Journey Optimizer integration with Customer Journey Analytics provides an holistic view of all your journeys with automated report distribution and custom visualizations of the data.
After creating your journey in Journey Optimizer, you can import your customer data to Customer Journey Analytics to start reports and understand the impact of every interaction a customer has with your journeys.
In addition to this integration, you can also export the content of Adobe Journey Optimizer datasets to cloud storage locations and use this information for reporting or analysis purposes. Learn how to export datasets to cloud storage locations
Note that the datasets export feature is currently in beta and available to all Adobe Journey Optimizer users. Please work with your Adobe representative on getting access to Destinations if you do not already have access.
Before using Customer Journey Analytics for your journeys, you must first configure this integration:
Create a connection in Customer Journey Analytics with the Dataset you want to send to Adobe Experience Platform.
The following Journey Optimizer can be configured:
Create a data view to configure the dimensions and metrics you want to use for your report.
You can create Journey Optimizer specific metrics to better reflect your journeys’ data. Learn more
Using Journey Optimizer with Customer Journey Analytics might lead to some discrepancy in reporting data caused by:
Both Journey Optimizer and Customer Journey Analytics sync data from Azure Data Lake Storage (ADLS) for reporting.
Processing time for incoming data can be slightly different between products. Due to this, data may not match when displaying reports from a given date to the current day. To reduce discrepancy, use date ranges excluding the current day.
In Journey Optimizer reports, Sent metric also includes Retry metric.
Retries will not be included in Sent metric in Customer Journey Analytics. This will cause Customer Journey Analytics Sent metrics to show lower values than Journey Optimizer. However, retry data is converged into the Messages successfully sent or Bounces metric.
To reduce discrepancy, use date ranges from a week ago or even later.
Reports are being served from a different datasource.
This could lead to between 1-2% data discrepancies between products.