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Feature

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Customer Journey Analytics allows you to combine data from multiple report suites as if they were a single report suite in �۶���Ƶ Analytics.

Customer Journey Analytics is combined with Experience Platform’s ability to hold all kinds of data schemas and types. Using Experience Data Model (XDM), data can be uniformly represented and organized, ready for combination and exploration. �۶���Ƶ Analytics is predominantly focused on web and mobile analytics data with some capabilities to import data.

Customer Journey Analytics supports the seamless combination of device-specific datasets from unauthenticated and authenticated sessions. Customer Journey Analytics offers to backfill historical data to known devices. In �۶���Ƶ Analytics, this capability is limited to a single report suite and the use of a device graph.

Customer Journey Analytics provides greater flexibility when using dimensions:

• Custom numeric-based dimensions: Create your own numeric-based dimensions within a data view.
• Sort string-based dimensions: Sort string-based dimensions alphabetically in a freeform table.

In �۶���Ƶ Analytics, only a handful of built-in numeric dimensions were available, and sorting by string-based dimensions was not possible.

Derived fields allow for report-time transformations to your data. Data can be combined, corrected, or created on the fly and these transformations apply retroactively to all reporting.

Enhanced security and privacy options - HIPAA readiness

Customer Journey Analytics is HIPAA ready and offers additional security options for regulation compliance. �۶���Ƶ Analytics is not HIPAA ready.

Customer Journey Analytics can evaluate the lift and confidence of any experiment from any data source defined as part of a connection. This evaluation allows you to understand cause-and-effect relationships between customer interactions spanning any channel. Analytics is limited to experimentation analysis through A4T.

Forecasting is an AI/ML capability that includes a statistical prediction for time-series-related data based on the historical data that already exists in Customer Journey Analytics. Forecasts can appear in freeform tables and line graph visualizations.

Guided analysis enables users to self-serve high quality data and insights about the customer journey through guided workflows, built on the cross-channel data of Customer Journey Analytics.

Intelligent captions use advanced Machine Learning and Generative AI to provide valuable natural-language insights for Workspace visualizations. The initial release provides auto-generated insights for the Line visualization.

Data views in Customer Journey Analytics allow you to further interpret data from a connection. You can alter or remove data without changing your implementation, use substrings to manipulate dimensions, create metrics from any value, or filter subevents. All of these transformations are done non-destructively. �۶���Ƶ Analytics provides limited capabilities through virtual report suites and custom session length.

The BI Extension lets you connect CJA directly to popular BI visualization tools such as PowerBI or Tableau. By using this extension, you can have your BI reports precisely match what you see in Analysis Workspace and other CJA reporting interfaces. This is a much easier way to get BI reporting for CJA without the need to recreate reports/metrics from raw data.

Using the Data Distiller option, Customer Journey Analytics can remove the limitations of data collected on �۶���Ƶ’s backend processing. You can modify your data with SQL, create values and datasets unique to your business and continue to explore. Analytics does not support any kind of SQL access to its data.

Stitching is a powerful feature that elevates an event dataset’s suitability for cross-channel analysis. Cross-channel analysis is a main use case that Customer Journey Analytics can handle, allowing you to seamlessly combine and run reports on multiple datasets from different channels, based on a common identifier (person ID).

Customer Journey Analytics dimensions are unlimited; values can be numeric, text, objects, lists, or mixtures of all. Dimensions can be nested or hierarchical.
By contrast, �۶���Ƶ Analytics supports up to a maximum of 75 props and 250 eVars.

Customer Journey Analytics supports unlimited unique values or dimension items that can be reported on within a single dimension.

There are no cardinality limits on a dimension, allowing for any unique value to appear and be counted.

This approach removes reporting and analysis limitations that can exist with large-scale �۶���Ƶ Analytics implementations, resulting in Low Traffic labels.

In Customer Journey Analytics, it is possible to see a Uniques Exceeded label, but these occur far less frequently and can be mitigated by applying a filter or segment to the data.

�۶���Ƶ Analytics Feature

Notes on CJA support

Full support

Full support

Full support. Any existing calculated metric in the traditional Analysis Workspace is not ported to Customer Journey Analytics.

Full support. Calendar events have been implemented as Annotations in Workspace.

Full support

Full support

Full support

All date range functionality is supported.

Full support. Customer Journey Analytics uses XDM and supports unlimited dimensions. Customer Journey Analytics is not tied to the custom eVars or props of traditional �۶���Ƶ Analytics.

Full support; note that GDPR is now handled in coordination with �۶���Ƶ Experience Platform. Customer Journey Analytics inherits whatever data changes Experience Platform makes to underlying datasets.

Full support via Experimentation panel

Full support. Customer Journey Analytics uses XDM and supports unlimited string arrays which can be used similarly to listVars.

Full support via binding dimensions and binding metrics

Full support; Customer Journey Analytics uses the Experience Data Model (XDM) and supports unlimited metrics and is not tied to the custom success events of �۶���Ƶ Analytics. Some standard metrics have been renamed from �۶���Ƶ Analytics: Visitors = People, Visits = Sessions, Hits = Events.

Full support.

Full support

Full support for the following panels: Blank panel, Attribution, Freeform, Quick insights, and Next or previous item.

Full Support

Full Support

Full Support

Full Support; Customer Journey Analytics relies exclusively on Report Time Processing.

Full Support; Available through the .

Full Support

Full Support. Now called “Filters” - note that any existing segments in traditional Analysis Workspace are not ported to Customer Journey Analytics.

