Implementing Adobe Customer Journey Analytics (CJA) involves three key steps: Data Ingestion, Enablement and Adoption, and Activation and ROI. By following these steps, organizations can unlock the full potential of CJA and maximize their investment.

As the seasons shift, we savor the last bursts of autumn’s vibrant colors and brace for winter’s quiet arrival. Across cultures, this transition from fall to winter is a time for reflection and preparation—a reminder that change, though it may seem stark, is essential for growth and resilience.

In contrast, changes in technology, such as implementing new analytics tools, can often feel daunting, accompanied by challenges and uncertainty. In this article, I’ll outline a clear and practical approach for rolling out Adobe Customer Journey Analytics (CJA), transforming the process from a season of adjustment into an opportunity for growth, helping you maximize the value of your investment and prepare for what lies ahead.

Intro and What

Organizations are striving to gain a comprehensive view of their customers, seeking cross-channel insights and identifying friction points as customers move between devices and platforms. This insight is essential for optimizing journeys and ensuring brands provide a top-tier, personalized customer experience. CJA is a powerful tool that offers a 360-degree view of the customer journey. However, there is no magic switch that instantly unlocks the full power of CJA.

Why

Organizations may have invested in CJA but fall short of utilizing its full potential. Some limit its use to web data alone, missing the opportunity to ingest and analyze cross-channel data for a holistic view. Others face challenges in adoption, unsure of how to proceed beyond implementation due to a lack of alignment between the necessary people and processes to support the technology. In this article, I will outline a strategic approach to implementing or migrating to CJA, focusing on the critical project management aspects to ensure you have a comprehensive plan for a successful rollout.

How

To successfully adopt and roll out Adobe Customer Journey Analytics, organizations can follow a powerful three-workstream model.

This model focuses on:

1) Data Ingestion

2) Enablement and Adoption

3) Activation and ROI.

Each of these workstreams plays a critical role in unlocking the full value of CJA and ensuring a successful implementation.

1. Data Ingestion

Data Ingestion is the most important and often the most challenging step of the CJA journey.  Our goal with Data ingestion is to ensure we are ingesting Data effectively preparing and integrating data from various sources into CJA. The foundation of any robust CJA implementation begins with data. Many businesses manage multiple web and non-web data sources, such as CRM, marketing, mobile, store data, and survey data.

• The first step in the ingestion process is to identify and list the various data sources you want to integrate into CJA. If you have a short-, mid-, and long-term plan for building a holistic customer journey view, it’s important not to feel pressured to integrate all data sources in the first year. Instead, prioritize the most important ones for year one, based on your team’s capacity. Consider what you want the connected customer journey to look like in year one and beyond.

• This prioritization is crucial because it allows you to focus on unlocking the most valuable insights while aligning with your business objectives. Therefore, the second step is to prioritize the data sources in a way that aligns with both your business goals and your team's capacity.

• Once the data sources have been identified and prioritized, the actual integration work begins. This involves setting up scalable pipelines to ensure data quality and consistency across all sources during ingestion.

• After determining which data sources to ingest, it’s essential to have a common identifier across these sources to create a unified, connected view of the customer journey.

• You will also need to design schemas for each data source to ensure proper ingestion into the Adobe Experience Platform (AEP). We’ll explore schema creation, the appropriate connectors, and other technical details based on the type of data in the next article.

• Ensuring Data Quality: Just like they say, "you are what you eat," CJA is what you ingest. It’s important to establish data quality checkpoints throughout the data ingestion process. Beyond typical engineering checks, such as comparing the number of rows sent and received, you should set up checkpoints based on key customer journeys you want to track. After ingesting data, check that the expected volumes and connections between datasets are reflected accurately in CJA.

  • Example: If you are connecting web data with call center data using a hashed email ID, once the call center data is ingested, consider the journey-based insights you aim to uncover. Review the connectedness and volume of customer journeys to ensure they align with the insights you intend to extract.
  • Example: After data ingestion into Adobe CJA, auditing primary keys (e.g., hashed email IDs, customer IDs) ensures data consistency and integrity. Regularly monitor unique ID counts to detect drops or spikes, signaling potential data loss or duplication. Ensure primary keys are complete and consistent across all data sources to accurately stitch customer journeys. Use trend analysis to identify anomalies and quickly address ETL or source issues. Validate data quality by checking for null, invalid, or duplicate keys. This proactive monitoring helps maintain reliable customer journey insights.
  • Example: After data ingestion into Adobe CJA, auditing timestamps is essential for accurate journey sequencing. Incorrect timestamp formats can misplace data within the customer journey, leading to skewed insights. Regularly review the data by day and hour to ensure timestamps from different sources are aligned as expected. Validate that journey-based insights follow a logical sequence—out-of-order timestamps can disrupt the entire customer journey. Ensuring timestamp accuracy post-ingestion allows for precise tracking and analysis of customer interactions across touchpoints.
  • Example: Consistently monitoring the data refresh process across all data sources is crucial for maintaining data accuracy. It’s important to track each individual data source to detect any lags or interruptions that could prevent the data from being fully populated. Even a small delay or breakage in one source can lead to incomplete or missing data, which can impact the overall analysis and decision-making process. Regularly checking for these issues ensures that your data flows seamlessly and remains reliable for generating insights.

