Import Column Mapping

How Column Mapping Works

Column mapping is the step between uploading your file and importing data into Fixmo. It tells Fixmo which column in your file corresponds to which field in the system. Fixmo attempts to do this automatically using fuzzy header matching, but you always have the option to review and adjust the mappings manually before proceeding.

Automatic Fuzzy Matching

When you upload a file, Fixmo reads the column headers from the first row and normalizes them by removing spaces, underscores, and dashes, then converting to lowercase. The normalized header is compared against each Fixmo field's key and display label to find the best match.

• Headers like 'First Name', 'first_name', 'first-name', and 'firstname' all normalize to 'firstname' and match the name field
• Headers like 'Phone Number', 'phone_number', and 'phone' all match the phone field
• Headers like 'Cost Price', 'cost_price', and 'costprice' all match the costPrice field
• Auto-mapped fields display a sparkle icon and 'Auto' badge to indicate they were matched automatically
• Fields that could not be auto-mapped are left unselected and require manual assignment or can be skipped

Manually Adjusting Mappings

Every column in the mapping table has a dropdown selector. You can change any mapping at any time, whether it was auto-mapped or left blank.

1. 1Review each row in the mapping table, your file's column header is shown on the left, the Fixmo field dropdown is on the right.
2. 2Click the dropdown next to any column to see the list of available Fixmo fields.
3. 3Select the correct field, or choose 'Do not import' to skip that column entirely.
4. 4Repeat for any columns that were not auto-mapped or were mapped incorrectly.
5. 5Ensure all required fields are mapped before proceeding.

Required Field Validation

Each import type has required fields that must be mapped before the import can begin. The proceed button remains disabled until all required fields have a column assigned.

• Customer import, name and phone are required
• Inventory import, name is required
• Supplier import, name is required

Previewing Mapped Data

Below the mapping table, a preview section shows the first 3 rows of your file with the data displayed under the mapped Fixmo field names. This gives you a quick visual check that the mapping is correct before you commit to importing. If something looks wrong, go back to the mapping table and adjust the column assignments.

Drag-and-Drop File Upload

The import page features a drag-and-drop upload zone where you can drop your file directly from your file manager. You can also click the upload zone to open a standard file browser dialog. Supported formats are CSV, Excel (.xlsx and .xls), and JSON (array of objects). The file is parsed immediately after upload and the column mapping interface appears automatically.

Guided Import Mode in Detail

Guided Import provides a row-by-row editing experience for maximum control over your imported data. It is ideal for files that need cleanup or verification before the data enters your system.

• Range picker, select a from-row and to-row to define which rows to process, allowing you to import in batches or skip header rows
• Editable form, each row is displayed as a pre-filled form where you can edit any field value before saving
• Save & Next, saves the current row and advances to the next one in your selected range
• Skip, skips the current row without saving and moves to the next
• Progress counter, shows your current position (e.g., 'Row 5 of 25') so you can track how far along you are

Error Handling During Import

Fixmo handles errors gracefully during both import modes. A single row failing validation does not stop the rest of the import from proceeding.

• In Bulk Import mode, rows with validation errors are skipped and the error is logged with the row number and message
• In Guided Import mode, validation errors appear inline on the form so you can fix them before saving
• The import results screen displays an error log showing the row number and error message for each failed row
• A maximum of 20 errors are displayed in the results, if more errors occurred, a message indicates the total count
• Common errors include missing required fields, invalid data formats, and duplicate records