Skip to main content
Smelt automatically analyzes your CSV headers and sample data to identify standard field types.

​
How Detection Works

  1. Header analysis — Column names matched against known patterns
  2. Confidence scoring — 0.9 for exact matches, 0.6 for fuzzy matches
  3. Sample verification — Sample values displayed for confirmation

​
15 Recognized Field Types

Smelt automatically detects these column types:

​
Viewing Detected Columns

After upload, the file detail page shows:
  • Each column name from your CSV
  • Detected field type (if recognized)
  • Confidence score
  • Sample values from your data

​
If Detection Is Wrong

Column detection is for display purposes only. It doesn’t affect how templates work.
In templates, always use the exact column name from your CSV:
The detection just helps you understand your data—it doesn’t rename or modify columns.

​
Unrecognized Columns

Columns that don’t match known patterns are still fully usable:
  • They appear in the column list
  • You can reference them in templates with {{Column Name}}
  • They just won’t have a “detected type” label

​
Custom Column Names

You can use any column names you want. Smelt will:
  1. List all columns from your CSV
  2. Attempt to detect standard types
  3. Let you reference any column in templates
Use descriptive column names like Pain_Point_Research or Recent_News for custom enrichment data. You can reference these directly in templates.