Our POV
Most brands evaluating a standalone CDP already have the data infrastructure to do what a CDP does. The data is unified. The profiles exist. The warehouse is running. What’s actually missing is an activation layer — a way for marketers to use that data in campaigns without filing a ticket to the data team every time. More often than not, the problem is tooling and workflow, and buying a CDP won’t necessarily fix that.
What a CDP actually does
A CDP’s core functions are:
- Ingest data from multiple sources
- Unify and resolve customer identities
- Create a single customer view
- Make that view available for segmentation and activation
Here’s what we see all the time: brands already have the first three covered.
All data lands in the data warehouse. It handles transformation and enrichment. ETL pipelines — the automated processes that move and clean data between systems — are running. Identity is being managed.
What they don’t have is a marketer-accessible interface on top of that infrastructure. A place where the CRM team can build segments, launch journeys, and run experiments without going back to data engineering for 70–80% of their work.
That missing piece is an engagement platform — not another data layer.
Our POV: A Standalone CDP usually adds more complexity than capability
When brands insert a standalone CDP between their warehouse and their engagement platform, the architecture gets longer:
Data warehouse → Standalone CDP → Engagement platform
Each handoff introduces latency. Data inconsistency. A new platform to maintain, integrate, and pay for. A new vendor relationship to manage.
What we consistently see is that brands end up with three platforms doing overlapping jobs — and a data team fielding integration issues instead of building better models.
The simpler architecture puts your data platform and your engagement platform in direct contact:
Data warehouse → Engagement platform
Fewer systems. Fewer handoffs. Fewer points of failure.
Modern engagement platforms like Braze connect directly to the most common warehouse platforms — Databricks, Snowflake, BigQuery, Redshift, Microsoft Fabric — via native Cloud Data Ingestion (CDI). That’s a direct, scheduled sync of profiles, attributes, and computed fields from your warehouse into Braze. No middleware. No standalone CDP sitting in between.
The data team owns the warehouse. The marketing team owns Braze. The integration between them is direct and maintainable.
Is your problem data access or data activation?
More often than not, the problem isn’t a lack of data. It’s that marketers can’t get to any of it — or don’t know how.
To use a segment, they need to describe it to a data analyst, who writes SQL, runs it, exports a list, and uploads it into the campaign tool. That process takes days. Sometimes weeks. It runs on request queues and sprint cycles.
Standalone CDPs market themselves as the solution to this problem. And they can be, in the right context. But what we find in practice is that brands evaluating them often don’t need a new data layer sitting outside their existing infrastructure — they need better tooling that brings marketers closer to the data they already have.
Braze does this natively. Marketers build segments in a no-code visual builder using any combination of profile attributes, behavioural events, and time-based logic. No SQL. No tickets. No waiting.
Where Standalone CDPs have the most value
Here’s our take on the scenarios when a standalone CDP can make sense.
When identity resolution is extremely complex. Brands with large anonymous user populations, heavy cross-device journeys, or significant probabilistic matching requirements — matching users across devices based on behavioral signals rather than a definitive identifier like an email — may find that a CDP’s native identity graph offers something a warehouse plus deterministic matching can’t easily replicate.
For omni-channel campaigns across owned and paid channels. Many martech platforms — Braze and Databricks included — have native integrations with advertising vendors like Meta. But standalone CDPs offer a distinct advantage for one specific use case: activating anonymized audiences across paid channels at scale.
The Braze/Meta integration works well when you already know who you’re targeting — lookalikes, retargeting, suppression. CDPs like TradeDesk and LiveRamp go further, making it easier to push first-party audience data into paid media at scale. For a true omnichannel play across owned and paid, a CDP can centralize data and make it accessible to both CRM and media buying teams.
That said, none of this applies to brands that already have a warehouse, a data team, and an established customer model. They don’t need more infrastructure sitting outside what they already have. They need activation.
Investing in CDPs for identity resolution
The most common concern we hear is: “But what about identity resolution? Doesn’t the CDP handle that?”
In most B2C environments, deterministic identity resolution — matching anonymous behavior to a known profile at the moment a user identifies themselves — covers the vast majority of use cases.
Braze handles this natively. The SDK creates anonymous profiles. When a user identifies (login, purchase, form submission), Braze merges the anonymous record into the known profile and backstitches prior behavior. Multiple identifiers are supported natively: email, device ID, external ID, in-app identifiers.
For more complex cross-system deduplication, that work happens upstream in the warehouse — before data reaches Braze. This is actually the better approach. The matching rules are visible, auditable, and owned by your team. Not locked inside a vendor’s black-box identity graph.
The cost reality of implementing a CDP
Standalone CDP licenses are not cheap. And they compound.
You pay for the license. You pay for the integration work to connect it to your warehouse and your engagement platform. You pay for ongoing maintenance when schemas change or pipelines break. You pay for someone to manage a third platform your team also has to learn.
When you look at total cost of ownership across a typical three-year contract, a standalone CDP is rarely just the license fee. It’s the integration overhead, the ongoing ops burden, and the organizational complexity of managing one more system sitting in the middle of your stack.
The smarter investment isn’t adding a standalone CDP on top of your existing warehouse. It’s making sure your data platform and engagement platform are doing the jobs a CDP was supposed to do — without the overhead of a third system inserted between them. The data team gets better models. The marketing team gets direct access to segmentation. The integration between them is leaner and more maintainable.
This isn’t anti-CDP; it’s about making the smartest investments in your martech stack
We implement CDPs regularly. When a brand’s architecture genuinely calls for one, we build it. What we’re pushing back on is the assumption that a standalone CDP — sitting outside your data platform, duplicating data, adding middleware — is always part of the answer. In a lot of cases, the problem brands are trying to solve with a standalone CDP is actually a workflow and tooling problem — one that a data platform paired with a best-in-class engagement platform already solves.
The question you should ask yourselves before you buy is: Do we need a new data layer sitting between our warehouse and our campaigns, or do we need marketers to be able to actually use the data we already have?
In most cases we see, it’s the latter. If that’s true, we recommend ensuring you fully understand and leverage the capabilities of your existing martech stack before adding more into the mix.
Continue Reading:
A Working Guide to CDP + Braze Capability Design (Matt Kingerlee, Solutions @ Stitch)
Meet the author.
Bobby Tichy is the co-founder and Chief Solutions Officer at Stitch, bringing over 15 years of deep expertise across the martech landscape. He’s 8x Braze Certified and holds additional certifications in Marketo and Salesforce. Connect with him on LinkedIn.
