--- title: "Getting Started with Related Data in Mapp Engage" slug: "getting-started-with-related-data-in-mapp-engage" updated: 2026-01-09T14:19:16Z published: 2026-01-09T14:19:16Z --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.mapp.com/llms.txt > Use this file to discover all available pages before exploring further. # Getting Started with Related Data in Mapp Engage ## Introduction Related Data in Mapp Engage allows users to store and manage multiple pieces of information about contacts in a structured and efficient way. Unlike contact profile attributes that store only a single value per contact, Related Data sets can contain extensive information tied to unique identifiers such as or Contact ID. This enables advanced customer communication, segmentation, and personalization. > [!TIP] > ![](https://cdn.document360.io/554b9b98-6720-4d8b-9919-c7b203d72648/Images/Documentation/grafik(33).png) > > Looking for a structured learning path? > > Learn step by step in our Academy Course: [Mapp Engage - Related Data](https://academy.mapp.com/catalog/courses/4888782). --- ### Benefits of Related Data - Store large amounts of structured data efficiently. - Use advanced segmentation based on past interactions. - Personalize messages dynamically using stored data. - Maintain product catalogs and purchase history for better targeting. - Establish relationships between different data sets for improved insights. ## Understanding Related Data Sets A **Related Data Set** is a table that can be linked to a profile attribute (e.g., User ID) or exist independently. These sets allow for: - Storing multiple data points about a contact (e.g., purchase history, preferences). - Connecting data for more personalized messaging. - Automating data-driven decision-making in marketing campaigns. ### Linked vs. Unlinked Related Data Sets - **Linked Data Sets**: Associated directly with an attribute (e.g., 'Purchase History' tied to a 'User ID'). These allow for easier data access and insertion into messages. - **Unlinked Data Sets**: Exist independently and require additional information to reference data within messages or segmentation. ### Unique vs. Non-Unique Data Sets - **Unique Data Sets**: Each record is distinct, such as a product catalog where each product has a unique ID. - **Non-Unique Data Sets**: Allow multiple entries per key, such as a purchase history where one customer can have many purchase records. ## Setting Up Related Data in Mapp Engage ### Prerequisites - **Ensure Related Data is enabled** in your Mapp Engage account. Contact your Account Manager if necessary. - **Obtain the necessary permissions** to view and modify Related Data Sets. ### Creating & Populating Data Sets - **Manual Import**: Upload CSV files with related data. - **Automated Import**: Set up a recurring automation for data import. - **Whiteboard Import**: Use workflows to dynamically update data sets. ## Using Related Data in Mapp Engage ### In Segmentation Builder - Use Related Data to filter audiences based on past interactions. - Example: Target users who purchased a tent in the last 6 months. - Use Case: [Target Audiences with Relevant Products](/v1/docs/target-audiences-with-relevant-products) ### Inserting Related Data into Messages - Use placeholders to insert personalized data into messages. - Example: Include product images and descriptions in emails based on past purchases. - Use Case: [Integrate Local Store Promotions in Your Regular Campaigns](/v1/docs/integrate-local-store-promotions-in-your-regular-campaigns) #### Example: Using a Product Catalog in Campaigns Imagine you have a **Product Catalog** stored as a Related Data Set, where each product is identified by a unique **Product ID**. This structured data allows for seamless integration into marketing campaigns. For instance, if a customer (d.ocustom@e.com) has an item in their wishlist for a while, you can dynamically insert the product's **image, name, and description** into an email. This enhances personalization and increases the likelihood of purchase. ![](https://cdn.document360.io/554b9b98-6720-4d8b-9919-c7b203d72648/Images/Documentation/e758c2b7-2083-4614-ab73-69b400758d0f.png) ### Cross-Table Queries - Create data views to link multiple Related Data Sets. - Example: Retrieve product details from a 'Products' data set using IDs from a 'Purchase History' data set. - More information: [Create Data Views for Cross-table Related Data Queries](/v1/docs/create-data-views-for-cross-table-related-data-queries) ## Next Steps - Explore the documentation on creating data structures. - Set up sample data imports to test functionalities. - Experiment with Related Data in segmentation and personalization to maximize engagement. A unique identifier automatically assigned by Mapp Engage when a new contact is added to the system. - The **Contact ID** cannot be changed or edited. - In some parts of Mapp Cloud, this identifier may also be referred to as **User ID**, but both terms describe the same concept. - You can find the Contact ID by going to *Audience > Contact Management > All Contacts* and checking the ID column. ## Related - [Related Data: Overview](/related-data-overview-window.md) - [Structure of XML and CSV Files (Related Data)](/structure-of-xml-and-csv-files-related-data.md) - [Personalization with Related Data](/personalization-with-related-data.md) - [How- To ](/related-data-how-to.md)