- Customer Journey Analytics Guide
- Release Notes
- Customer Journey Analytics overview
- Customer Journey Analytics overview
- Getting Started
- Consistency of metrics and audience membership counts between Real-time CDP and CJA
- CJA Access Control
- Customer Journey Analytics landing page
- Adobe Analytics to Customer Journey Analytics evolution
- User Guide for new Customer Journey Analytics users
- View and manage CJA usage
- Frequently asked questions
- Compare Adobe Analytics and Customer Journey Analytics
- Utilize Adobe Analytics data in Customer Journey Analytics
- Customer Journey Analytics feature support
- Compare terminology for Analytics data passed through the Analytics Source Connector
- Compare data processing across Adobe Analytics and CJA
- Virtual reporting environments and sandbox environments
- Processing Rules, VISTA and classifications versus Data Prep
- AAID, ECID, AACUSTOMID and the Analytics Source Connector
- Deletion implications
- CJA glossary
- Data Ingestion
- Connections
- Data Views
- Workspace projects
- Analysis Workspace overview
- Perform basic analysis
- Perform advanced analysis
- Projects
- Visualizations
- Panels
- Curate, Share and Schedule projects
- Attribution IQ
- Virtual Analyst
- User preferences
- Workspace FAQs
- Components
- Components overview
- Annotations
- Audiences
- Dimensions
- Metrics
- Filters
- Calculated Metrics
- Calculated metrics overview
- Calculated Metrics workflow
- Calculated metrics workflow
- Find metrics
- Build Metrics
- Metric Type and Attribution
- Build a simple “Page Views per Visits” metric
- Filtered metrics
- Stack and replace segments
- Filtered and weighted metrics
- Use functions
- Participation Metric
- Tag calculated metrics
- Approve calculated metrics
- Share calculated metrics
- Calculated Metric Manager
- Basic functions
- Advanced functions
- Date ranges
- Analytics dashboards
- Report Builder
- Cross-Channel Analytics
- Adobe integrations
- Data Governance
- Use cases
- Labs
- Troubleshooting
- CJA API
Integrate Adobe Journey Optimizer with Customer Journey Analytics
Adobe Journey Optimizer helps you deliver connected, contextual, and personalized experiences. It helps expose your customers to the next step in their customer journey.
You can import data generated by Journey Optimizer to perform advanced analysis in Customer Journey Analytics by performing the following steps:
Send data from Journey Optimizer to Adobe Experience Platform
Adobe Experience Platform serves as the central data source and link between Journey Optimizer and Customer Journey Analytics. See Get started with Datasets in the Journey Optimizer user guide for steps on how to send Journey Optimizer data to Platform as a Dataset.
Create a connection in Customer Journey Analytics
Once Journey Optimizer data is in Adobe Experience Platform, you can Create a connection based on your Journey Optimizer Dataset. Select the Dataset that you sent to Platform.
Configure the Data view to accommodate Journey Optimizer dimensions and metrics
After a connection is created, you can create one or more Data Views to configure the desired dimensions and metrics available in Customer Journey Analytics.
You can create the following metrics in a data view to achieve approximate parity with similar metrics in Journey Optimizer. See Component settings in the Data View Manager for details around how to customize dimensions and metrics.
| Metric | Description | Data View settings |
|---|---|---|
| Bounces | The number of messages that bounced | Use the schema string element _experience.customerJourneyManagement.messageDeliveryfeedback.feedbackStatus with the following settings:Component type: Metric Include exclude values: If any criteria are met Equals: bounceEquals: denylist |
| Errors | The number of messages that errored out | Use the schema string element _experience.customerJourneyManagement.messageDeliveryfeedback.feedbackStatus with the following settings:Component type: Metric Include exclude values: Equals error |
| Excludes | The number of messages excluded | Use the schema string element _experience.customerJourneyManagement.messageDeliveryfeedback.feedbackStatus with the following settings:Component type: Metric Include exclude values: Equals exclude |
| Unsubscribes | The count of unsubscribes | Use the schema string element _experience.customerJourneyManagement.messageInteraction.interactionType with the following settings:Component type: Metric Include exclude values: Equals unsubscribe |
| Clicks | The count of clicks within messages | Use the schema string element _experience.customerJourneyManagement.messageInteraction.interactionType with the following settings:Component type: Metric Include exclude values: Equals click |
| Opens | The number of opened messages | Use the schema string element _experience.customerJourneyManagement.messageInteraction.interactionType with the following settings:Component type: Metric Include exclude values: Equals open |
| Spam complaints | The count of spam complaints | Use the schema string element _experience.customerJourneyManagement.messageInteraction.interactionType with the following settings:Component type: Metric Include exclude values: Equals spam_complaint |
| Messages successfully sent | The number of messages successfully sent | Use the schema string element _experience.customerJourneyManagement.messageDeliveryfeedback.feedbackStatus with the following settings:Component type: Metric Include exclude values: Equals sent |
| Sync failures | The total number of messages that failed to sync | Use the schema string element _experience.customerJourneyManagement.messageDeliveryfeedback.messageFailure.category with the following settings:Component type: Metric Include exclude values: Equals sync |
Configure Calculated metrics using Journey Optimizer metrics
Once you have configured the desired dimensions and metrics for the Journey Optimizer dataset, you can also configure Calculated metrics for additional insights around that data. These calculated metrics are based on the above metrics created in the Data View Manager.
| Calculated metric | Description | Formula |
|---|---|---|
| Total messages sent | The total number of messages sent, successful or failed | [Messages successfully sent] + [Bounces] + [Sync failures] |
Differences in reporting between Journey Optimizer and Customer Journey Analytics
Data discrepancies between products is typically between 1-2%. Larger discrepancies between products can potentially be attributed to the following:
- Processing time for incoming data can be slightly different between products, especially for data collected within the last two hours. Use date ranges excluding today to mitigate discrepancies involving processing time.
- The calculated metric ‘Total messages sent’ does not include the ‘Retries’ metric. Data for the ‘Retries’ metric is not included in the Dataset, showing potentially lower numbers in CJA reporting versus AJO reporting. However, retry data is converged into the ‘Messages successfully sent’ or ‘Bounces’ metric. Use date ranges a week or older to mitigate discrepancies with the ‘Total messages sent’ metric between products.
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