Demo of Real-Time Customer Data Platform
Last update: February 14, 2025
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This video shows how Real-Time CDP is used to collect data from multiple sources, merge that data into a single real-time customer profile, and activate that data to create personalized customer experiences. For more information, please visit the Real-Time Customer Data Platform documentation.

Transcript
Hi everyone. In this video, we will be showing you Adobe’s real-time customer data platform, in action. We will be using Luma, and Athletic apparel company. With Adobe’s Real-Time CDP, powered by Adobe Experience platform, Luma’s marketing organization, can address three key steps. First, bringing data, from disparate platforms, and make sure it’s available downstream, for other marketing activities. Second, create a single, real-time view of their customers, independent, of where data is coming from. And third, drive a consistent, relevant and personalized experience, across every touch point. So let’s take a look and start with a customer journey. The journey starts on the website. As someone interacts, with the Luma brand, data is captured in real-time, and sent it not only to a report tweet in Adobe Analytics, but also to Adobe Experience platform. As this happens, we begin to create a single view of the customer, based on behavioral data, in the real-time customer profile or platform. We know that many visitors to the website, are probably repeat customers, who have previously purchased from Luma. It’s important for the brand to personalize messaging and offerings, to address both new and repeat visitors. Let’s see what happens, when this visitor logs into their account. This is a critical moment for the brand, as we go from an anonymous visitor to a known customer. We’ve just merged, pseudo-anonymous browsing data, with the existing account holder data. And we are pushing this data, into the single profile that is now live in platform. We may have thought that the visitor was a male, but it turns out, it’s a female returning customer, named Sarah Rose, who’s actually loyal to the brand. She’s welcomed with a message, and thanked for being a loyal customer, and provided with a link to access more information on benefits. Sarah, is also receiving a highly personalized homepage experience, that is dynamically delivered, based on her real-time profile, in Adobe Experience platform. Further down to page, she sees featured products, and recommendations, based on her most recent browsing history. Now, let’s go behind the scenes, and see how Adobe Experience platform, helped us, get to this point. Here we are, in Adobe’s Real-Time CDP, powered by Adobe Experience platform. It is purpose built, for customer experience management. It enables brands such as Luma, to simplify data ingestion, and activation, govern known, and unknown data’s usage, and accelerate marketing use cases at scale. As we previously saw, with Adobe Real-Time CDP, we bring data from disparate sources, into a single unified customer profile. So let’s have a look into Sarah’s Rose profile. Here we can see, all the information that we have from her, such as address, communication preferences, behavior across channels and screens, and segments she qualifies for. We see that she is indeed a returning customer, her loyalty status, and that she has been engaging with the brand, mainly through the website, and mobile app, and that she has been racking up on points from past purchases. Fantastic. Now, let’s take a look, at how we brought all these data together. This view, lists all the data sources Luma is using right now. From Adobe’s own applications, such as analytics and Audience Manager, to non-Adobe sources as well, such as Microsoft Dynamics and others. Using our open API’s, Luma can also ingest IoT, point of Sale, and call center data, and much more. At this point, Luma has a rich set of data, about their customers, and can use it to further enhance Sara’s experience and increase her loyalty with the brand. So let’s take a deeper look into Luma segments The segmentation capabilities of platform, are powerful. Marketers, can combine attributes, events, and existing segments, based on data we capture in the real-time customer profile. In her recent experience, Sarah’s interactions on the website, exhibit a different behavior. She has a propensity to buy woman’s apparel. However, the item in her cart is a men’s sweatshirt. This sudden change, in apparel category or size, infers, that this person, isn’t shopping for themselves. So, let’s create a segment, that will represent cart abandoners, with propensity to be in the process of buying a gift. The definition of this segment, would be to identify profiles, who have abandoned their cart, in the past seven days, and, any product left behind, with a different category than the one they usually shop for, with a size that is different from theirs. We can also narrow the segment, to only target loyal customers. Our gift giver segment, has now been created, and we can now estimate how many people are part of it. Now that we have our new segment, we want to take action and make it available for personalization across channels. In Adobe’s Real-Time CDP, we see all the destinations available for Luma, to send a segment to, both Adobe and non-Adobe applications. Let’s say we want to activate the segments for email marketing, using Adobe Campaign. Following this process, we can select the data we want to send to the email solution. In this case, we want first and last name, in addition to email. We can schedule this activation to start or end, at a particular time. And that means, that these segments will be posted and automatically updated, as per those dates. And we’re done. Later that day, Sarah rose receives a marketing email, opens it, and discovers an offer related to the product she left behind. As she clicks, her experience on the website, remains consistent, with the addition of a personalized section for gift givers. The same consistent experience, will be executed as she opens the Luma mobile app and explores content. What we’ve just shown you, is the power of Adobe’s Real-Time CDP, powered by Adobe Experience platform, where brands, can ingest data from multiple sources, merge them into a single real-time customer profile, and, deliver a consistent, relevant and personalized experience across every touchpoint. Thank you. -
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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
- 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