2. Enablement and Adoption

• Our goal in this step is to empower teams to effectively leverage cross-channel insights from CJA. Once data is ingested, the next critical phase in the rollout is enablement and adoption, where the customer journeys we brainstormed at the start of the CJA rollout plan—and the insights revealed by our ingested data—truly come to life.
• Start by considering which parts of the business will benefit from insights derived from these connected customer journeys. There are many resources available to learn how to create dashboards in CJA, but your internal Data Analytics or Center of Excellence team should be the first to be enabled. Ensure they are aware of CJA, the "new kid on the block," and how it can be leveraged to derive meaningful insights.
• Next, clearly communicate the differences between using  Adobe Analytics (AA) and CJA The table below highlights some key distinctions, and you can customize it to fit your organization’s specific needs. This comparison will help clarify the unique benefits CJA offers over traditional Adobe Analytics, particularly around cross-channel analysis.
• One advantage of driving adoption with CJA is that it shares the same UI code base with AA Analysis Workspace, making the learning curve for analysts less steep. The main task here is to provide comprehensive documentation that explains what is being enabled. Documentation stemming from the schema created during the data ingestion step will be especially useful, as it can help analysts understand how variables beyond just web engagements are mapped.
• This step involves identifying key internal and external stakeholders—particularly power users and data consumers from Adobe Analytics and other BI tools within your organization. Creating structured communication plans, such as monthly newsletters, roundtables, and workshops, will help educate and enable them to fully understand and take advantage of what CJA can do.

Major differences between Adobe Analytics & Customer Journey Analytics

3. Activation and ROI

The third step of our CJA rollout plan focuses on activation and ROI. The primary goal of this step is to demonstrate the return on investment (ROI) for our investment in CJA. It's essential to recognize that much of what we can achieve in this phase will depend on the technology stack we have to complement CJA.

Using CJA as an independent technology, disconnected from other key onsite and offsite activation platforms, is not a viable option. Instead, CJA greatly enhances our onsite and offsite personalization engines, whether they are Adobe solutions or other platforms.

To effectively prove ROI, we need to tie the actionability of insights drawn from CJA to measurable outcomes, such as revenue attained and improvements in customer experience (CX) scores. The amount of customization required will depend on the technology stack in place to facilitate audience transfer from CJA.

Based on the scale of our technology rollout plan, we can classify various use cases of CJA into crawl, walk, and run scenarios:

1. Cross-Channel Insights Reporting: One significant use case for reporting from cross-channel insights is the effective measurement of Return on Ad Spend (ROAS). With CJA, we can report conversions regardless of whether they occur on web or non-web platforms, allowing us to accurately attribute sales to the marketing channels that drove those conversions.
2. Target for CJA Reporting: Another key aspect is Target for CJA reporting, which will be particularly beneficial for your optimization and personalization teams. Target for CJA enables the reporting of results from experimentation activities, focusing on conversions that occur as a result. By leveraging the Target experiement data ingested into CJA, this functionality allows teams to attribute conversions and engagement to specific experimentation activities, regardless of where they occur. This capability provides true value to learning and can transform inconclusive or failed tests into concrete results that drive better personalization for customers.
3. Create and Publish Audiences from CJA to RTCDP: If your organization uses Adobe's Real-Time Customer Data Platform (RTCDP), Customer Journey Analytics (CJA) can become even more powerful. The link between CJA and RTCDP in AEP allows you to extract audiences for further activation. This enhances the actionability of CJA insights by applying them to identified audiences.

For organizations already utilizing Real-Time Customer Data Platform (RTCDP), the ability to create audiences from CJA significantly enhances targeting strategies. Audiences can be developed directly within the CJA through the Audiences interface or from visualizations like Freeform tables and Journey canvas. This flexibility allows marketers to define segments based on real-time insights derived from customer behaviors and interactions, ensuring that the audiences are both relevant and contextually aligned with their marketing objectives.

Once published, these audiences seamlessly integrate with existing customer profiles in RTCDP, facilitating precise cross-device and cross-channel targeting. Users can configure the refresh frequency of these audiences, ensuring they remain up-to-date for time-sensitive campaigns. With the capacity to accommodate audiences of up to 20 million people and a quick publication process that takes only seconds, organizations can effectively leverage journey-specific data to refine their personalization strategies and enhance overall customer engagement.