Key takeaways:
- When migrating from Adobe Analytics to Adobe Customer Journey Analytics, start change management as soon as possible, even at the consideration phase.
- Engage stakeholders early through interviews and surveys, including third parties like agencies and vendors.
- Customer Journey Analytics introduces fundamentally different measurement concepts. Approach migration as a fresh start rather than a copy-paste exercise from Adobe Analytics.
- Build a dual-platform strategy that accounts for an intentional historical data approach with intentional cutover milestones so users can hit the ground running.
- Treat Customer Journey Analytics as a living product that requires ongoing governance and ownership.
Getting the most out of Adobe Customer Journey Analytics (CJA) is as much an organizational challenge as a technical one.
The implementations that deliver lasting value treat the human side of the transition with the same rigor as the technical side. As practitioners who've guided organizations through this process across industries and organizational sizes, we've seen what separates the migrations that stall from the ones that reach their potential.
The short version: change management needs to start earlier than you think, and a lift-and-shift approach isn't really a migration at all.
Why does change management for Customer Journey Analytics (CJA) start before implementation?
Most organizations don't think about change management until implementation is nearly done. The assumption is that once the technical work is complete, you migrate users over and you're done.
What gets forgotten, or started too late, is mapping all the people who will be impacted and bringing them into the process early. If you don't bring those people along and make them part of creating the change, you risk ending up with a fantastic tool that nobody uses, which makes it very hard to deliver on the value you promised leadership when you made the case for the investment.
Kicking off change management as early as the consideration phase is genuinely worth it. A targeted series of small-group interviews, surveys, or individual conversations with stakeholders across the organization gives you a much richer picture of potential use cases and value, as well as potential roadblocks. That upfront investment is far less painful than going back to an executive six months into implementation to say you need twice as long.
| PRO TIP One group that's easy to overlook is third parties. Many organizations have agency partners, vendors, or mobile app development teams with access to their current Adobe Analytics environment, and every one of those relationships takes time and budget to account for in a migration. Building that mapping into your early change management work means they're ready when you are, rather than becoming a source of delays when you can least afford them. |
All of that groundwork also surfaces champions. Stakeholders who weren't on your radar—teams in finance, operations, or outside agencies—sometimes become the strongest internal advocates for the investment once they understand how Customer Journey Analytics addresses their specific needs. Those voices carry a lot more weight with executives than the analytics team making the case alone.
What's wrong with recreating your Adobe Analytics instance in Customer Journey Analytics (CJA)?
This is one of the most common mistakes in a Customer Journey Analytics migration.
Customer Journey Analytics introduces fundamentally different measurement concepts like person-based attribution, cross-device sessions, and the ability to stitch together data sources that were previously siloed. When you bring those new models into play, metrics that your organization has been reporting on can shift.
We've seen this play out with a client where conversion rate was a publicly reported KPI. In Adobe Analytics, a user on a laptop and a smartphone simultaneously counted as two visits. In Customer Journey Analytics, it's one session. While that client now had a more accurate picture of their conversion rate, without early stakeholder alignment and clear communication, that kind of shift can land like an error.
Building something genuinely new in Customer Journey Analytics, rather than recreating what existed before, is also exactly the argument you need to justify the investment to leadership. A clearer, unified view of how customers actually behave across channels translates directly into smarter decisions and stronger outcomes.
But again, you do need to be conscious of the people aspect of this process and start conversations early. When you change the metrics, you're potentially changing how people are evaluated for bonuses and development opportunities. Bringing in finance, anyone with awareness of external reporting obligations, and team leads across affected areas allows you to collectively identify the risk and plan for it before it becomes a crisis.
How should you handle historical data?
Every analyst's first question when arriving in a new tool is some version of "how does this compare to last year?" Without historical data, that question is unanswerable, and users won't trust the tool.
Our approach is to build out new data collection using modern SDKs and semantic schemas from the start, like naming variables as "internal search term" rather than "eVar 20." That helps us build toward the future data model. Once that new data reaches a critical mass, we go back and convert historical Adobe Analytics data into the new schema, targeting either 13 or 25 months of converted history. That way, once users arrive in Customer Journey Analytics for the first time, they can answer year-over-year questions immediately.
The practical effect on adoption is significant. Running Adobe Analytics and Customer Journey Analytics in parallel for an extended period is expensive and creates organizational drag. Getting users to a place where they can fully commit to Customer Journey Analytics is much easier when the historical context is already there waiting for them.
What’s a better migration approach for Customer Journey Analytics: a big bang or phased rollout?
In theory, when migrating to Customer Journey Analytics, a phased rollout is incredibly appealing, especially for large organizations. It aligns with agile methodologies, allowing teams to treat the migration like a series of sprints where they can train a small group, learn from their feedback, and mature the backlog before expanding. But in practice, we’ve seen that a phased rollout tends to compound the problem you’re trying to solve.
One of the primary risks of a use-case-by-use-case approach is the erosion of an overarching data strategy. When you solve for one specific need at a time, you often discover by the fourth or fifth use case that your initial data modeling needs to be completely reworked for the entire organization.
A phased approach also creates a two-tier organization where some people have access to Customer Journey Analytics and others don't. The group without access often still has Adobe Analytics available to them, so while they may explore Customer Journey Analytics out of curiosity, they don't change their day-to-day workflows. That can lead to delays when it comes to full adoption of the new solution.
What actually moves organizations forward is an approach closer to a "big bang,” or a series of "coordinated bangs" by business unit for larger companies. The goal is to move entire departments or business units at once, rather than cherry-picking a few users for a pilot. When a whole team makes the switch together, the new platform becomes their shared reality instead of just an optional experiment.
This also prevents a massive headache with your reporting. As we covered above, since Customer Journey Analytics uses person-based metrics that differ from old-school tracking, your numbers will change. If one team is using the new metrics while another sticks to the old, your data will never align. A clean cutover ensures everyone is finally looking at the same version of the truth.
How do you keep the momentum going after launch?
Getting users into Customer Journey Analytics is a huge milestone, but it’s not the finish line. To keep the momentum going, you have to shift from "migration mode" into "product mode." The organizations that see the most value treat Customer Journey Analytics as a living product that requires ongoing care and feeding, not a project you complete and walk away from.
A big part of that is turning your data owners into long-term partners. When the people who know the data best are actually in the tool running their own insights, they become your best line of defense for data quality. This goes hand-in-hand with governance. You don't need a rigid, corporate committee, but you do need a strategy for how new data gets added and how metrics are reviewed. Without it, you end up with a cluttered environment that’s expensive to maintain and confusing to navigate.
What does the change management blueprint actually look like?
If you’re looking for a change management blueprint, the timeline is simple: start earlier than you think. Ultimately, Customer Journey Analytics is a transformation rather than just a technical migration. It’s about moving from "keeping the lights on" to putting a spotlight on what’s now possible for your business. The organizations that invest in the human side of this change with the same rigor as the technical side are the ones that actually see the ROI they were promised.
Adswerve was named Adobe CXO Partner of the Year in 2026, a recognition of our work helping brands navigate these exact transitions. If your organization is evaluating Customer Journey Analytics or working through a migration that's stalled, we'd love to talk. Reach out to our Customer Journey Analytics team to get started.
