40 Migrations Later: Top Tips from CDP Replacement Experts
Last updated April 16, 2025You’ve weighed the reasons to switch your CDP. You’ve reviewed the details of the migration process. You’ve finally selected the perfect new CDP for your needs. Now, the crucial question remains:
How can you make this transition as seamless as possible and sidestep the pitfalls others have encountered?
In our webinar, How to Successfully Migrate to a New CDP: Lessons from the Trenches, two martech leaders offered valuable insights drawn from their experience helping 40 brands transition from legacy CDPs and systems to platforms that deliver measurable outcomes.
Amit Erande, GM of AI and Personalization Services at Treasure Data, and Simon Green, Solutions Architect, revealed seven key lessons learned from their work with various brands and shared a few success stories.
Data and integrations
1) Use historical and current data from source systems for your migration
More often than not, brands migrate to a new CDP because they’ve lost trust in their existing CDP or it isn’t doing the job that it was meant to do. The CDP may have continuous data issues, be unable to handle requirements for data mapping, or have unreliable data unification.
In situations like this, while migrating to a new CDP, get both historical as well as ongoing data from source systems. The CDP is not a system of record. In most cases, the data in the CDP can be recreated as long as there is access to the historical data from those source systems, as well as the business rules that are necessary to make that data effective and usable in the CDP.
2) Conduct a data quality audit
Data quality is the foundation of a CDP. Data needs to be cleansed to stitch the data together and apply segmentation and unification rules. For instance, product IDs in your web data may need to be mapped to match product IDs in your sales data.
Issues with the quality of email addresses and phone numbers can be measured in dashboards and cleansed using standard frameworks. But some issues we find are more surprising and require custom cleansing.
What is initially thought to be a unique identifier for a customer sometimes turns out not to be useful in building a unified customer profile. For example, we’ve seen lots of different customers merging into the same unified profile because sales agents were using their own phone numbers or dummy numbers in custom forms.
If your initial CDP implementation has already identified such issues, then the new CDP implementation should not be delayed by these surprises in the data.
Treasure Data CDP migration success story: Reduced deployment time by up to 60%
At Treasure Data, we share reports that give you full clarity on each step: how data is evolving across the platform, a pre- and post-data unification dashboard, and how data is actually consumed by audiences in the CDP.
We’re also innovating significantly in AI to further accelerate migrations. AI agents are now helping throughout the entire implementation process by analyzing data quality, automating data pipelines, and assisting with data cleansings required in data transformations.
We can superpower data engineers and reduce deployment time by up to 60% in some cases.
3) Prioritize a CDP with an effective, built-in integration framework
Building trust in the new CDP is critical. Typically, this is an extremely sensitive topic because of the previous failure of the legacy CDP. It’s important to make sure that the ongoing migration as well as the new data integrations are not a black box and are transparent and explainable.
Data is generated in your systems at different times and at different velocities:
- Streaming data: Some channels, websites, or apps generate data in real time. It’s important to bring this data into the CDP in a time-sensitive manner for real-time enrichment, segmentation, and activation.
- Batch data: In other cases (e.g., CRM systems) it may not be necessary or cost effective to bring that data into the CDP immediately. A daily batch may be sufficient.
Your CDP must be able to handle different velocities of data and unify all of this data at scale. Well-intentioned companies often create a customer data “Frankenstein” because they had to build custom scripts or a hodgepodge of tools to manage data that was flowing in at different velocities. That becomes a nightmare to manage because you build up tech debt into your integration process.
This occurs when a CDP has limited integrations, yet you’re activating data across a wide array of channels or importing data from diverse sources at varying speeds. Our recommendation is to switch to a CDP with an effective integration framework built in, and to use native integrations for both real time as well as batch or offline data movement.
Another reason to consider a CDP with robust native integrations is because upstream and downstream systems, such as Facebook, often make changes to their APIs and integrations. You don’t want to be the one managing this – the role of the competent CDP is to be able to build and manage all of these integrations for you.
At Treasure Data, our schema-on-read approach ensures schema flexibility and low maintenance requirements. This allows us to accommodate new fields in source data without code changes and use out-of-the-box connectors to easily pull in and assess new data sources.
Enablement and training
4) Organize your team around the CDP in the right operating model
Often, there is already a sense of fatigue within the organization because, despite having highly competent staff, they haven’t been able to make the legacy CDP work effectively.
But enabling your team as well as creating the right data model is just as important as choosing the right CDP. Use this migration opportunity to organize your team better and make sure that your new CDP is a success.
