• Your product data file should be a simple .csv table, with each row containing all the attributes of a given product, such as the item ID, the URL of the product page, a link to a product image, etc.
• Use a CSV export library that is compatible with the standard CSV format.
• Use a comma to separate fields in a row.
• In fields containing multiple values, use a pipe (|) to separate the values. Example: …,John Lennon|Paul McCartney|George Harrison|Ringo Starr,...
• When a field does not have any value, leave it empty. Example: value1,,value3,value4
• Do not use newline characters, either unquoted or quoted, in the fields.
• Use UTF-8 encoding.
• Include the field names in the first row (header) and make sure that all the subsequent rows contain the values corresponding to the fields listed in the header.
• Do not use more than 255 columns.
• Do not use field values longer than 64 KB.
• Redundant (starting and trailing) white spaces are automatically trimmed unless they are quoted (e.g. 1, 2, 3 is the same as 1,2,3).
• Even though your product data file normally contains information that is publicly available on your website, you may want to add a level of security by password-protecting it. Emarsys fully supports uploading password-protected product data files over a secure connection.

In the category field, you submit the product category path of your items according to the product categorization system of your online store. 

A category path describes the location of each product in the category hierarchy. It is a >-separated list of subcategories that starts with the top-level category.

For example, a small bicycle store may have the following category hierarchy:

In this structure, Bikes and Bikes > Road Bikes are both valid category paths, while Road Bikes in itself is not, since it is not a top-level category.

The category path for bike1, an awesome road bike, is Bikes > Road Bikes, which can be submitted in your product data file like this:

* In this field, you can use multiple values.

* In these fields, you can use multiple values.

Besides the standard and predefined product data fields, you can also add other product information to your data file by using custom fields. The names of custom fields has to begin with the c_* prefix (e.g. c_color or c_size).

When deciding on custom fields, think about the kind of segmentation you would like to have available in your Emarsys account, then work back to identify the fields that you need in order to achieve those goals. 

This is particularly relevant if you are using Smart Insight, as these fields will enable you to create segments based on product attributes.

If you run a web store in multiple markets or languages, it may be necessary to also include the localized versions of standard product data fields in your product data file. Name your localized fields using the pattern [field name]_[language identifier], that is, the name of the standard product data field must be followed by an underscore and the language identifier (for example, title_it for the Italian title of a book).

All standard and predefined product data fields can be localized, except for item.

Since several product attributes, such as categories, authors and actors, can be used to build statistical models, it is important to use them canonically. For example, the author J. K. Rowling should always be spelled the exact same way in the product data file. When there are more identical strings representing different values of a given attribute, they should be disambiguated consistently, for example J. Doe and J. Doe(2).

Certain Emarsys apps, such as product recommendations, work properly with smaller images. If you only have high-resolution product images, Emarsys can create their thumbnail versions for you. To use this automatic image resizing service, simply replace the image URL with the following URL pattern in the image field:

Make sure to start the URL of the original image with the protocol, which can be either http or https, and to use the standard URL syntax.

This is how a product data file looks like in the Emarsys CSV format. Click here to download a sample file.

The above file without white spaces: 

Note that Emarsys considers both files exactly the same as redundant white spaces and redundant quoting are ignored. Also note that values containing the separator character must be enclosed in double-quotes (e.g. "Foo, Bar").