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Can Customer Journey Analytic replace Adobe Analytics?

Adobe’s customer journey analytics platform is the newly launched Analytic tool for tracking in-depth user journeys across different channels. It is built on top of the Adobe Experience Platform and offers the same functionalities as the Adobe Analytics workspace.

When and how to use CJA?

A consumer who is interested to purchase a product would start by gathering information on it, start reading through reviews, searching for offers, best price point, and might even get few steps closer to the purchase by adding the product to the cart.

With the existing Analytics tracking in place within the website or app, the business can get an overall idea of the customer’s interest and journey.

But there is always a possibility that the user may visit a nearby store and decide not to purchase. Since the offline part of the customer journey is not known to the business, they might already start investing in various solutions such as retargeting to give the consumer an extra nudge towards the final step in conversion.

These decisions would be made based on an incomplete set of data.

For this particular use case choosing Adobe analytics as a data analysis solution wouldn’t be enough.

To get a holistic view of the entire customer journey, you can start using CJA.

It is includes tracking of both online and offline channel data as well. CJA can work with multiple data sources. It can stitch the data from different channels such as point of sales, CRM, web, app, etc. using a common key, which is termed as ‘Person ID’.

It is built on top AEP and has similar functionalities and capabilities to the Adobe analytics workspace. But it is more flexible than Adobe Analytics.

Terminology Updates:

Customer Journey Analytics

Adobe Analytics

*The standards metrics have been renamed but they function the same as before.

The definition of session expiry has changed a bit. So if a user spends 20 minutes on the website and ends the session, and reaches out to the call center to place the order, the time spent or the call duration would also be recorded within the same session.

Therefore 30 minutes of inactivity would no longer be an accurate definition of session expiry.

Not Supported:

The data is measured as ‘Dimensions’ and ‘Metrics’.

The metrics are no longer classified as ‘Success events’. So the shopping cart events (prodView, scAdd, scRemove, scView, scOpen, scCheckout, Purchase) are not supported.

Since the variables are broadly classified as ‘Dimension’ and ‘Metrics’. eVars, props, list prop no longer supported. Instead of list prop, string arrays can be used.

Why is CJA better than Adobe Analytics?

1. Unlimited Variable:

It’s not restricted to a fixed number of eVars and props.

2. Alter historical data:

At any point, data can be deleted or modified in AEP.

3. Cross-report-suite data:

Can create combined online and offline channel data.

4. Sequential data analyses:

Can view and analyze data sequence.

For example, you would know if the user journey started from an online channel and then progressed to an offline channel and then back to the online channel. This sequence can easily be analyzed.

5. Unlimited row processing:

Historically you could process around 2.5 billion rows of data. But now the number of rows processed is unlimited.

Architecture Workflow:

Step #1: Data Integration

The first step is to pull the data into AEP. Data from Adobe SDK, Adobe solutions, 3rd party solutions, ETL can be pulled into AEP by streamlining or batch files upload or through connected data sources such as Adobe Launch.

Step #2: Structured Data

The data collected within the Data Lake needs to be structured as per the XDM (Experience Data Model) schema.

Once the dataset is defined in AEP, it is ready to use in CJA.

Step #3: Choose ID

You can define an identifiable parameter that can tie the data from different platforms together.

Step #4: Create a connection

Connections can be created by selecting & configuring the data set which were created in the Adobe Experience platform(Refer step 2)

Multiple connection can be created and stitched together using the common key, also known as 'Person ID'.

Step #5: Perform Analysis

Once the connections have been created successfully, you can start creating report for basic or advance analysis.

Multiple connections can easily be compared against each other.

Even if the connection do not have a common 'Person ID', you can still perform basic analysis within a single report by comparing the data source, source & medium, trending online & offline store KPIs etc.


Customer Journey Analytics is a complete package that offers valuable data and insights from both online and offline channels. This does aid in making accurate decisions.

Unlike Adobe analytics. you would have the entire view of the customer’s journey.

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