Associated Terms for Data Foundation

Review terms that you must know when creating your data foundation.

Data 360 Terms

• Activation: The process that publishes a segment to activation platforms (targets).
• Activation Target: The location, including authentication and authorization information, where a segment’s data is being sent to during activation, such as an advertising platform or Marketing Cloud Engagement.
• Attributes: Information or data found in objects for example in data model objects (DMOs). Data 360 has two types of attributes in segmentation:
  • Direct attributes (1:1): Attributes that have a direct relationship in a data model object, meaning a user has only one value, for example, postal code or first name. 
  • Related attributes (1:N): Attributes that have a one-to-many (1:N) relationship, meaning they could have many values per attribute for a specific user, for example, purchases or email events.
• Individual: An Individual profile represents an instance of a person from an external system, such as a SubscriberKey from Marketing Cloud Engagement. To get each instance of a person into the data extension, you segment and activate audiences at the Individual level.
• Segment: A grouping of data that shares some set of characteristics, for example, customers who have the same birthday.
• Unified Individual: A Unified Individual is a grouping of separate Individual profiles that relate to a single Unified Individual profile. These relationships are based on your Identity Resolution and Reconciliation Rules. To include attributes from multiple Individuals into a single data extension row, segment and activate audiences at the Unified Individual level.

Marketing Cloud Engagement Terms

• Attribute: Information or data about a contact found in a data extension created as part of a Data 360 activation. You can use attributes throughout Engagement for content personalization, Omni-Channel messaging, or journey decisioning. For example, a contact’s gender.
• Attribute Group: A logical grouping of data extensions that make up the Contact Model within Engagement. Data specialists can manage attribute groups and their associated data extensions in Contact Builder
• Contact Model: A collection of attribute groups that define a person within Engagement. You can use data related to the Contact Model more widely throughout Engagement, including Journey Builder.
• Data Extension: A table that stores data in Engagement. You can use a data extension for data storage or for sending messages to customers. Each Data 360 activation creates and populates a data extension in Engagement.
• Data Foundation: An implementation where you activate data from Data 360 into the Engagement Contact Model. Easily refresh and reuse this data across Journey Builder for journey decisioning, wait until and exit activities, as well as the content personalization of event-triggered journeys.
• Journey: A marketing workflow that orchestrates a series of personalized messages, decision splits, and other activities. Marketers create journeys in Journey Builder.

Data Foundation Terms

• Core Audience Model: Two core data extensions are connected to the Engagement Contact Model for content personalization and decisioning across many different Journey Builder use cases.
  • The Individual data extension contains your full audience and their commonly used attributes, such as first name, last name, address, gender, opt-in status, loyalty status, and lifetime value at the Individual level.
  • The Unified Individual data extension contains your full audience and aggregate data or Calculated Insights at the Unified level, such as loyalty tier and lifetime value.
• Collective Core Audience Model: Multiple Individual data extensions and one or more Unified Individual data extensions are connected to the Engagement Contact Model. Use these core data extensions for content personalization and decisioning across many different Journey Builder use cases. For example, create one Individual grouping for demographics: gender, age, and country attributes. Create a second Individual grouping for ecommerce: loyalty tier and lifetime value. Then create a single Unified Individual data extension containing aggregate data or Calculated Insights, such as loyalty tier and lifetime value.