Fuzzy match Excel lists without an add-in, Mac included

Copy the name column from each sheet into the two boxes above, or save each sheet as CSV and drop it in. The page scores every likely pair and returns the best match for each row in list A.

• QuickBooks Online: Reports > Standard reports > Customer Contact List (or Vendor Contact List) > Export/Print > Export to Excel.
• HubSpot: CRM > Companies or Contacts > Export, file format CSV. The download link arrives by email; an export of all properties has the Record ID as the first column.
• Bank payees or any sheet: copy the cells, header row included, and paste.

Then download list A with a matched ID and score on every row, ready to paste back into your workbook.

Yes. This page runs in Safari, Chrome or Edge on a Mac, so there is nothing to install.

Inside Excel itself (Excel 2021 for Mac and later), XLOOKUP with match mode 2 does wildcard matching, so "*Acme*" finds “Acme Supply Co.” It still misses misspellings like “Jonson” for “Johnson”, which is what a match score catches.

Each pair gets a score from 0 to 100%. Half of it is how alike the letters are (Jaro-Winkler similarity); half is how many words the two names share, with near-spellings counted.

Score = 50% letter similarity + 50% shared words, then plus 6 points if the second column you chose agrees (same email domain, phone or ZIP) and minus 6 if it differs.

Example: “Johnson HVAC Services” against “Jonson HVAC”. The words match closely (“Services” counts for little), the letters are close, and both use johnsonhvac.com. Score: 96%, a match.

Pairs at 90% or above count as matches and 70% to 89% go to review. Both cut-offs are yours to change. Excel’s Power Query fuzzy merge uses a different method (Jaccard similarity) and starts at 0.80 on a 0 to 1 scale.

Clean the names first, then compare. Before scoring, the page:

• lowercases and removes punctuation
• reads “&” as “and”, then drops it
• removes Inc, LLC, L.L.C., Co, Corp, Ltd, PLLC, LLP and The
• expands short forms like Grp, Mfg, Bros, Intl, Svcs and 1st
• reads St, Street and Saint as the same word
• keeps “Co-op” and “Joe’s” as one word
• weighs common words like Group, Services and Holdings lightly
• compares both halves of a “dba” name

Example: “Greenfield Mfg. Inc” and “Greenfield Manufacturing” both become “greenfield manufacturing”: 100%.

Keep the pairs file as your mapping table: one row per business with its ID in each system. It is what an import, a sync setup or a one-time update needs to link records without guessing.

To find duplicates inside one list instead, use the duplicate customer finder. To compare two files that already share an ID, use compare two CSV files.