Import Customer Data via CSV File
3 min readLast updated: February 20, 2026Integrations
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If you do not want to synchronize your customer data through a direct Shopify or Billbee integration, you can also import orders and customer addresses via CSV file into AutoLetter. This is especially useful for one-time imports, migrations, or when you want to use data from systems without a direct integration.
AutoLetter offers you two ways for the CSV import:
Navigate to Integrations, click Add, and select CSV as the integration type. Give it a name, e.g., "CSV Import March 2026".
Choose one of the two methods: Upload a CSV file or paste the content as text.
AutoLetter automatically recognizes the columns based on the header row. The mapping is not case-sensitive -- firstname, FirstName, and FIRSTNAME are treated the same. Review the mapping and adjust if needed.
Confirm the import. AutoLetter processes the data and then displays a report.
Make sure your CSV file contains a header row. AutoLetter uses it to automatically map columns to the correct fields. Without a header row, the automatic recognition does not work.
The following column names are recognized and mapped by AutoLetter:
| Field | Description |
|---|---|
FirstName | Customer's first name |
LastName | Customer's last name |
Email | Email address |
Company | Company name (optional) |
Street | Street |
HouseNumber | House number |
ZIP |
Not all fields are required. For successful delivery, you need at least the address fields (name, street, house number, ZIP code, city, country).
During import, you can enable update mode. When active, existing records with a matching order ID are updated instead of being created as duplicates. This is especially useful for repeated imports from the same data source.
After the import, AutoLetter shows you a detailed error report. For each faulty row, you can see:
This way, you can fix your CSV file and re-import it.
| Postal code |
City | City / Town |
Country | Country (country code or name) |
OrderId | Internal order ID |
OrderNumber | Order number |
Amount | Order amount |
Date | Order date |
Products | Purchased products |