Platform Architecture · Adobe Analytics & CJA

Most organizations that moved to CJA moved the problem with them.

Customer Journey Analytics is a genuinely more capable platform than Adobe Analytics. Whether it returns on that capability depends almost entirely on what happened before and during the migration: whether the XDM schema was designed from the organization's data requirements, whether Person ID strategy was decided before Connection configuration, and whether Data View governance was built to hold.

Adobe Experience Platform
Adobe Analytics
Still active for most enterprise clients. No public sunset date. All new capabilities shipping to CJA only. Infrastructure deprecations accelerating through 2026.
Customer Journey Analytics (CJA)
Adobe's forward analytics platform. Built on AEP. XDM schema-driven. Connections, Data Views, Analysis Workspace. Reached feature parity with AA in 2025.
Adobe Experience Platform (AEP)
The data foundation. XDM schemas, datasets, Real-Time Customer Profile, Data Lake. CJA Connections pull directly from AEP datasets.
Adobe Web SDK + TagsReplaces AppMeasurement
Adobe's recommended collection layer. Replaces AppMeasurement. Streams XDM-native data via Datastreams to AEP. Critical path for clean CJA architecture.
Data Insights AgentAI · GA June 2025
AI assistant in CJA for natural-language analysis, visualization generation, and anomaly exploration. GA June 2025. Queries the Data View.
Adobe Journey Optimizer (AJO)
Omnichannel activation on AEP. CJA audiences activate into AJO. Journey Agent (AI) in GA September 2025. Downstream of the CJA signal layer.
01Who this is for

Three states — same underlying architecture problem.

Organizations in the Adobe analytics stack arrive at the same set of architecture decisions from different points in the journey. The decisions are identical regardless of where you're starting from.

Still on Adobe Analytics

Planning the move to CJA and want the architecture designed before implementation starts

The XDM schema, Person ID strategy, and Data View governance need to be decided before a line of Web SDK code is written. Organizations that skip this design phase spend the first year in CJA correcting architecture under production pressure.

Mid-migration

In CJA but running Adobe Analytics in parallel, and the CJA numbers don't match AA yet

The dual-running state has a cost: two implementations, two data models, a team that has to maintain both. The faster it resolves, the lower the cost. Resolution requires the architecture decisions the migration started without.

Already in CJA

Landed in CJA and the platform isn't returning what it was bought to deliver

This is the most common state. CJA is live. The Data Insights Agent is available. The schema inherited from the AA migration doesn't support the analysis the platform is capable of. And nobody wants to rebuild it now.

02Why CJA underdelivers

CJA is more capable than Adobe Analytics. The architecture that makes that capability available is what most migrations didn't build.

A well-architected CJA implementation can answer questions that were structurally impossible in Adobe Analytics — cross-channel journey analysis, person-level attribution, direct integration of offline and CRM data.

The most common post-migration state: CJA is live, the Source Connector pulled in AA historical data, the Data Views mirror the old AA report suites, and the team is waiting for the cross-channel insight the platform was bought to produce. That analysis isn't available — because the schema doesn't support it.

XDM schema design determines every dimension and metric available. Person ID strategy determines how journeys stitch across devices. Data View governance determines attribution models and reporting alignment.

These three decisions dictate CJA's analytical ceiling. And most organizations make them by default during migration.

03The architecture we govern

Every layer of the CJA stack has an architecture dependency in the layer beneath it.

The six layers of the Adobe measurement stack each have specific architecture decisions that determine whether the layer above them returns what it's capable of.

Collection · Client-side
Adobe Tags (Launch)

Deploys Web SDK and manages data elements, rules, and publishing. Configuration determines what data the Web SDK collects and how it's structured before hitting the Datastream.

Tag governanceData element designWeb SDK configuration
Collection · AEP path
Adobe Web SDK

Adobe's replacement for AppMeasurement. Streams XDM-native data via Datastreams to AEP. The critical difference: Web SDK produces data in the organization's XDM schema, not in legacy schema.

Migration architectureDatastream configXDM field mapping
Data model · Foundation
XDM Schema · AEP

The data model that structures everything in AEP. Every dimension and metric in CJA Data Views traces to an XDM field. Fields cannot be removed once data flows into them.

Schema architectureField group selectionSchema governance
Identity · Cross-device
Person ID · Identity

The identifier CJA uses to stitch events into a coherent customer journey across devices, channels, and time. Determines what cross-channel analysis is possible.

Person ID strategyIdentity namespacesCross-device stitching
Configuration · Governance
Connection + Data View

The Connection links AEP datasets to CJA. The Data View is the reporting governance layer — controlling dimensions, metrics, attribution, persistence, and session definitions.

