Label, ingest, and verify identity data

Learn how to label data fields as identities, ingest identity data, and verify the data in the Adobe Experience Platform Identity Service private graph. For more information, please visit the identity service documentation

Hi, in this video, we’ll show you how to label data fields as identities, ingest identity data, and then verify that the data has made it to the Adobe Experience Platform, Identity Service private graph. This slide represents data that we bring into Experience Platform for our demo brand, Luma. In a previous video, you saw how we modeled this in the Schema Editor, and then use batch or streaming ingestion to load the data. Now, we’ll focus on labeling the data to build a private identity graph. Key elements, are the different disconnected datasets. For example, loyalty data, CRM data, and analytics data.
Here we are in the Platform interface. I’ll go to the Schema list and open my Luma CRM Schema. In this example, we have data coming from the Luma CRM system. In this system, the crm_id is the primary way to identify the records, however, any data field that could identify a customer as an individual, for example, email address or phone number, can be labeled as an identity to build a more extensive graph. It’s this selection of identities that powers the joining of datasets. In that other video, we created a schema for our Loyalty ID system with email labeled as an identity. Now, we’ll label the email field in our CRM schema as an identity, so we can join the two datasets together in the realtime customer profile. Be sure to work with your legal and privacy teams to determine which identity you should be collected and use dual labeling to protect the consumer’s privacy. When you select any field that’s a String type, you’ll see an option on the right-hand side to label it as an Identity. Once you label a field as an identity, you need to choose a namespace. The namespace, refers to the system of record or the type of identity. For example, if you have a driver’s license, the system of record for it is the Department of Motor Vehicles. For an email address, there isn’t really a system of record, so you’d use the Type, which is Email. A bunch of standard namespaces are provided by default, if you don’t find the namespace you need, you can create one. I need to create one for my crm_id, so I’ll go to the Identities page and click on Create Identity Namespace. This opens up a widget, where I’ll enter a display name, a shorthand code, and click Create. Once you’ve created a new ID namespace, you can associate the XDM field to this newly created ID namespace.
Note this other option I’m given when I check the Identity box, should this identity be considered a Primary Identity? You can only choose one primary identity per dataset. If the schema is like a database table, think of the primary identity as the primary key. The primary identity plays a special role in the realtime customer profile. You can use it to both update and lookup a profile. In my example, the crm_id should be the primary identity, so I’m going to check that box. Once all of the identity fields have been labeled in this schema, I need to make sure the schema is Enabled for Unified Profile. Next, I can upload my Luma CRM dataset, making sure my dataset is also Enabled for Unified Profile. When a dataset is ingested via batch or stream, the identity fields are ingested into the private graph, populating your graph with more and more identities. Post ingestion, you can use the Monitoring and Identities pages, to confirm if the data was successfully ingested into the private graph or not. So those are the simple steps to label identities, ingest identity data, and populate the private graph. Thanks for watching and have a great day.