Format guidelines for the CSV file

To successfully import CSV files into your store, make sure that they meet certain formatting requirements described in this article.

If you export products from a store on our platform, a CSV file already has the correct formatting.

General rules

Here are some general guidelines for compiling a CSV file:

Every file must have a header with column names. See List of supported columns →
Column order doesn't matter as long as you use the right column names.
Add any columns required to import your data, and feel free to leave out the other ones.
For example, when updating details for existing products, you can have only those columns you make changes to plus the identifier columns.
Pay attention to mandatory columns. They depend on the type of the item and on the aim of your import (creating new items or updating the existing ones). See CSV file column reference for more info.
Save your CSV files in UTF-8 (that’s the recommended encoding).

Header

The most important part of your CSV file is the header. It’s the first row that contains all the column names. These column names convey what kind of data sits in a particular column.

Format guidelines for the CSV file (3).png

You cannot import a file if there’s no header.

Data types

Each row in the file – except for the header – is dedicated to a specific set of data. To specify what exactly the information in the row is about, you use the “type” column:

Format guidelines for the CSV file (2).png

Based on the type, rows can contain data on:

a product (type = ”product”)
a product option or input field (type = ”product_option”)
a product variation (type = ”product_variation”)
a product file (type = ”product_file”)
a store category (type = ”category”)

If all the rows in your file are for products (type=”product”), you can omit the entire “type” column. Unless otherwise specified, all the rows are considered “product” rows.

Columns

All the columns in your import file except for the “type” column are dedicated to specific information like product name, SKU, price, etc:

Format guidelines for the CSV file (1).png

The information can refer to a product, product option (or input field), product variation, product file, store category depending on a particular row.

Check out the full list of supported columns. You can place columns in any order you like, but make sure you specify column names exactly as given in the reference.

Identifiers

To match data from a particular row with specific products or categories, you use identifiers. For example, when you need to point out which product the option belongs to:

Format guidelines for the CSV file (4).png

When updating existing products, specify product ID or unique product SKU.
When adding options, input fields, variations, or files, specify a unique SKU or ID of the product they must be assigned to.
When updating existing store categories, specify category ID or full category path.

See the list of supported CSV columns for column names.

To know IDs of products or categories, export your catalog and find “product_internal_id” and “category_internal_id” columns respectively. To know redirect IDs, export your redirects.

If you have non-unique or empty SKUs in your store, you can only identify products by their IDs.

Set of sample CSV files

Check out our set of sample CSV files with ready-made examples for different use cases:

You can use these files as a template and see how rows and columns work together. Replace sample items with your products or categories and add more property columns if you need them.

You can learn more about compiling files for specific goals from our detailed case studies.