Dataset joinsComponent governanceAttribution models
Analysis · AI features
Workspace · AI

CJA's analysis environment and AI features (Data Insights Agent, Intelligent Captions). All AI features query the Data View — output quality is determined entirely by the architecture beneath.

Workspace governanceComponent libraryAI readiness
04What goes wrong

The architecture gaps that show up as analysis problems.

These are the consistent patterns across Adobe Analytics and CJA environments — the decisions that weren't made explicitly, and that appear as data quality or reporting problems months or years later.

01
Variable allocation has drifted from what reports assume
eVar persistence and allocation settings were configured at go-live. Business logic has changed — but the variable settings haven't. Reports are calculating attribution against rules that no longer reflect how the business thinks about credit.
02
The schema was designed to replicate AA — not to enable CJA's capabilities
The XDM schema was built by mapping AA props and eVars into custom fields. The result inherits AA's constraints and makes it structurally impossible to take advantage of CJA's cross-channel and multi-dataset capabilities.
03
Cross-device journeys break at every authentication boundary
The CJA Connection was configured with ECID as the Person ID because it was the most available identifier. Cross-device analysis shows separate journeys for the same customer on desktop and mobile.
04
CJA and AA report different numbers for the same metric
Adobe Analytics uses Last Touch attribution by default. CJA uses Same Touch on dimensions by default. Attribution models weren't mapped deliberately when the Data View was built. The numbers diverge.
05
Web SDK was deployed — but it's still producing AA-schema data
Web SDK was implemented by mapping existing AA variables into XDM through Tags rules. The collection layer is modern. The data model it's producing maps to the same legacy schema as AppMeasurement.
06
Consent architecture isn't enforced at the data level
AEP's data governance framework was configured during initial setup. New datasets were added without inheriting the governance model. Consent captured in the CMP doesn't propagate consistently through the AEP data pipeline.
05CJA's AI layer

The Data Insights Agent is a force multiplier. What it multiplies depends on the Data View.

Every AI feature in CJA queries the Data View. If the underlying data has schema gaps, identity fragmentation, or unresolved attribution mismatches, those issues appear in the AI output as confidently as accurate insights do. The AI layer doesn't fix architecture gaps upstream of it.

01AI Querying

Data Insights Agent

Natural-language queries, visualization generation, anomaly exploration. GA June 2025. Output quality is determined by Data View governance and XDM schema design.

02AI Narrative

Intelligent Captions

Auto-generated narratives for Line, Area, Bar, Flow, and Fallout visualizations. Inherits the attribution model and dimension definitions of the Data View it's reading from.

03AI Detection

Anomaly Detection

Statistical anomaly detection across metrics. More reliable when metric definitions are governed and stable — schema drift and inconsistent variable allocation produce false positives.

06How we engage

Four entry points — one underlying architecture problem.

The right starting point depends on where the gaps are showing up. All four paths begin with the Assessment, which maps the current state of the environment.

01Pre-migration

Pre-migration architecture design

XDM schema, Person ID strategy, and Data View governance — designed before implementation starts. The Assessment maps the current AA environment against CJA requirements.

What this produces
Schema designIdentity strategyData View planning
  • Implementation team has clear blueprints
  • Migration takes one pass instead of two
02Audit

AA environment audit

For organizations where Adobe Analytics is still the production environment. Variable allocation review, implementation documentation, eVar and prop governance, Solution Design Reference.

What this produces
Variable allocationSDR updateProp governance
  • Trustworthy production environment
  • Clean baseline for future migration
03Correction

CJA architecture correction

For organizations already in CJA where the architecture didn't land correctly. XDM schema assessment, Person ID strategy correction, Data View component governance, attribution model alignment.

What this produces
Schema correctionIdentity stitchingAttribution alignment
  • Capabilities unlocked without full rebuild
  • CJA returns on its promised value
04AEP Foundation

Full AEP measurement layer

For organizations with CJA, AJO, and RTCDP in scope simultaneously. XDM schema designed to support analytics, activation, and journey orchestration from the same data model.

What this produces
Omnichannel schemaRTCDP integrationAJO journeys
  • One data model feeding all AEP apps
  • Consistent audience activation

If CJA isn't returning what it was bought to deliver — the architecture decisions are where to look first.

The Measurement Architecture Assessment maps the current state of the Adobe environment: XDM schema design, Person ID strategy, Data View governance, Web SDK implementation status, and the gap to be closed.

Start here
The Assessment is calibrated to the specific Adobe environment and where the gaps are showing up — not a generic analytics review. The output is a specific architecture diagnosis.