Fuzzy Dedupe
Upload a dataset to begin
Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
Sign in for free for unlimited files, no payment required.
About Fuzzy Dedupe
Find and merge similar records (e.g. "Jon Doe" vs "John Doe").
Fuzzy Dedupe catches near-duplicate records that an exact match would miss, entries like "Jon Doe" and "John Doe," or "Acme Corp." and "Acme Corporation."
It scores string similarity between values using fuzzy matching algorithms and merges records that cross a similarity threshold you can adjust, consolidating them into a single clean entry.
Category: Cleaning & PreparationCommon Use Cases
- Cleaning a CRM export where the same customer was typed with slightly different spellings
- Merging duplicate company names collected from different sales reps
- Consolidating a contact list built from multiple sign-up forms with inconsistent formatting
Key Features
- Fuzzy string matching with an adjustable similarity threshold
- Merges matched records instead of just flagging them
- Works across name, company, and address fields
- Shows matched pairs before merging so you can review edge cases
Run Fuzzy Dedupe after Logical Dedupe has already removed the exact-match duplicates, so it only has to catch the harder, spelling-variant cases, then use Fuzzy Join if you need to match this cleaned list against another dataset.
Frequently Asked Questions
It uses fuzzy string matching to score how similar two values are, rather than requiring an exact character-for-character match.
It finds and merges similar records that pass the similarity threshold, consolidating them into a single entry.
Built for anyone cleaning CRM, contact, or vendor lists where the same real-world entity was entered inconsistently across sources.
Read the related guide →