Turn messy supplier datainto publish-ready product catalogues
Send the spreadsheet exactly as your supplier shipped it. A SKU or barcode per row is enough. RefynData finds every product online, fills the gaps, tidies the formats, and hands back a catalogue ready to import into your store.
What changes in your product data
The same product before and after, so you can see exactly what improves.
SKU NX-4821-W
SKU NX-4821-W
Every value carries a link to where it was found
A list of SKUs is enough to start
Plenty of suppliers send nothing but a code. RefynData matches each SKU to the real product, then goes and finds the values a shopper actually filters on: name, brand, sizes, capacity, energy, finish. Every one is recorded with where it came from, so anyone on your team can check a figure in one click.
Every catalogue gets a score
One number for how ready your data is to go live, broken into the three things that make it ready, plus a grade on every product, worst first, so you know where to start.
It recalculates itself every time the data changes, and it warns rather than blocks. Exporting a catalogue scoring 61 is your call to make.
Checks that found nothing are shown too. A score you can read is worth more than a score you have to trust.
Grade E
Refrigeration · 297 productsCompleteness
the values a shopper filters on
Consistency
same unit, same word, everywhere
Confidence
how much is traced to a source
What was checked
Measured over 297 products on 12 August. Scoring changes nothing. It only reads.
Who uses RefynData
Built for the teams stuck reconciling supplier spreadsheets by hand. RefynData closes the gap between messy supplier feeds and a functional ecommerce catalogue, whatever you sell.
Retailers
Streamline supplier product onboarding and cut manual data management overhead.
Distributors
Onboard hundreds of supplier catalogues without adding headcount.
Merchandising teams
Free merchandisers from manual enrichment work so they can focus on assortment and AOV.
Ecommerce & PIM teams
Hand Pimcore, Akeneo, Magento or Shopify a file that imports first time: complete, consistent, and in your structure.
Six recent jobs
Our own account of work we have done. The customers are unnamed here, and every figure is one we put in the report we handed them.
Here, fridge water filters belong under the appliance, not under filters. Nobody told us that. We picked it up from their own corrections rather than pushing a standard taxonomy on them, and 96% of the next upload came back filed their way.
Appliance retailer · 3,100 SKUs
Sixty-two wall panels, spread across fifteen categories. Tiles, cladding, even sofas. We pulled them into one range and kept the old category as a filter shoppers can still use.
Bathroom retailer · wall panel range
Two hundred and twelve products came back empty on the first pass. We put twenty of them straight back through, with no code changes and nothing retyped. Fourteen came back with a real source attached. They were never missing, just badly searched.
Percussion and pro-audio retailer
Single Ended and Single End Bath. Corner and Corner Bath. Freestanding and Freestanding Baths. Twelve spellings in one column covering eight actual bath types, so shoppers got twelve filter options for eight real things. The filters only started working once the twelve became eight.
Bathroom retailer · 329 baths
We checked 874 of 901 products against a named source, and listed the other 27 as unchecked rather than guessing at them. Knowing what we could not verify is what makes the number at the top of the report worth reading.
Kitchen appliance distributor
Their importer used to throw supplier image links out. Wrong format, or dead by the time it ran. We fetch every link before it reaches the file, so this time the import rejected none of them.
Magento retailer · 8,400 SKUs
The practical answers
The things retailers and distributors ask before they send us their first file.
What do we need to send you?
Just the spreadsheet your supplier sent, exactly as it arrived. Any columns, any names, no template. A SKU or barcode per row is enough, and brands are spotted automatically.
Where does the missing data come from?
Each product is found online on retailer and manufacturer pages, including the datasheet PDFs attached to them. Specs, images, manuals and accessories are pulled in, every value keeps a link to its source, and each page is checked to make sure it really shows your product.
Do we have to check everything ourselves?
You stay in control without doing the legwork. AI cross-checks descriptions against specs and flags anything that looks off, and nothing is exported until you approve it, or deliberately skip that step.
What do we get back?
A Google Sheet or Excel file formatted to import into your store or PIM, with one tab per category, images converted to store-safe formats, and product descriptions and SEO copy already written.
Does this help when shoppers ask an AI instead of searching?
It is the same job. An AI answer is assembled from whatever specs are published about a product, so a listing with a dealer code where the name should be and three blank spec cells gives it nothing to quote. RefynData fills the specs, makes them read the same way across every supplier, then writes the title and description from those values only. It also shows you where a product name is too vague to identify one item, which is the usual reason an answer comes back describing something you do not sell.
Whose data is it?
Yours. Every spec, image and description RefynData assembles belongs to your catalogue. Your data is never sold, shared, or used to improve anyone else's product.
How fast is it?
Enrichment runs on its own once a file is uploaded. Catalogues that took weeks of copy-paste typically come back ready to review in days, not weeks.
See it work onyour own data
The quickest way to judge RefynData is on your own catalogue: your file, your categories, cleaned in front of you.
One email to set a time. No mailing list, no follow-up sequence.