Excel Import Tutorial
Transform your Excel files into structured RFQs
Prepare Your Excel File
QuoteBase works best when your Excel file follows a simple structure. Row 1 must contain column headers.
Required Columns
- Description - What you're buying (e.g., "Aluminum Bracket", "Steel Shaft")
- Quantity - How many units (numeric values only, e.g., 500, 1000)
- Unit - Unit of measure (e.g., "pieces", "kg", "meters", "liters")
Optional but Recommended
- Part Number - Internal SKU or part code
- Category - Product category for grouping
- Notes - Additional specifications or requirements
Example Structure
| Part Number | Description | Quantity | Unit | Material |
|---|---|---|---|---|
| AL-2401 | Aluminum Bracket | 500 | pieces | 6061-T6 |
Pro Tip
Add extra columns like "Material", "Finish", "Tolerance" - these become custom fields automatically! No need to set them up first.
Important
Avoid merged cells, formulas, or multiple header rows. Keep it simple: 1 header row, data rows below.
Upload & Auto-Detection
QuoteBase automatically detects your columns and suggests mappings using heuristic analysis. The ExcelParser reads your file and identifies data types.
Upload Process
- Click "New RFQ" → "Upload Excel"
- Drag & drop your .xlsx or .xls file (max 10MB)
- Wait for parsing (usually <5 seconds)
- Review detected columns and data types
What Gets Detected
- Column headers (from row 1)
- Data types: text, number, currency, email, phone, date
- Suggested field mappings (Description → description, Qty → quantity)
- Empty rows (skipped automatically)
- Invalid data (shown as warnings)
The parser looks for common column name variations. "Qty", "Quantity", "Amount" all map to quantity field.
Map Custom Fields
Any columns that aren't standard RFQ fields become "custom fields". These are stored as JSONB and validated automatically on client and server.
Standard vs Custom Fields
Standard fields: description, quantity, unit, part_number, category, notes. Everything else becomes a custom field stored as JSONB in rfq_lines.custom_fields column.
Custom Field Auto-Mapping
- Parser detects non-standard columns (e.g., "Material", "Finish")
- Converts column names to snake_case keys (e.g., "Material Grade" → material_grade)
- Infers data type from values (number, text, etc.)
- Validates against existing custom field definitions (if any)
- Shows mapping preview for confirmation
Important
If you have custom field definitions in Settings, Excel columns must match the field_key exactly. Case-insensitive matching is supported.
Review & Validate
Before creating your RFQ, you'll see a preview table with all mapped fields. This is your last chance to catch errors!
Validation Checklist
- All required fields are mapped (description, quantity, unit)
- Quantities are numeric (no text like "approx 500")
- Custom fields have correct data types
- No red validation errors showing
- Preview table looks correct
Common Validation Errors
- Missing required field: Add missing column or map existing one
- Invalid quantity: Must be a number, not text
- Custom field type mismatch: Number field has text value
- Duplicate part numbers: Okay if intentional, warning shown
Pro Tip
Use the "Download Template" button to get a pre-formatted Excel file with all your custom fields included.
Create & Finalize
After validation passes, set your RFQ details and create it. All line items will be imported with their custom field values.
- Enter RFQ title (e.g., "Q1 2025 Production Parts")
- Set deadline date and time
- Choose currency (defaults to org currency)
- Add description/notes (optional)
- Click "Create RFQ from Excel"
- Wait for processing (shows progress bar)
- Redirect to RFQ detail page
Excel imports are processed immediately. For very large files (1000+ lines), this may take 10-15 seconds.