This article is a continuation of my original blog post on Customer Journey Analytics (CJA) pitfalls and how to avoid them. If you haven't already, I recommend reading Part I to gain a comprehensive understanding of the challenges and solutions discussed in this series.

This blog post aims to identify potential issues to consider when using CJA and provide practical tips and strategies to avoid them. By understanding these pitfalls and following best practices, you can ensure that the insights derived from CJA are accurate, reliable, and valuable to your business.

In this blog post, updated as of September 2023, I will guide you on a comprehensive learning journey to introduce you to Customer Journey Analytics (CJA). My goal is to familiarize you with the platform's features and capabilities and provide valuable insights and knowledge to help you fully utiliz...

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...

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...