Segmentation & Consent

Overview of segmentation and consent – including data model concepts: data streams, identity, resolution rules, and unified individual.
Deck: http://sfdc.co/ceUCAG

The video covers the following key areas:

Marketing Cloud Growth and Advanced Platform: Overview of the platform, which is built on Data Cloud, aiming to integrate and harmonize data from various sources (CRM, ERP, commerce, etc.) into a single, unified dataset for messaging execution. It is characterized by one data set, one workflow, and leveraging AgentForce for faster operations.

- The Unified Customer Data Model: Details Data Cloud as the foundational layer for connecting, unifying, analyzing, planning, generating, and activating data.
This includes a five-slice funnel visualization:
- Data Streams: Raw population data from sources like CRM (Contact, Lead, Account) via the CRM connector.
- Identity Resolution: Rules (e.g., normalized email) to define the marketable population by unifying multiple pieces of data into a singular "Unified Individual" profile.
- Segments: The infrastructure for creating targeted audiences based on defined criteria.
- Unified Individuals: The consolidated, marketable profile of a single person.
- Consent: The final check (explicit consent) before any communication is sent.

- Segmentation Features and Creation Methods: Segmentation is defined as filtering data to target specific groups. Four methods for segment generation were outlined: converting Campaign Members, using Quick Filters, Manual creation with explicit criteria, and co-creation with Einstein AI using natural language prompts.

- Segment Builder and Attributes: Discussion of the Segment Builder's views and how attributes/calculated insights define the audience, differentiating between direct Data Model Objects (DMOs) for single values and related DMOs for multiple values. Also covered are segment properties like data space, the "unified individual" basis, and publish types ("standard publish" and "rapid publish").

- Advanced Segmentation and Testing: Demonstrated how to combine logic for multiple attributes, use the "include" and "exclude" toggle (like a suppression list), and methods for reviewing and previewing segments (e.g., Data Cloud segment preview, SQL snippets, or running through a basic Flow).