This post serves as a high-level guide to ingesting data into Customer Journey Analytics (CJA) using Adobe Experience Platform (AEP) datasets. By connecting to CJA via Connections, AEP datasets provide a comprehensive view of customers' attributes, journeys, and behaviors. The post provides an overv...

Creating a Connection in CJA involves several steps. After completing the Connection process, you can perform analysis and gain insights using the CJA workspace built on top of the AEP. CJA helps you make informed decisions by providing data that helps you understand your customers and their journey...

To fully leverage CJA, it is important to ensure that the data model on AEP is robust and that the data used is at the appropriate level of granularity. This means that data brought into CJA should be structured suitably for the intended analysis. To achieve this, it is essential to establish a stro...

Please note the Best Practices guidance with Adobe Analytics Attribution IQ capabilities is to not have Direct and Internal/Session Refresh channels anymore:https://experienceleague.adobe.com/docs/analytics/components/marketing-channels/mchannel-best-practices.html?lang=en Check out the Marketing Ch...

The Adobe Experience Platform offers a range of tools for manipulating data throughout the entire data value chain. This blog post provides a high-level overview of Data Prep (Mapper), Data Distiller, CJA Derived Fields, and CJA Component Settings.

This blog post provides a detailed framework for decision-making when it comes to using derived fields in CJA. It covers key concepts to consider when manipulating data and creating custom derivative fields.

Unleashing the true potential of Customer Journey Analytics (CJA) requires an understanding of derived fields functionality. In this blog post, we explore some of the most compelling use cases of derived fields in CJA. Read on to learn how to tap into the transformative power of derived fields.

This blog post explores the fundamental role of user-defined filters in Customer Journey Analytics (CJA). By utilizing filters, you can effectively sift through vast amounts of data to identify relevant information and eliminate noise. Additionally, this post delves into the benefits of layering seq...

@Jennifer_Dungan is correct - this is a scenario of the Orders metrics having different contexts when applied at different dimension levels (Top Line vs. Product line item level). Conceptually in the case of orders where the metrics are dually applied at a per-product line item level AND against cor...

This blog post discusses how to handle "No Value" entries in CJA. It covers available methods for administrators to mitigate them in the Data View component settings and at the user level in workspace projects.