Own-label products have no reviews, creators or press to vouch for them. Why that's an existence problem when AI decides what customers find.
And in a world where AI decides what customers find, that’s a bigger problem than you think.
We were doing an enrichment project for a client recently.
The branded products were straightforward. You pull the data, run the process, and there’s loads to work with. Journalists have reviewed it. Creators have shot content about it. Bloggers have pulled it apart. It’s all out there.
Then we hit their own-label range.
And there was nothing. Not thin data. Not patchy data. Just… nothing. No reviews worth noting. No editorial coverage. No independent voice had ever said a word about the product beyond what the retailer had written themselves.
And I thought: these products don’t have a CV.
They exist. They’re probably decent. They’re almost certainly good margin. But as far as the internet is concerned - as far as any system trying to understand what a product is and whether it’s worth recommending - they don’t really exist at all.
The World Has Changed. Private Label Hasn’t Caught Up.
Let’s think about how AI-assisted shopping works in the real world.
When someone asks ChatGPT, Perplexity, or Google’s AI Mode about the best mascara for a night out, those systems don’t just look at what’s on your PDP. They draw on everything they know about a product - every review, every editorial mention, every comparison article, every creator who’s ever opened it on camera.
That’s how a Maybelline mascara ends up in the answer. Because Maybelline’s product has a footprint. It has citations. It has lived experience, documented and indexed across the web.
Your own-label mascara? The one sitting on shelf three-of-four in the category? Nobody has ever said a word about it independently. No creator has featured it. No journalist has reviewed it. No beauty editor has put it in a round-up.
If your product were a job candidate, it would turn up to the interview with a blank CV and wonder why it didn’t get the job.
In the old world - the world of traffic acquisition and promotional spend - that was a manageable problem. You could still push it to the front of someone's experience via paid placements or a well-placed navigation tile. You controlled the shelf. You decided what got seen.
In the emerging world? You don’t control the shelf. The AI does. And it’s going to recommend the products it knows something about.
This Isn’t an SEO Problem. It’s an Existence Problem.
I want to be careful here, because I’m not just talking about improving your product descriptions or sorting out your attributes. Those things matter - and they’re a good starting point - but they’re not the whole picture.
The challenge with own-label ranges in a zero-click economy is more fundamental than that.
Think of it like link-building back in the early days of SEO. You could write a great article.
But what made Google trust it wasn’t the article itself. It was whether anyone else linked to it. Whether it got cited. Whether trusted sources said: yes, this is worth reading. That citation analysis - that web of external validation - was what turned good content into authoritative content.
Your own-label products are the unlinked articles. They’re written by you, published by you, endorsed by you. And that’s all. The system can see it. But the system doesn’t trust it.
A famous furniture retailer’s range is a good example. There’s a reason you can tell the difference between shopping for a branded sofa and shopping for an own-label equivalent. The branded one has been photographed in fifty living rooms on Pinterest. It’s been featured in interior design content. It’s been reviewed. It has context.
The own-label version has a product page. That’s it.
Now ask yourself: when AI becomes the starting point for product discovery, which one shows up?
The Marketplace Expansion Problem Nobody’s Talking About
There’s a version of this that’s going to become a serious issue for retailers who’ve been aggressively expanding their marketplace ranges.
The logic of marketplace expansion is sound enough on paper. Bring in more products, extend your range, increase the surface area of what you sell. More products, more chance of conversion.
But there's an awkward reality: much of that expansion is being done using grey-market OEM products. Things badged as own label. Things sourced from manufacturers who make the same product for seventeen different retailers under seventeen different names. Things that nobody outside the retailer’s own ecosystem has ever written about, reviewed, or cited.
And those things have no footprint.
So, what you’ve actually done is massively expanded your range with products that are, for the purposes of any AI-driven discovery system, essentially invisible. They’re in your catalogue. They’re on your site. But they’re not on the internet. And right now, the internet is how customers start their shopping.
You haven’t expanded your discoverability. You’ve expanded your inventory. Those are not the same thing.
Whose Job Is This, Exactly?
This is the elephant in the room.
For branded products, this problem doesn’t really sit with the retailer. Maybelline has a global marketing operation whose job is to make sure its mascara has a digital footprint. Dyson has people whose entire careers are built around getting their products into editorial. Nike has more creator relationships than most retailers have SKUs. It’s their job. It’s built into their model.
But when a retailer decides to launch a private-label version of a product, there’s no one whose job it is to build the product's external reputation. It gets listed. It gets a description. It gets a price. And then it gets forgotten.
In-store, that was fine. You own the shelf. You can merchandise it however you like. The customer is already in your building. You control the entire context of discovery.
Online, and particularly in the agentic era? You don’t own the shelf. And if nobody external has ever said anything about your product, you’re already severely disadvantaged.
It’s a structural gap that most retailers haven’t fully reckoned with yet. Own-label strategy was built for physical retail. Digital changes the rules entirely.
What Good Looks Like
The retailers who will win on own-label in the next phase of digital commerce will be those who treat their private-label ranges with the same seriousness that branded manufacturers apply to their products.
That means getting products into creators' hands before launch, not after. It means investing in editorial coverage, not just listings. It means having a point of view on what your own-label range stands for - and making sure that point of view gets out into the world where people and AI systems can encounter it.
It also means getting your product data right. Because even if you can’t manufacture external citations overnight, you can make sure that what you do have - your product content, your attributes, your descriptions - is built in the language customers actually use, not the language your catalogue team invented.
That’s where intent-led enrichment comes in. It’s not a magic wand that creates a digital footprint where none exists. But it’s the foundation that makes everything else work. If your product data is thin, poorly attributed, or built around internal taxonomy rather than customer language, you’re compounding the footprint problem, not solving it.
Start with the data. Everything else follows.
Three Things E-Commerce Directors Should Do Right Now
1. Audit your own-label range for digital footprint - not just product data.
Pull your top 20 own-label SKUs by margin. Then search for each one externally - not on your site, but on Google, creator platforms, editorial sites. Ask honestly: does this product have any independent voice? Are there reviews, articles, comparisons, or creator content that would give an AI system reason to trust and recommend it? If the answer is mostly no, you have a structural problem that product enrichment alone won’t solve. You need an external presence strategy for your private label range, not just a better PDP.
2. Treat your private label launches like brand launches, not category fills.
The moment a retailer decides to make their own version of a product, the clock starts. Every day that product sits in your catalogue without any external footprint is a day the gap between it and its branded competitor widens. Build creator and editorial outreach into your own-label launch process before the product goes live. Even a handful of genuine, independent reviews gives AI systems something to work with. A press sample programme for own-label may feel like overhead. In a zero-click economy, it’s a competitive necessity.
3. Enrich your own-label product data in customer language, not catalogue speak.
You may not be able to build a digital footprint overnight, but you can make sure the data you control works as hard as possible. That means enriching your own-label product attributes and content using the language customers actually search with, not the internal taxonomy your team built around operational convenience. Intent-led enrichment won’t substitute for external citations, but it will ensure that every touchpoint your product does have - on your site, in your feeds, in any AI system that encounters your catalogue - is telling the clearest, most relevant story it possibly can. It’s the foundation. Build it first.
Until Tuesday after next,
Warren
Founder & CEO, FoundIt! - The intent-led commerce platform
About Warren Cowan & FoundIt!
Warren Cowan is Founder and CEO of FoundIt! , the intent-led commerce platform used by leading multi-category retailers including M&S, B&Q, Neiman Marcus, John Lewis, and Fenwick. He writes about the future of product discovery, the intent gap, and what it actually takes to make an e-commerce site work the way customers expect.