Data deduplication tools that match more than an exact value

Each cluster reports which pass caught it, so you can trust a same-email cluster quickly and spend your attention on the close matches.

When you approve a merge, the rows are left out of the cleaned file you download. Your original file is untouched, and every merged row is written into the audit log with the row it merged into. If you decide later that a merge was wrong, the record of it is right there.

They come from forms without validation, from imports run twice, from a sales team that adds an account rather than searching for it, and from joining two exports that disagree about spelling. None of those are fixed by deduplicating once.

Cleaning at the point of export, every time, keeps the number small enough that reviewing the list stays a five minute job. The scoring behind the close matches is fuzzy matching, collapsing a cluster to one record is entity resolution, and the CRM specific version of this page is Salesforce deduplication. For email lists split across several audiences, the same pass is on Mailchimp duplicate contacts, and for lists about to be imported into Constant Contact it is on Constant Contact duplicate contacts.

Every tool on the shortlist removes exact repeats. What separates them is what happens to the rows that are almost the same, who gets to see a merge before it is applied, and whether anyone can tell afterwards which record absorbed which. Ask those three questions of each option before you compare anything else.

We ran the engine on an eleven row customer list with the problems a real export has: a re-keyed row in capitals with trailing spaces, a legal suffix on one copy and not the other, accents missing on a retyped name, and a one letter typo. It proposed four clusters and changed nothing until they were approved.

It also left one pair alone on purpose. Daniel Ortiz at Bluefield Logistics LLC and Dan Ortiz at Bluefield Logistics have different emails and a nickname instead of a typo, so the score stays under the threshold. That is the pair a human should look at, and it is why a deduplication tool that shows its reasons is safer than one that merges on a guess. If you need to resolve those cases across a whole file, the grouping step is entity resolution.

The buyer is usually the person who has to sign off on a number: a RevOps lead about to load a list into a CRM, a finance or AP analyst cleaning a customer or vendor master before a migration, or a marketing ops manager whose email platform bills per contact. All three need the duplicates gone this week and need to show what was removed when somebody asks.

The Analyst plan covers unlimited files of up to 25MB each, and Enterprise puts several people on one invoice. See pricing, or run the demo above on your own file first. The demo runs in your browser and nothing is uploaded.