The CDP is a paradigm change in operations for an organization. Marketing teams are usually operating in their channels, and the CDP is the opposite of that – it unifies data across channels and creates accessibility for data across your organization.
The CDP is a paradigm change in operations for an organization. Marketing teams are usually operating in their channels, and the CDP is the opposite of that – it unifies data across channels and creates accessibility for data across your organization.
However, channel teams need help changing their daily workflows. They’re not automatically going to change tomorrow and start using the data in the CDP. We highly recommend an operating model exercise that creates the path to production:
- Center of excellence: If your organization is complex and matrixed, and you have a mandate to globally deploy your CDP, then a center of excellence model is highly recommended.
- Hub-and-spoke model: A centralized marketing organization with dedicated channel teams works best with a hybrid hub-and-spoke model. This ensures a centralized audience team with alignment to channels.
As you execute the migration, it’s important to build this operating model for your teams in parallel, and make sure that the team is upskilled with the capabilities of the CDP using resources like Treasure Data Academy. Once the CDP is live, your team can then hit the ground running.
Learn how Condé Nast and Constellation Brands structure their teams around the CDP.
Treasure Data CDP migration success story: User adoption
A customer previously using a legacy CDP found it difficult to use, with only two out of 60 team members actively engaged. During the migration, we involved the entire channel team, who were impressed by Treasure Data CDP’s capabilities and data accessibility.
This transition not only upgraded the company’s CDP but also fostered champions and power users within the organization. Successful adoption depended on both user-friendly functionality and an intuitive data model.
Use cases and measurement
5) Map out segments and campaigns in order to redesign CDP use cases
Customers typically accumulate a lot of campaigns, segments, activations, etc. in the legacy CDP. You may not be utilizing all of these assets, so use this opportunity to reevaluate everything from a use case perspective.
Additionally, your new CDP may dictate changes to your underlying data model, in turn mandating changes to your use cases. Here’s how to approach the migration of the business end of the platform into the new CDP:
- Map all existing segments and campaigns into one place, whether it’s an Airtable, Jira ticket, Google Sheet, etc.
- Redesign your use cases. Don’t just migrate your existing assets, but redesign your use cases to improve efficiency, reduce complexity, increase campaign effectiveness, and incorporate experimentation if possible.
Bring business teams early into the process of evaluating existing work and eliminating assets that aren’t needed. In this exercise, expect some worry from the business: “How can we do this in the new platform?” “We’ve always done it this way.” “How will the new platform change my daily workflow?”
This is good because you want them to ask these questions early and buy into the new CDP. It’s important to go in with thought leadership on how the new CDP will help address their needs, campaigns, and use cases, and make them even more effective in the future and easier to manage.
Treasure Data CDP migration success story: Simplified data modeling and segmentation
Treasure Data enables complex transformations of source data structures, making it easy to model the data in a manner that simplifies segmentation for users. In a project for a multi-brand quick-service restaurant (QSR) company, we reduced over 200 tables in 70 formats to just 10 behavior tables for easy segmentation.
6) Put a measurement and optimization framework in place
When migrating your use cases, it’s also important not to forget a measurement and optimization framework. When you deploy use cases on a CDP, more often than not, they don’t achieve the expected result in the first attempt.
Therefore, it’s important to put a framework in place that helps you understand what’s happening with the campaign and drive optimization for segmentation, machine learning, creative experimentation, etc.
To maximize your CDP investment, always think outcome-first. We recommend that you have a fully built out optimization strategy. AI can also lift this burden off teams (e.g., using reinforcement learning-based agents that automate experimentation and outcome achievement tasks).
To maximize your CDP investment, always think outcome-first.
Decommissioning and cutover
7) Build a full cutover plan
Remember to review the contract of the legacy CDP and determine when you can move on from that platform. (Remember, Treasure Data’s CDP Trade-Up program offers incentives to help reduce switching costs.)
Factor this into your step-by-step CDP migration plan, built in partnership with Treasure Data and your implementation partner. Pro-tip: Build a buffer between the go-live of the new CDP and the decommissioning of the existing one. In our experience, it’s typically 1–2 months to ensure complete confidence in the data and efficacy of the segments.
During the parallel run phase, be mindful of the potential for extra load on your source systems for extracting data twice. That should only be temporary, but it’s worth checking that you don’t cross any source limits on API calls, for example.
Ready to make the switch? Take advantage of our CDP Trade-Up program for a fast migration and flexible contract terms to reduce the financial burden of switching CDPs.
