Product Data for Wine and Spirits: Making Tasting Notes, Vintage and Region Speak

A bottle of wine is never sold on its EAN. It's sold on a story: a grape, a slope, a year with just enough rain, a nose of dark cherry and a finish that lingers. The same is true of a single-cask whisky or a small-batch gin. And yet the data that reaches a retailer almost never carries any of that. You get a producer's hand-kept Excel, an importer's PDF price list, a distributor feed with little more than name, EAN and price. The descriptive layer — the part that actually converts — is missing.

Product data for wine and spirits is descriptive data: tasting notes, vintage, region and grape are what sell the bottle, and they are exactly what suppliers deliver worst. This sub-category sits under the broader food & beverage challenge — but where packaged food leans on GTIN, nutrition tables and GDSN, wine and spirits lean on sensory and origin attributes that no standard reliably transports.

Why is wine and spirits data so hard to structure?

The core multi-supplier problem — no two sources deliver alike — is sharper here because the valuable attributes are qualitative:

• Sensory attributes: nose, palate, finish, body, sweetness. These live as free-text tasting notes, if they exist at all, not as fields you can filter or facet on.
• Origin attributes: region, appellation, terroir, producer. Rich and marketing-relevant, but delivered inconsistently — sometimes a full DOCG designation, sometimes just a country.
• Vintage and variant: the same wine changes every year; bottle sizes and cask editions multiply the SKUs — all keyed only by EAN if you're lucky.
• Fragmented sources: a boutique winery sends Excel, an importer a PDF, a large distributor a thin CSV. Each has its own columns, units and language.

Doing this by hand — retyping a PDF price list, writing every tasting note yourself — doesn't scale past a few hundred SKUs. The path out is the standard one: consolidate, normalize, enrich and publish — with the enrichment step doing most of the work in this category.

Which standard applies — and where does it stop?

It's worth being honest about what the available identifiers and standards actually carry for a bottle:

So the identifiers solve the plumbing — you can match a bottle and move a pallet. What no standard solves is the sensory and origin story, and that story is precisely what a wine or spirits shop competes on. Excel and PDF from the producer, retyped and rewritten by hand, is the default state. That's the gap.

How does Productbay help wine and spirits retailers?

The answer is the same three-step job every multi-supplier retailer needs — but weighted heavily toward enrichment, which is where this category hurts:

• Consolidate: import every source once — producer Excel, importer PDF price list, distributor CSV, feed URL, FTP, API — and match on EAN/GTIN so a new vintage updates the right record instead of creating a duplicate.
• Enrich: AI structures the descriptive layer — it drafts tasting-style descriptions from grape, region, vintage, cask and ABV, assigns categories, fills missing attributes from whitelisted sources, reads specs out of PDF price lists, and translates via DeepL — always through a review queue so a human signs off on every sensory and origin claim before it publishes.
• Publish: two-way sync to Shopify and Shopware, ERP connections (Xentral, weclapp) and feed exports for Amazon, OTTO and Kaufland — each with per-channel transformations.

The point is structure plus content: vintages, bottle sizes and cask editions become consistent attribute groups you can filter and facet, and the descriptive copy no supplier delivered gets written once, reviewed, and pushed everywhere. Productbay is built for specialist retailers running multi-supplier, multi-channel catalogs — the exact shape of a serious wine and spirits assortment.

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