How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut


How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

How to Align Adobe RT-CDP Capabilities Across Your Organization

March 11, 2022, Bryan Rekrut

We hear from a lot of clients who are ready to move forward with CDP adoption but aren’t sure how to deploy the CDP in their organization. In a recent article, we discussed What a Successful CDP Implementation Actually Looks Like at a higher level. Let’s take a more focused view on how to align CDP capabilities across an organization with a specific implementation: Adobe’s Real-Time Customer Data Platform (RT-CDP).

With any CDP implementation, there must be cross-functional alignment across IT, marketing, and analytics. The main capabilities to consider, as noted in the figure below, are identity management, data modeling, unified profile, and segmentation.

adobe

Identity management

One of the most powerful capabilities within the foundation layer of Adobe RT-CDP is ingesting identity fields across numerous sources to create an owned identity graph and holistic customer profile. The CDP links data fragments together based on identity fields defined in the inbound data collection flows to create an identity graph. The linkage of identity fields should be managed in the CDP, with the Adobe RTCDP having clear ownership of this capability. A CDP is not an identity resolution solution, so consider using an external standalone identity solution to support the CDP.

Data modeling and collection

Each of the fragments of data ingested into Adobe RT-CDP need to be evaluated as either record-level data against the experience data model (XDM) individual profile (data which does not change that often) or XDM experience event (data which is based upon the timestamp of the event type). Data ingested into Adobe RT-CDP does not need to match the source data format; it can be formatted in an object-oriented manner instead of conforming to traditional relational database tables.

Unified profile view

Cross-functional team alignment on the identity management and data modeling and collection capabilities will help form a common unified profile within the Adobe RT-CDP. A key consideration with the unified profile view is to understand what data attributes are needed for the activation systems. Options include emailhash only, emailhash with record, and event-level data attributes. The attributes you need will vary based upon the activation channel/system. 

Segmentation

The last main component to organizational alignment with the Adobe RT-CDP is segmentation logic. A single segmentation definition based on web data and first-party offline data can be shared with Adobe Target, Adobe Campaign Standard, and paid media channels to create organizational alignment and avoid siloed segments per activation or channel. Adobe RT-CDP segmentation logic is created within one component, then shared as micro-segmented data for use in activation channels.

Additional considerations

Additional items to consider when moving forward with an Adobe RT-CDP implementation are query service, Customer Journey Analytics, and Data Science workspace.

The Adobe Query service allows data to be ingested into the Adobe RT-CDP data lake without having to predefine data aggregates externally. Adobe Query is a powerful engine which has Adobe-defined functions, Spark SQL functions, and prepared statements. This gives users the flexibility to build targeted data sets which can be made available within the Adobe RT-CDP profile store for segmentation and/or activation.   

Customer Journey Analytics allows you to use online and offline data from the Adobe RT-CDP data lake to build reports. The result of these reports can help create targeted segments within Adobe RT-CDP.

The Data Science workspace of Adobe RT-CDP is an additional add-on feature that assists with modeling. Users can leverage pre-built data science models or build their own model to meet unique business needs. While the additional add-ons to Adobe RT-CDP will help realize additional value, getting the foundational layer alignment across the organization is key.  These key foundational layers, which should have clear ownership within the Adobe RT-CDP, include identity management, data collection, unified profile, and segmentation.

To learn more about Adobe RT-CDP and its capabilities, please join me during the Adobe Summit Braindate using the portal here.

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