognise it for what it actually is:
A data hygiene forcing function that opens up new distribution, new channels, and new types of customer interaction.
If you get your data right, you're not just compliant. You're visible. You're AI-readable. You're prepped for marketplaces, aggregators, search engines, and digital assistants that reward structured data and penalise chaos.
What You Should Do Now
If you’re not already doing this, start here:
Audit your product data sources. What lives in PLM, what lives in ERP, what lives in buying spreadsheets, and what ends up on site? Map the gaps.
Standardise naming conventions. Agree on fibre formatting, naming, certification labels. Clean up your taxonomy.
Push structured attributes to your PDPs. Make it visible, machine-readable, and customer-relevant.
Assign clear roles. Someone needs to own fibre composition validation. Someone else might own circularity info. Don’t leave it to chance.
Invest in better processes, not just better tools. A new system won’t fix sloppy handoffs or unclear accountability.
Closing Thoughts: A Quiet Shift, Hiding in Plain Sight
DPP isn’t just about sustainability. And it’s not just about compliance.
It’s about setting your brand up for a future where products are discovered through intelligent, structured queries. Where AI platforms look for more than keywords. And where being found depends on being understood.
DPP could be the unlock for that.
If you’re willing to clean up your data first.