- Overview
- Intro to Audience Manager
- Setup and Admin
- Web Implementation
- Integrating Offline Data
- Mobile Implementation
- Audience Marketplace
- Build and Manage Audiences
- Data Explorer
- Using the Signals Dashboard to Quickly View Top Available Signals
- Using Data Explorer to Search for Used and Unused Key/Value Pairs
- Saving Searches in Data Explorer for Convenience in Re-use
- Using Data Explorer to Create Retroactive Traits and Segments
- Using Data Explorer to Validate Trait Creation for Your Onboarded Data
- Using Data Explorer to Work with Signals Coming from Adobe Analytics
- Traits and Segments
- Planning Trait Creation from Analytics Data
- Creating a Trait Taxonomy
- Creating Rule-based Traits
- Creating Onboarded Traits
- Creating Conversion Traits
- Choosing a Data Source when Creating Traits
- Configuring Trait Expiration with the Time to Live (TTL) Setting
- Using Code View to Create and Edit Traits
- Introduction to Bulk Management (BAAAM)
- Creating and Managing Traits in Bulk with BAAAM
- The Basics of Creating Segments
- Creating a Segment Taxonomy
- Practical Segment Definition and Creation
- Creating Segments from Multiple Data Sources
- Choosing a Data Source when Creating a Segment
- Enhancing your Segments with Trait Recommendations
- Trait Recommendation Enhancements in the Segment Builder
- Using Recency and Frequency in Segments
- Using Code View when Building Segments
- Import Segments from Adobe Analytics into Audience Manager
- Building a Segment to Suppress Ads to Customers
- Mapping Audience Manager Segments to Destinations
- Mapping Segments to a Device-based Destination
- Understanding Numbers in the Trait Graph
- Understanding Numbers in the Segment Graph
- Customer Tips - Traits and Segments Best Practices
- Algorithmic Models
- Understanding Predictive Audiences
- Configure and Report on Predictive Audiences
- Creating a First Party Look-Alike Model
- Excluding Traits in Algorithmic (Look-Alike) Models
- Increase ROAS by Using Algorithmic (Look-Alike) Models
- Using Look-Alike Models to Extend Sold Out Inventory from Your 1st Party Data
- Profile Merge
- Profile Merge Rules
- Overview of Profile Merge Rules
- Profile Merge Rule Examples and Use Cases
- Choosing the Right Profile Merge Rule
- Creating and Using Simple Profile Merge Rules
- Using Profile Merge Rules to Personalize in an Authenticated State
- Using Profile Merge Rules for Device Extension and Increased Reach
- Overview of Profile Merge Rule Enhancements
- Profile Merge Rule Enhancements - Pre-Requisites
- How Profile Merge Rule Enhancements Impact Segmentation, Activation, and Reporting
- Interpret Audience Identity Reporting
- Understanding Cross-Device Metrics in Audience Manager
- Customer Tips - Getting the most out of Profile Merge Rules
- Data Explorer
- Data Activation
- Destinations Basics
- Audience Lab
- People-Based Destinations
- People-Based Destinations Videos and Tutorials
- People-Based Destinations Data Flow
- Creating a Data Source for People-Based Destinations
- Understanding Hashed PII Data Ingestion for People-Based Destinations
- Ingesting Hashed PII for People-Based Destinations
- Using setCustomerIDs() to Ingest and Hash PII as a Declared ID
- Configuring Profile Merge Rules for People-Based Destinations
- Creating Segments for People-Based Destinations
- Create and Configure People-based Destinations
- Understanding and Configuring the LinkedIn People-Based Destination
- Understanding and Configuring the Google Customer Match People-Based Destination
- Reports
- Other Integrations
- API
Understanding Numbers in the Trait Graph
Get some tips on understanding the reported numbers for traits in the trait info screen.
Resources on adobe.com
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