Jaro-Winkler distance is a string-similarity measure that compares matching characters, character order, and a shared prefix. It returns a score between 0 and 1, where 1 means the strings are identical.
The method extends Jaro similarity by increasing the score when two values start with the same characters. This makes it useful for short names and values where a typo appears near the end.
When Jaro-Winkler helps
Jaro-Winkler can find variations such as transposed or missing characters in:
- Person names
- Company names
- Short labels
- Addresses
It does not understand whether two values refer to the same real-world entity. A high name similarity can still join different people.
Jaro-Winkler compared with Levenshtein
Levenshtein distance counts the edits needed across the entire string. Jaro-Winkler considers matching character order and favors a shared prefix.
Test both on a labeled sample when matching quality matters. The best threshold depends on the length, language, and cleanliness of your values.
⚠️ Review approximate matches
Use another identifier such as email, phone, domain, address, or external ID before merging records based on a fuzzy name score.
Use Jaro-Winkler in Datablist
In the Duplicates Finder, select a text property, choose Distance, select Jaro-Winkler, and set the similarity threshold. Distance matching is available on paid plans.
Read the data matching guide for algorithm selection and the Duplicate Finder reference for the current settings.