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Should you buy Adobe Analytics or Customer Journey Analytics for Web Analytics use cases today?

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The market for web analytics tools is going through some big changes right now. On one hand, Google has officially announced to sunset Universal Analytics (also known as “the ‘good’ Google Analytics”) next year in favor of the universally hated GA 4. On the other hand, Adobe is heavily promoting their new tool Customer Journey Analytics, both to new and existing Adobe customers.

There is no doubt that, at some unannounced point in the future, Customer Journey Analytics will become Adobe’s only analytics tool. However, there is one important detail about Customer Journey Analytics that we need to keep in mind: It is not a dedicated web analytics tool like good old Adobe Analytics. Customer Journey Analytics is built to handle data from all sources you can think of, not just websites and apps. Because of that, Adobe Analytics still has some unique features, like the Visitor Profile, that are specifically designed to help companies analyze user behavior on digital platforms, like websites and apps.

This situation evokes a couple of questions, most importantly: What should new customers buy today? And should existing Adobe Analytics customers start migrating to Customer Journey Analytics already? I’ve given some comparisons and recommendations in the past but always faced the same challenge when giving advise: The speed with which Adobe releases new features for Customer Journey Analytics and incorporates customer feedback may change my recommendation with every new release.

By now, many of my original requests and wishes have already been built into the product. I once wrote a post about Props in Adobe Analytics that included a wish list for features which, by now, have become reality in Customer Journey Analytics. And on top of the things we always wanted to do in Adobe Analytics, Customer Journey Analytics has some super exciting features that we never dared to dream about. While you can’t really go wrong with either tool, every new release has the potential to change what I would recommend for most companies.

This post tries to solve the challenge of recommending one Adobe tool over the other. Below, you will find a handful of items:

  • A list of unique Adobe Analytics features
  • A list of unique Customer Journey Analytics features (which, in my view, hold value for web analytics use cases)
  • A recommendation which tool to buy for web analytics today
  • A list of previously unique features that are now available in both tools
  • A wish list for new features in Customer Journey Analytics

With every new release of either tool I will continuously update this post to reflect any new features until Customer Journey Analytics becomes my general recommendation. If there is any post on this blog that is worth revisiting it is definitely this one! So, let’s start with the first list.

Adobe Analytics’ unique features

This list shows all the features that, in my humble opinion, hold a lot of value for any web analytics tool and are not (yet) available in Customer Journey Analytics.

  • The visitor profile: Having the option to use a “Visitor/Original Value” dimension that holds the first ever known value for a user, even if it lies outside the reporting and attribution window
  • Visit Number dimension: Being able to identify the first/second/nth session of a user (a basic version of first and return sessions is now available in CJA)
  • Domain dimension: Get the visitor’s ISP or network information from their IP address
  • Hit depth dimension: Identify the first/second/nth event of a session
  • Time Prior to Event: Answering when in a session an event has happened
  • Days since last Visit: How much time has passed since the last session of a given user
  • Entries/exits metrics: Counts how often a given dimension item was the first or last value in a session
  • Counter eVars: Being able to define a dimension in a given scope that increments and decrements based on rules
  • Activity Map: A dedicated user interface that overlays websites to show what users clicked on and some additional reports
  • Integrations: Offering native integrations to marketing tools like Google Ads and others
  • Data Sources: Offer a way to import summary-level data without additional cost and without inflating session/user count
  • Data Feeds: A way to export hit-level data with unprocessed and processed fields
  • Data Warehouse: Reporting without row/granularity limitations to enterprise-like destinations

Customer Journey Analytics’ unique features

  • Derived Fields: Create new fields and values based on existing ones
  • Attribution IQ for dimensions: On top of changing the expiration for metrics, CJA can also create new dimensions with individual expiration settings that can even be used for breakdowns
  • Type conversions: Dimensions can be used as metrics and vice versa
  • Retroactive formatting: Dimensions can be lower-cased, substringed, bucketed, exploded, or URL parsed
  • No value options: Unspecified/None values can be renamed and treated as a value
  • Filtering: Values can be completely filtered out from reporting
  • Experimentation Panel: Treat any dimension as A/B-testing-like dimensions and conduct statistical analysis on them

Which web analytics tool should you buy today?

Buy Customer Journey Analytics!

For most companies, Customer Journey Analytics will provide more value. There’s still some work to do for Adobe to bring more features into CJA, but the advantages outweigh the shortcomings for most users.

Adobe Analytics is still a very valuable and capable solution. There is no killer-feature in CJA that would require existing customers to migrate soon, but a long-term migration plan should be considered.

Previously unique AA features:

  • Classification Rule Builder: Applying a number of transformations to derive new dimension values from tracked values can now be done through derived fields (Source)
  • IP/Bot Exclusion: Be able to exclude traffic while offering a dedicated reporting section for that traffic can now be done through derived fields (Source)
  • Analytics for Target: Being able to easily analyze the impact of A/B testing, personalization, and recommendations from Target can be done through the Experimentation Panel, even though some manual work is required (Source)
  • Marketing Channels: Create dimensions based on rules incorporating multiple other dimensions can now be done through derived fields (Source)
  • Internal URL filter: Exclude internal domains from referrer reports can now be done through derived fields (Source)
  • Referrer-related dimensions: Clustering referrers into referrer types, referring domains, etc. can now be done through derived fields (Source)
  • First/Return Sessions: CJA now has a probabilistic way to determine new and return sessions, but no Visit Number equivalent yet (Source)
  • Geo lookups: This is now available in Data Streams at data collection time (Source)
  • Report Builder: While CJA had an Excel plugin for a while, it recently got updated to support scheduling and bulk management, making it practically full-featured compared to AA’s Report Builder (Source)
  • Entry/exit dimensions: CJA now supports every dimension as a entry or exit dimension using the first/last known attribution settings (Source)
  • Merchandise eVars: Dimensions in CJA can now be bound to other dimensions (Source)
  • Processing rules: More and more Experience Platform Connectors can use Data Prep functionality, which is pretty similar to Processing Rules in Adobe Analytics (Source)

Feature wish list

  • Workspace Templates: In addition to user-created templates, provide templates based on Adobe-provided AEP Field Groups. There should be a template that you can use if you follow the Adobe Analytics Field Group or the Web SDK Field Group
  • Dimension and metric templates: Similar to the previous point, provide a certain set of dimensions and metrics with different configurations depending on the used AEP Field Groups. For example, provide Entry- and Exit Page if the Web SDK field group was used
  • (Full) Pathing: While paths can be created using Query Service, I would really like to create dimensions that summarize the full/previous/following sequence of actions from a given dimension.
  • More metric de-duplication options: Allow metrics to be only counted once per Event/Session/User based on aggregations like Min, Max, Sum, Average, Median, First, Last, etc. For example, allow to configure a metric to return the most valuable item from a session or the playback position of the last watched video

Other cool posts:

  1. It’s finally time to migrate to Adobe Customer Journey Analytics
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  2. Web Analytics with Adobe’s Customer Journey Analytics, Part 7: Customer Journey Analytics Backend Configuration
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  3. Web Analytics with Adobe’s Customer Journey Analytics, Part 5: Basic Data Processing in Query Service
    This post is the fifth post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we took a look at doing the implementation using Adobe Launch, the Adobe Web SDK,...
  4. Web Analytics with Adobe’s Customer Journey Analytics, Part 6: Advanced Data Processing in Query Service
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  5. Web Analytics with Adobe’s Customer Journey Analytics, Part 8: A new home
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  6. The Visitor Profile: Adobe Analytics’ Big Advantage
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