dataclean.to

Remove Duplicates from Distillery and Spirits Product Data

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12

Spirits databases are duplicate magnets because the same product is referenced by its distillery name, brand name, age statement, proof, and bottle size in combinations that vary across distributors, retailers, and tasting databases. A single-malt Scotch might appear as 'Glenfiddich 12 Year', 'Glenfiddich 12yr 750ml', and 'Glenfiddich Twelve Year Old Single Malt' in the same product catalog. dataclean.to normalizes product names, matches age statements and ABV values, and clusters records that describe the same bottle to consolidate your spirits data.

The Problem

Duplicate spirits records create inventory and compliance problems. Liquor retailers with duplicate product entries cannot accurately track stock levels, leading to over-ordering of products already on the shelf or running out of popular items because inventory was counted across separate records. State regulatory filings that require accurate product lists become error-prone when duplicates inflate the reported catalog. Tasting notes and ratings split across duplicate entries prevent consumers and buyers from seeing the full range of reviews for a particular spirit. Distribution partners working from duplicated catalogs may process what appear to be separate orders for the same product. TTB Alcohol and Tobacco Tax and Trade Bureau spirits regulations

How to Fix It

1
Export your spirits product catalog
Pull product data from your inventory system, distributor feeds, and retail platform. Include product name, distillery, spirit type, age statement, ABV or proof, bottle size, price, and any regulatory product codes.
2
Upload to dataclean.to
Upload the CSV. The tool normalizes product names, converts between ABV and proof values, standardizes age statement formats, and matches records that refer to the same bottle despite naming differences.
3
Review duplicate product clusters
Examine groups of entries flagged as the same spirit. The tool shows how names differ across sources, whether ABV values match when converted, and any conflicting age statements or bottle sizes.
4
Merge into canonical product entries
Consolidate confirmed duplicates into one listing per product. Retain all distributor codes and retailer SKUs as cross-references while keeping the most complete product description and tasting notes.
5
Export the clean product catalog
Download the deduplicated CSV and update your inventory and sales systems. Each spirit now has one listing with accurate specifications and no redundant entries.

Frequently Asked Questions

How does the tool handle different bottle sizes of the same spirit?
Different bottle sizes like 750ml and 1L of the same spirit are treated as distinct products. Only entries with matching or missing size information and the same product name and specs are flagged as true duplicates.
Can it match products listed with proof versus ABV?
Yes. The tool automatically converts between US proof and ABV values. A spirit listed at '80 proof' in one entry and '40% ABV' in another is recognized as matching, since proof equals double the ABV.
What about limited edition releases with similar names to core products?
Limited editions that include distinguishing terms like 'Cask Strength', 'Single Barrel', or a specific vintage year are treated as separate products from the core range. Only entries with matching distinguishing attributes are clustered together.

Example: Input → Output

nameskupricebrandrating
Wireless Headphones ProWHP-001$89.99SoundTech4.5
wireless headphones proWHP00189.99soundtech4.5/5

Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Wireless Headphones Pro",
  "sku": "WHP-001",
  "offers": {"@type": "Offer", "price": "89.99", "priceCurrency": "USD"},
  "brand": {"@type": "Brand", "name": "SoundTech"},
  "aggregateRating": {"@type": "AggregateRating", "ratingValue": "4.5"}
}
💡 How it works: Product schema enables rich results with price, availability, and star ratings in Google Shopping.

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