Are these two strings the same record?
"Jonn Smith" and "John Smith" look like the same person, but an exact match misses them. When you are merging lists or catching typos, you need a number that says how close two strings are, not just yes or no.
Compute the distance
The String Similarity tool calculates the Levenshtein distance — the count of single-character edits needed to turn one string into the other — and a normalized similarity ratio. Set a threshold and you can flag near-duplicates automatically.
See the actual edits
A distance number tells you how different two strings are; the Text Diff Viewer shows you where. Paste the two values side by side to see exactly which characters differ, which is far easier to judge than a raw score.
Where it pays off
- Deduplicating names or addresses across merged datasets.
- Catching likely typos before a send or an import.
- Ranking fuzzy search results by closeness.