With ​Related Data, you can define multiple fields in which to save information. The field where data is saved is called a related data set. A related data set can be linked directly to a profile attribute (standard or custom) or can exist independently in the system.

A related data set linked to an attribute​

When recipient-specific information is saved in a related data set, this data set can be directly linked to those recipients. This connection is established via the attributes, and a direct connection is established between the related data set and the attribute. An entire data set (or multiple data sets) can be associated with an attribute, which means that individual pieces of information are not saved in individual attributes.

For example, the attribute 'User ID' is linked to the related data set 'Purchase History'. All customer purchases are saved in this related data set.

The key for the related data set is the User ID. There is a direct link between the attribute and the related data set. Therefore, Mapp Engage uses the ID saved in the attribute to identify which data set pertains to which recipient.

When the data is used to personalize the message content, the system uses the connection to the attribute to determine which related data sets to access.

Data Selection​

Access to the data set depends on whether the related data set is linked to an attribute, or exists independently in the system.

The system requires less information to identify the desired data set when the data set is linked to an attribute. The attribute link determines which related data sets are used, and can even determine which data sets are relevant for the customers. Therefore, related data sets that contain customer-specific information are linked to an attribute.


You want to insert product data that is stored in the related data set 'Purchase History' into an email message.

First, insert a placeholder into the message. The placeholder must contain information that indicates which related data set is referenced since each attribute can be linked to more than one data set. The placeholder must also indicate which column of data in the related data set is needed. The appropriate User ID number is already in the linked attribute and the related data set links to the attribute. Therefore, Mapp Engage has enough information to determine which data to insert. The system selects and imports the relevant product information (in this case, the Product ID) from the 'Purchase History' related data set.

To use the data that is saved in an unlinked related data set, additional information must be entered into the placeholder in the email message. To enable the system to insert the correct data in this case, enter the following details into the placeholder:

  • The related data set the data is saved in (in this case, Purchase History).
  • The data set to be selected (in this case the data set with ID 1234, although more complex inquiries are also possible).
  • The exact data to be imported into the message (in this case, the ​Product ID​ column).

Links between Related Data Sets​

You can also link individual related data sets with each other.

Example: Linking Product History to Product Data

The previous example only inserts the product numbers into the email message. However, you can also create a rule that uses those product numbers to access additional data that is saved in a different related data set. For example, you can get product names and sizes from the related data set 'Products'. The related data set 'Purchase History' is directly linked to an attribute (as illustrated under “A related data set linked to an attribute”). During the inquiry, the value in the product column is used to identify the correct data set within the related data set 'Products'.

Data Set identifiers: unique and non-unique​

Depending on their use, the data sets in a related data set can either be unique or non-unique. When creating a new related data set, you must indicate whether the data exists once or more than once. If the data set is unique, Mapp Engage checks during the data import process that the transferred data really exists only once.

If the data set is non-unique, you can have up to 800 similar keys in the data set.

Example: a non-unique data set

The related data set 'Purchase History' contains a record of all customer purchases. These data sets are non-unique: the customer number serves as the identifier of a data set. Every time the customer completes a purchase, a new data set with the same customer number as key is created. One customer could therefore have an unlimited number of data sets (purchases).

Example: a unique data set

The related data set 'Products' contains all data for products sold. These data sets are unique, as each product exists only once with a single product ID number as its key.