Everyday practice tends to look something like this: the wholesaler or manufacturer makes its new product list available, complete with SKUs, EAN codes, technical specifications, a few photos and a ready-made product description. The webshop imports the data, the products appear in the catalogue, and at first glance it may seem that most of the content work is already done.
Naturally, that same data package isn't used by a single merchant but by "anyone and everyone". It may easily be that the same photos, data and texts are used, unchanged, by another twenty, fifty or even several hundred webshops. Within a short time, the same product can appear with a near-identical description in countless stores — sometimes right next to each other on Google's results page.
With large product catalogues this is an entirely ordinary situation. You can't write the data sheets of several thousand products from scratch, one by one, so using supplier content is not a problem in itself. The more important question is whether you treat it as finished copy, or rather as raw material to be shaped to your own customers' needs and your webshop's goals.
From an SEO and sales perspective, this is exactly where the two approaches part ways. One webshop simply rebroadcasts the same information that can be found elsewhere; the other builds genuine added value around it.
Duplicate text doesn't mean an automatic Google penalty
The phrase "duplicate content penalty" has been floating around SEO advice for ages, and it comes up especially often in connection with webshops — but the reality is far more nuanced.
According to Google's documentation, duplicate content in itself doesn't count as spam. The internet is full of pages that publish partly or entirely identical information, whether it's technical data, product specifications, press releases or even legal texts. A webshop therefore doesn't need to fear being penalised for an adopted manufacturer description. The problem is rather that if ten webshops offer the same product with the same text, the content itself gives the search engine little reason to consider one of those pages more useful than the others.
It's not worth approaching the task as mere "de-duplication" either. The point isn't for every sentence to sound different — it's for your product page to offer more useful information than your competitors' do.
The manufacturer and the customer don't see the product the same way
It's no bold claim that manufacturer data sheets exist to convey precise product information; in them you'll find the power rating, the dimensions, the material composition, the compatibility, the part number and every technical detail needed to identify the product unambiguously. The customer, however, is rarely after raw data — what they really want to know is whether the product suits the purpose they have in mind for it.
With a cordless drill, for example, it's not only the maximum torque that matters, but also whether it can handle drilling into brick or is better suited to lighter assembly work. With a running shoe, it's not necessarily the name of the midsole technology that aids the decision, but whether the shoe is recommended for longer road runs, everyday training or racing. Explanations like these are often missing from the supplier material — yet this is precisely where the merchant can add real value.
The factual data from the manufacturer doesn't need creative rewriting, of course. A 1,200-watt machine should stay 1,200 watts, and the accuracy of dimensions, part numbers and compatibility information matters more than making every line unique.
A rewritten text isn't necessarily a better text
In many webshops, a "unique product description" really just means rephrasing the supplier text in different words. The "high-performance motor" becomes a "powerful motor", the "premium-quality material" becomes a "premium fabric". The text changes in form, but the customer learns essentially the same things from it as before.
That's why mass rewriting with artificial intelligence doesn't solve the problem by itself either. If ten thousand product descriptions are produced from the same raw material with the same instruction, you can easily end up with ten thousand fluent yet utterly empty texts.
Genuinely useful content starts with understanding what the customer actually wants to know. A coffee machine involves entirely different considerations than a lawnmower, and a child car seat isn't chosen on the same data as a phone case. There is, in other words, no universal template that works equally well in every product category.
A good product page helps the customer see who the product is recommended for, what to watch out for when choosing, how it differs from similar alternatives, and whether it has any limitation better known before purchase. That's genuine added value — not a simple word swap.
Managing ten thousand products is nothing like managing a hundred
It's true that with a smaller range it can be realistic to carefully craft the data sheet of every important product, but a portfolio of tens of thousands calls for a different mindset — there's no justification for spending as much editorial time on a slow-moving accessory as on a product that drives significant traffic and revenue.
Content development needs to be prioritised on both business and SEO grounds. Start with the products that attract substantial organic demand, carry high margins, serve as entry points to important categories, or already rank well in Google with a realistic chance of further improvement. For the less important part of the catalogue, well-constructed automated content can be perfectly adequate. That's not an inevitable compromise on quality — it's sensible resource management.
A product page isn't good because it's long
A myth still persists around product descriptions: that there's an ideal word count above which a product page becomes "SEO-friendly". No such general rule exists — and in truth, it never did.
A simple HDMI cable doesn't need a thousand words if the important information fits into a few paragraphs and a well-structured specification table. For an expensive, more complex product, on the other hand, it can be justified to present the usage, the features, the compatibility and the differences between alternatives in more detail.
