Integrate Google Customer Match
- Topics:
- Destinations
CREATED FOR:
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Learn how Adobe’s Real-Time Customer Data Platform and Google’s Customer Match capabilities help brands engage with customers on Google’s owned and operated properties to scale their outreach campaigns. For more information, please visit the documentation.
Transcript
Hi, everyone. In this video, we will be showing you how to combine Adobe’s Real Time CDP and Google’s customer match capabilities to help brands engage with their customers on Google’s own and operated properties with the business objective to increase their outreach campaigns. We will be using Luma, an athletic apparel company.
Luma has recently launched a new line of athletic gear and aims to promote it to its audiences. To capture their attention during the early phases of the customer buying journey, Luma wants to activate their most loyal audiences across Google’s own and operated properties to maximize its awareness campaigns. So let’s see how Adobe’s Real Time CDP can help. Here we are in Adobe Experience Platform. One of its core capabilities is the ability to create rich business segments using online, offline, real time Adobe and non-Adobe generated data. This screen shows Luma’s active segments.
The one we’re focusing on today is the tier one customers, which includes loyal customers who bought any of Luma’s products in the past through online or offline channels and who have recently engaged with the brand and looked at any of its products. Through Adobe’s Real Time CDP, this segment can be activated using one of its several out-of-the-box destinations. As Luma wants to maximize its outreach campaign through Google’s properties, such as YouTube, search and Gmail, we will be using the Google customer match destination. During this process, and after selecting the tier one segment, practitioners can then determine how to match its customers with Google’s, define the start and end date of this activation, and publish it for immediate use in Google. Now, as practitioners pivot to Google’s advertising products, they can see their activated segment learning in Google’s ad console under Audience Manager and can use them as part of any of their awareness campaigns. From a consumer perspective, Sarah Rose, a loyal Luma customer who is part of the tier one segment is targeted and will see Luma’s awareness campaign. This campaign will be seen on Google’s properties, and in this case, on YouTube.
With Adobe’s Real Time CDP support for Google’s customer match, brands can now combine rich historical online, offline and real time behavioral data and reach out to their potential customers when they’re at a critical moment of their journeys. -
Real-Time Customer Data Platform
- Platform Tutorials
- Introduction to Platform
- A customer experience powered by Experience Platform
- Behind the scenes: A customer experience powered by Experience Platform
- Experience Platform overview
- Key capabilities
- Platform-based applications
- Integrations with Experience Cloud applications
- Key use cases
- Basic architecture
- User interface
- Roles and project phases
- Introduction to Real-Time CDP
- Getting started: Data Architects and Data Engineers
- Authenticate to Experience Platform APIs
- Import sample data to Experience Platform
- Administration
- AI Assistant
- Audiences and Segmentation
- Introduction to Audience Portal and Composition
- Upload audiences
- Overview of Federated Audience Composition
- Connect and configure Federated Audience Composition
- Create a Federated Audience Composition
- Audience rule builder overview
- Create audiences
- Use time constraints
- Create content-based audiences
- Create conversion audiences
- Create audiences from existing audiences
- Create sequential audiences
- Create dynamic audiences
- Create multi-entity audiences
- Create and activate account audiences (B2B)
- Demo of streaming segmentation
- Evaluate batch audiences on demand
- Evaluate an audience rule
- Create a dataset to export data
- Segment Match connection setup
- Segment Match data governance
- Segment Match configuration flow
- Segment Match pre-share insights
- Segment Match receiving data
- Audit logs
- Data Collection
- Collaboration
- Dashboards
- Data Governance
- Data Hygiene
- Data Ingestion
- Overview
- Batch ingestion overview
- Create and populate a dataset
- Delete datasets and batches
- Map a CSV file to XDM
- Sources overview
- Ingest data from Adobe Analytics
- Ingest data from Audience Manager
- Ingest data from cloud storage
- Ingest data from CRM
- Ingest data from databases
- Streaming ingestion overview
- Stream data with HTTP API
- Stream data using Source Connectors
- Web SDK tutorials
- Mobile SDK tutorials
- Data Lifecycle
- Destinations
- Destinations overview
- Connect to destinations
- Create destinations and activate data
- Activate profiles and audiences to a destination
- Export datasets using a cloud storage destination
- Integrate with Google Customer Match
- Configure the Azure Blob destination
- Configure the Marketo destination
- Configure file-based cloud storage or email marketing destinations
- Configure a social destination
- Activate through LiveRamp destinations
- Adobe Target and Custom Personalization
- Activate data to non-Adobe applications webinar
- Identities
- Intelligent Services
- Monitoring
- Partner data support
- Profiles
- Understanding Real-Time Customer Profile
- Profile overview diagram
- Bring data into Profile
- Customize profile view details
- View account profiles
- Create merge policies
- Union schemas overview
- Create a computed attribute
- Pseudonymous profile expirations (TTL)
- Delete profiles
- Update a specific attribute using upsert
- Privacy and Security
- Introduction to Privacy Service
- Identity data in Privacy requests
- Privacy JavaScript library
- Privacy labels in Adobe Analytics
- Getting started with the Privacy Service API
- Privacy Service UI
- Privacy Service API
- Subscribe to Privacy Events
- Set up customer-managed keys
- 10 considerations for Responsible Customer Data Management
- Elevating the Marketer’s Role as a Data Steward
- Queries and Data Distiller
- Overview
- Query Service UI
- Query Service API
- Explore Data
- Prepare Data
- Adobe Defined Functions
- Data usage patterns
- Run queries
- Generate datasets from query results
- Tableau
- Analyze and visualize data
- Build dashboards using BI tools
- Recharge your customer data
- Connect clients to Query Service
- Validate data in the datalake
- Schemas
- Overview
- Building blocks
- Plan your data model
- Convert your data model to XDM
- Create schemas
- Create schemas for B2B data
- Create classes
- Create field groups
- Create data types
- Configure relationships between schemas
- Use enumerated fields and suggested values
- Copy schemas between sandboxes
- Update schemas
- Create an ad hoc schema
- Sources
- Use Case Playbooks
- Experience Cloud Integrations
- Industry Trends