Field mapping is the step that connects your CSV or Excel file to Shopify.
Instead of the system guessing what each column means, you explicitly decide the correspondence.
Once configured, you can save the mapping as a reusable configuration so you don't have to repeat the process on every import.
1) What is field mapping?
When you run a custom import from a CSV or Excel file, the system doesn't know what each column means. Mapping solves this: you tell the system "the column Product Name corresponds to the Title field in Shopify".
Your CSV or Excel
| Name | Code | Price |
|---|
| Chair XL | SKU-01 | 49.99 |
→
Shopify field
- Name → Title
- Code → SKU
- Price → Price
When is mapping used?
Only in Custom Imports. Standard Imports don't require mapping because the file comes from a system export and already has the known structure.
2) Creating a mapping configuration
Follow these steps the first time you use a custom import type:
-
Select the import type
(e.g. "Product update", "Price update", "Full products"…).
-
Upload or provide the CSV or Excel (.xlsx/.xls) file
so the system can detect its columns.
-
Open the mapping screen.
You will see two columns: on the left the headers detected in your file, on the right dropdowns for Shopify fields.
-
Associate each file column with its Shopify field
using the dropdowns. Columns you don't need to import can be left unassigned.
-
Give the configuration a name
and click "Save configuration".
Tip:
Use a descriptive name that includes the type and source of the file, for example "Supplier ABC – Price update".
This makes it easy to identify it in future imports.
3) Field types: standard, metafields and fixed values
Standard fields
These are Shopify's native fields available directly from the dropdown: Title, SKU, Price, Inventory, Product type, Vendor, SEO fields, Images, Variants…
Product update: always map SKU as the identifier. This import type only accepts standard product and variant fields; metafields are not shown as an option and are ignored if they come from an old configuration.
Metafields store additional data that doesn't fit into Shopify's standard fields. When you select "Metafield" in the dropdown, you must provide:
| Parameter |
Description |
Example |
| Namespace | Logical grouping for the metafield | custom |
| Key | Unique name within the namespace | ean |
| Type | Data type: text, number, boolean… | single_line_text_field |
Fixed values
A fixed value assigns the same data to all products in that import, without needing it to be in the CSV.
Usage examples:
- All products in this CSV are from supplier "Northern Distributor" → Vendor field = fixed value "Northern Distributor".
- All imported products belong to the type "Accessories" → Product Type = "Accessories".
To use a fixed value, select the target Shopify field and enable the "Fixed value" option instead of selecting a CSV column. Then type the value you want to assign.
4) Reusing saved configurations
Once a configuration is saved, you don't need to map again on subsequent imports of the same type. The process is:
- Select the import type.
- Upload or provide the CSV or Excel file.
- In the mapping screen, open the "Saved configurations" dropdown and select the right one.
- The system automatically fills in all the assignments. Check that no new columns are left unmapped.
- Continue with the options and start the import as usual.
Important:
If your supplier adds or renames columns between file versions, the saved configuration will not cover those new columns. Always review the mapping before confirming the import.
5) Editing or deleting an existing configuration
Configuration management is done directly from the Import screen:
- Go to Imports and choose a custom import type.
- In the mapping section, open the "Saved configurations" dropdown and select the one you want to modify.
- Make changes to the field assignments and click "Save configuration" to update.
- To delete it, select the configuration in the dropdown and use the "Delete configuration" button.
Warning:
Deleting a configuration is permanent. If a recurring import uses it, subsequent runs will fail. Deactivate or update the recurrence first if applicable.
6) Best practices: consistent column names
A saved mapping configuration is based on the exact column header names in the file (CSV or Excel). If a name changes, the mapping breaks.
❌ Inconsistent
- Version 1:
Sale Price
- Version 2:
sale_price
- Version 3:
Price
Each change breaks the saved mapping.
âś… Consistent
- Version 1:
sale_price
- Version 2:
sale_price
- Version 3:
sale_price
The mapping always works without any changes.
Recommendations:
- Use lowercase letters and underscores:
sale_price, sku_code.
- Avoid spaces, accents and special characters in headers.
- If you receive the file from an external supplier, create a transformation template (in Excel or a script) to normalise the headers before importing.
- Keep an internal record of which mapping configuration corresponds to each supplier or source.