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PURIST
312+
Clients automated
14 h/wk
Avg time saved
99.97%
Uptime SLA
< 7 days
Deploy time
PURIST AI
Claude Opus 4.7 · n8n v1.71 · <80ms
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Free Tools /Development

CSV Column Mapper

Paste two column header lists and get confidence-scored field-mapping suggestions using real fuzzy matching, not just exact-name comparison.

Source columns (one per line)
Target columns (one per line)

How this tool works

01

Real fuzzy matching, not exact-match only

Uses Levenshtein edit-distance and common naming-convention normalization (removing underscores, spaces, case) to score every possible pairing, not just flag identical column names.

02

Confidence-scored suggestions

Every suggested mapping shows a confidence percentage, so you know at a glance which pairings are safe to trust and which need a manual look.

03

Handles common naming mismatches

Correctly scores "Full Name" against "full_name" or "fullName" as a strong match despite the different formatting, the exact case that breaks a naive exact-match approach.

Frequently asked questions

How does the confidence score actually work?

Each target column is compared against every source column using normalized Levenshtein similarity (case, spacing, and punctuation-insensitive) plus a bonus for exact substring containment. The highest-scoring pair becomes the suggestion, and its raw similarity score becomes the confidence percentage shown.

Why did it suggest a mapping I know is wrong?

Fuzzy matching works on how similar the names look, not what the data actually contains. "Country" and "County" are similar-looking strings but different fields entirely, always review suggestions below roughly 80% confidence rather than trusting them blindly.

Can this tool actually migrate my data, or just suggest the mapping?

This tool only suggests the column mapping itself, it does not move or transform your actual data rows. Use the confirmed mapping to configure the field-mapping step in your CRM's import tool or an n8n Set node.

What if a source column has no good match at all?

It is shown with a low confidence score and flagged for manual review rather than forced into an incorrect mapping, a genuinely unmapped field is safer than a confidently wrong guess.

Does this handle one-to-many mappings, like splitting "Full Name" into first and last name?

No, this tool suggests one-to-one column pairings only. A field that needs to be split or combined (like Full Name into First/Last) requires a transformation step, not just a rename, typically handled in an n8n Code or Set node after the initial mapping.