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The starting point for AEP is to understand what the platform will be used for immediately and in the long run. It is essential to conduct in-depth discovery around the business use cases as well as the data needed to support them. In this phase, we will spend time with stakeholders across the organization to understand the current state and the needs for the future state once the platform is stood up. Another aspect of the discovery is spent with the IT and Data Engineering team to map out the available data points and how to bring them into the platform. Our team will document all the business cases and data requirements that will serve as our guiding document as we transition into the design phase. 

AEP is a schema-based platform which means that data needs to be prepped before reaching the platform. Contrary to relational databases, AEP will only ingest data that fits the specs defined in each schema. Data prep can be a heavy lift for clients depending on their current state of data maturity. Our team will work with clients on the best practices, data models, file formats, and data fields. These best practices will be in line with the use cases that we gather in the discovery phase. 

As the business requirements are finalized and signed off, our team will work on designing the data model within AEP. This process will consist of identifying the data sources, key schemas and mixins needed as well as the identity groups and namespaces.  Our team will document all the data mappings and work with the client on running initial test files to validate the schema designs and identity stitching. 

AEP will be a key building block of the client’s marketing technology stack. Our team will architect how the platform will be configured but more importantly how data will enter the platform and be activated on. All design aspects from real-time pipelines, batch uploads, and data flows will be designed and agreed on with the client. This will be documented in a detailed solution design document that captures the use cases from the business requirements document and showcases how they will be executed within the platform. 

If all pieces fall into place, data ingestion into AEP will be a breeze. When it comes to data ingestion, it happens in phases. Post-design, our team will work with the client on testing sample data, file formats and ingestion frequency. Data will be ingested into different sandboxes before it is finally loaded into the production instance. At this stage, our team will conduct in-depth testing and validation to confirm that data is loaded properly to ensure a comprehensive and accurate customer profile for segmentation and activation. 

Adobe’s Real-time Customer Data Platform (RT-CDP) runs on top of the Unified Profile. When standing up the CDP, all steps from data prep to design, modeling, architecture, and data ingestion need to be in place for the CDP to be operational. Operating the RTCDP is split into two phases: Audience Segmentation and Activation. Segmentation might not always be attainable through AEP’s Segment Builder UI. For advanced segmentation, audiences are created through API or through the query service. Digital Strategist, Data Architect and Data Engineer support the audience segmentation, destination enablement and audience activation. 

Customer Journey Analytics (CJA) can be described as bring your own data (BYOD) into Analysis Workspace (adopted from Adobe Analytics). CJA is a powerful reporting, dashboarding and analysis tool that runs on top of AEP’s datasets. Unlike RTCDP and AJO, CJA doesn’t run on top of the unified profile. It is a common misconception, but this gives CJA an edge to mold the data, identity and stitching needed for a given use case and analysis that takes advantage of the AEP Data Lake. We offer guidance on best use cases to implement within CJA as well as the right resources to implement the data views and connections to power up a CJA dashboard. 

Adobe Journey Optimizer (AJO), recently upgraded from Journey Orchestration, is an all-in-one comprehensive marketing orchestration tool that runs on top of the unified profile. AJO has its own email and push notification engines allowing it to run independently of other marketing automation tools. It also has the option to enable offer decisioning capabilities. Since AJO runs on top of the unified profile, it is crucial that all design and data modeling is setup properly to enable all the customer journeys, transactional triggers, and marketing campaigns.