Streaming media data are available using the Analytics source connector as part of the Media Concurrent Viewers panel and the Media Playback Time Spent panel in Workspace.

Full support

Full Support. Now called Data views.

Full Support. Now part of Data views.

Supported for both Analytics source connector-based datasets and for datasets generated by the WebSDK. Refer to documentation on which Analytics variables are supported via ADC. If you use Experience Platform Web SDK data collection, Device and dimensions based on the Device lookup are not currently supported. Future support is planned. For adding device and browser lookups to your Web SDK datastream, refer to this documentation

Feature

Notes

You can collect historical data for AMO IDs and EF IDs for use in Customer Journey Analytics.

The process of using alerts in Customer Journey Analytics is nearly identical to using alerts in �۶���Ƶ Analytics.

However, due to the timing of data collection in Customer Journey Analytics, hourly alerts are not available. In Customer Journey Analytics, alerts can be configured for daily, weekly, or monthly.

The integration between �۶���Ƶ Customer Journey Analytics and Target provides powerful analysis and timesaving tools for your optimization program.

Supported if licensed with �۶���Ƶ’s Customer Data Platform or Journey Optimizer products. Audience Publishing sends audiences to Real-time Customer Profile in Experience Platform.

Now called “Lookup Datasets”. Classifications used in Analytics can be imported to the Experience Platform and Customer Journey Analytics using the Analytics Classifications Source Connector. Lookup datasets can also be uploaded to Experience Platform directly and made available in Customer Journey Analytics.

Supported using substrings in Customer Journey Analytics. Uses string manipulations at report time rather than lookup datasets.

Session length can be configured through Session settings in a Data view. See Session settings for more information.
Handling of mobile background events is supported through the �۶���Ƶ Experience Platform Mobile SDK. See for more information.

Supported as part of formatting a metric component in a data view.

Now called “Profile Datasets”, they do not get automatically imported from Experience Cloud, but must be uploaded to Experience Platform before they are available in Customer Journey Analytics.

First-generation data export of datasets is available through the Experience Platform Data Access API and through Experience Platform Destinations. These options provide event/row level export of all data collected or ingested into Experience Platform Data Lake. Post-process data columns are not available because post columns are computed at query time. Export of post columns is available through reporting.

Customer Journey Analytics Full Table Export is the evolution of Data Warehouse reports in �۶���Ƶ Analytics, with many new, often-requested features that are not available in Data Warehouse today.

Supported (Entries and Exits are now called Session Starts and Session Ends) and are calculated in a slightly different way.

eVars are no longer part of Customer Journey Analytics. However, persistence settings are now part of Data Views and are available for all dimensions. Keep in mind that persistence is based on report time processing, not data collection processing. Dimensions set within Data Views are limited to a 90-day max persistence and do not support unlimited persistence.

Through Graph-based Stitching, you can harness the power of the identity graph in �۶���Ƶ Experience Platform Identity Service to elevate datasets to their preferred identity.

The process of using alerts in Customer Journey Analytics is nearly identical to using alerts in �۶���Ƶ Analytics. However, there are important differences.

For Customer Journey Analytics customers using the Analytics source connector to populate data from �۶���Ƶ Analytics into Customer Journey Analytics: IP obfuscation settings applied in �۶���Ƶ Analytics flow through to your Customer Journey Analytics data. You can control these settings in �۶���Ƶ Analytics as needed.

For Customer Journey Analytics customers using Experience Platform Web SDK to populate data into Platform and Customer Journey Analytics directly. You can use Data Prep for Data Collection in Platform to configure rules that obfuscates the IP address based on your company’s requirements.

When using the Analytics source connector, Marketing Channels data flows into Customer Journey Analytics through that connector. Marketing Channel rules are configured in traditional �۶���Ƶ Analytics and some rules are not supported. See Customer Journey Analytics Marketing Channels for more information.
For WebSDK implementations, report-time marketing channel processing rules are supported through Derived fields.

Full Support via binding dimensions and binding metrics

Now configured on metrics within Data Views. Metric deduplication happens at the person or session level rather than the Dataset, Data view, or Connection level.

Formerly accomplished using the Visit Number dimension. New vs. Repeat sessions are supported with a 13-month lookback window.

Supported using �۶���Ƶ Experience Platform Data Prep functionality as well as derived fields for both WebSDK based datasets and data from the Analytics source connector.

Within the Experience Platform, users can use an array of objects within a dataset schema to satisfy this use case. Within Customer Journey Analytics, customers can use any number of product variables and are not restricted to a single variable as in �۶���Ƶ Analytics.

Project sharing is only supported between users of Customer Journey Analytics - there is not project sharing between Customer Journey Analytics and the traditional Analysis Workspace.

Supported with a new Office 365 plugin for Excel.

Customer Journey Analytics distinguishes between �۶���Ƶ Admin Console product admins, product profile admins, and users. Only product admins can Create/update/delete Connections, Projects, Filters, or Calculated Metrics that were created by other users, while product admins and product profile admins can edit Data views. Additional user permissions are available for things like creating calculated metrics, filters, or annotations.

All Workspace visualizations are supported except for the Map visualization.

Supported for event datasets containing identity information. See Stitching.

Feature

Notes

Blank Panel, Attribution Panel, Freeform Panel, and Quick Insights are fully supported. The Segment Comparison and Analytics for Target (A4T) panels are not supported.

Feature

Notes

Support is planned.

Support is planned.

Support is planned.

Support is planned.

Support is planned.

Feature

Notes

Support is not yet planned.