The right length, then, depends on how much information the customer needs to make a good decision. If a text is long only to pile more "SEO content" onto the page, readers usually reward it by closing the tab — nobody enjoys getting lost in a maze of useless information.
The product description is only one part of the product data
A common mistake in webshops is trying to cram every piece of information into the running text, when much of the data belongs elsewhere. The EAN, the manufacturer part number, the size, the colour, the material, the power rating, the stock status and the compatibility are all typically structured product data.
This helps the customer too: comparing two products is far easier with tidy, ordered fields than by fishing the important details out of a long description. What's more, that same data can later be reused in filters, in the webshop's own search, in product feeds and on external sales channels.
With a large catalogue, content development shouldn't be treated as mere copywriting; first the data structure has to be put in order, and only then is it worth building the written content on top of it.
This is where AI can become genuinely useful
Artificial intelligence seems the obvious answer for processing thousands of supplier descriptions — but only if you don't use it for simple mass text production.
In Sellvio's system, for example, product data can be generated with AI based on the EAN, and for books there's ISBN-based processing as well. The generated content can be tailored to the character of the webshop and the category, which — with a large catalogue — is already a far more usable approach than plain rewriting.
The key, however, isn't the generation itself, but what data the system works from, what rules it's given and what you expect in a given category. For a power tool, the usage scenarios may matter most; for a furnishing item, the size, the material and where it can be placed; for clothing, the cut, the sizing and the fabric's properties. If you define these in advance, the AI no longer simply "writes something about the product" — it works to an established editorial logic. With a large product range, that makes a real difference.
With Sellvio, it's about more than a text generator
Sellvio's AI features are best imagined as part of a larger product data management process. As we know, a webshop's data can arrive from supplier imports, an external ERP, manual uploads or other systems, and thanks to the API connections these needn't be isolated steps. The merchant can build their own workflow: a new supplier product list arrives, the system processes its data, enriches it based on the EAN and other identifiers, and then produces product copy matched to the category. The high-traffic or strategically important products can then receive an additional round of editorial review.
That's far more realistic than hand-writing unique descriptions for thousands of products. The goal isn't to replace human work entirely, but to direct editorial attention to where it genuinely creates added value.
There is, however, a line you shouldn't cross
AI can only work safely from information that has a reliable source. Technical data, compatibility or safety properties must never be simply inferred because they're typical of similar products.
This is especially important with electronics, tools, children's products and other categories where a wrong piece of data can have serious consequences. If the IP rating or the maximum load capacity isn't specified, for instance, these shouldn't be filled in with guesswork.
The generated text's job is not to invent new product attributes, but to present the available, verified information clearly and usefully.
What to do with the thousands of supplier descriptions you already have?
For most webshops it isn't realistic — nor necessarily justified — to rewrite the entire product catalogue. Once the decision is made to improve the content of your product pages, it's far wiser to proceed gradually, starting with the pages that bring organic traffic, generate significant revenue, carry high margins or stand a good chance of improving their search performance.
The most important products can get individual editing, the next group can work well with category-specific AI-based content, and on the less important part of the catalogue even the supplier description can stay for the time being — provided the data is accurate and well organised.
There's no need to treat every product with equal weight; in commerce, not every product carries the same importance to begin with.
You don't have to throw away the manufacturer description either
The original manufacturer material is often genuinely valuable, as it can contain technical details, standards and compatibility information that shouldn't be left out of your own product copy either. In many cases the best solution is to keep the precise manufacturer data as a clearly separated specification, with your own, more accessible explanation alongside it to help the customer make sense of it.
"80 Nm maximum torque", for example, is an important and precise technical fact — but for someone who doesn't work with power tools every day, it means far more to also learn what kinds of tasks that amount of power is sufficient for.
The two kinds of content don't replace each other, then — they complement each other: the manufacturer data guarantees accuracy, while your own explanation helps the customer understand what that information means in practice.
Supplier data is a good foundation — but don't stop there
If we want to sum up everything covered in the sections above: product catalogues are hard to run efficiently without supplier imports, feeds and centralised product data, so using these tools is completely natural. The trouble starts when that same data becomes the webshop's entire content strategy.
The better approach is for the webshop to organise, enrich and clarify the solid facts coming from the supplier. Automation can reduce the manual work, and for the more important products you can add the experience, explanation and context that no plain product feed can provide.
Sellvio's AI-based product management, EAN-based data processing and API options can truly help here. Not because they "solve SEO" with a single click, but because with a catalogue of several thousand products they make content development more manageable and more consistent.
The ultimate goal is for your webshop to stand apart from the competition not only on price, but also in how much more effectively it helps the customer make the right decision.