Why the Composable CDP is Now on the Menu
There’s been a major shift in how enterprise organizations approach their customer data stacks — and it’s being driven by data and IT teams. Thanks to them, the composable CDP will become the new standard for enterprise organizations.
Traditional customer data platforms (CDP) used to be the norm, forcing data and IT professionals to implement bundled technologies regardless of their wants or needs. As brands raced to keep up with rising expectations and deliver more personalized customer experiences, alternative choices were limited.
But all that has changed. Thanks to the hard work of data and IT teams — and the evolution of cloud data warehouse technology like Databricks, Snowflake, Teradata VantageCloud, Amazon Redshift and Google BigQuery — the future is looking a lot more flexible.
Read on to learn why composable customer data platforms will become the new standard for enterprise companies — and how data and IT professionals can make sure they get it right.
Why the Composable CDP is Now on the Menu
Moving Beyond Fixed Menus
There are 161 CDP vendors selling their wares, according to the Customer Data Platform Institute. Data and IT teams are spoiled for choice — but only if they want to order off a fixed menu.
There are certainly differences between vendors — you can pay the exorbitant price of a fancy banquet from a well-known brand or opt for a faster, cheaper meal from a new upstart — but most have one thing in common: traditional customer data platform architecture. So whether it’s filet mignon or a burger and fries, ordering à la carte isn’t an option, no matter what IT teams would prefer.
Freedom and flexibility are key to helping IT professionals build the internal customer data infrastructure they need to maintain control, manage costs and improve performance. But traditional CDPs prevent this.
The result?
- Buying everything instead of only what you need
- Copying data from one system to another instead of deciding where it lives
- Contending with strict system architectures instead of adapting them to the needs of the business
- And living with closed systems instead of swapping new capabilities in and out as needed
There’s a better way — and data and IT teams found it.
Embracing Composable (Customer Data Platform) Architecture
There’s a reason data cloud companies such as Snowflake, Databricks, Google BigQuery, AWS Redshift and Microsoft Azure are making waves: They’re helping organizations embrace the power of composable technology stacks.
Composable architecture allows data and IT professionals to centralize customer data and create their own sources of truth — and eliminate the need for bundled or prepackaged CDPs in the process. With the cloud data lakes they’ve built, data and IT teams can develop their own customer 360 technology and truly tailor their customer data stacks to their unique requirements.
Sixty-three percent of chief information officers at organizations with high composability report better business performance when compared to industry peers. That helps explain why 60% of organizations plan to invest in composable enterprise technology within the next three years, according to the 2022 Gartner CIO and Technology Executive Survey.
But building a 360-degree view of customers is only one piece of the puzzle. Now that data and IT professionals can build the ideal CDP for their needs, the challenge is making sure it serves the needs of the whole organization.
Building a Better Customer Data Stack with a Composable CDP
Creating a comprehensive view of the customer is key to delivering better customer experiences, but data and IT teams need a way to extend the hard work of centralizing data in their cloud data lakes so business teams can leverage the benefits of data centralization for audience segmentation, journey orchestration and real-time experiences.
Reverse ETL is key, but not just any application that supports reverse ETL will do. Data and IT professionals want to focus on building and maintaining data systems, not fielding ad hoc requests. But too many applications built on top of data lakes require IT professionals to write endless SQL queries on behalf of business users.
To build a customer data stack that serves both the needs of technical and non-technical users, IT professionals must seek out solutions that give business teams a user-friendly interface they can use to generate queries, have those queries automatically translated into SQL, and push them down to the data lake to be executed.
Results can then be processed and served back up to the application, allowing data and IT teams to decide where data is stored and queried while making sure business users can self-serve their needs — with role-based access to data. We’ll take a closer look below.
Methods to Plug Your Composable CDP into Your Data Warehouse
All Composable CDPs are not created equal. some Composable CDPs tap directly into the data warehouse, zero copies required. But with “zero copy” emerging as a buzzword in composable architecture, it’s important to understand the differences in meaning.
There are different modalities by which an application can connect to the data warehouse and facilitate composable architecture, such as data sharing or query pushdown. For a CDP, these could include:
Reverse ETL Data Pipeline
A Reverse ETL pipeline can be a fast and simple way to copy data from the warehouse to a destination without creating another silo.
However, it is extremely limited in its ability to allow business users to orchestrate campaigns and experiences in a way that CDPs typically enable, and it can only pipe data from one single database to a destination.
Data Sharing
Data Sharing solutions provide a storage layer with access to data. The compute layer (e.g. execution of the query), however, is decoupled and not provided in this scenario.
A Data Sharing integration enables a CDP to access data in the data warehouse and use it for orchestration and other CDP functions, but it is limited to one specific warehouse and requires a lot of data copy in the process.
Query Pushdown and Federated Query Pushdown
CDPs use query pushdown to delegate compute to where the data is stored, in this case a single cloud data warehouse.
This offers both the benefits of a CDP and a high degree of benefits that composability provides, by essentially no compute or storage.
Federated Query Pushdown
Federated query pushdown goes one step further to combine data on-the-fly from cloud warehouses and local CDP data stores to power sophisticated use cases.
Testing each component’s interoperability is a critical step during implementation, guaranteeing that the stack performs and scales within a new connected ecosystem.
Selecting the Composable Flavor That’s Right For You
Data and IT professionals can now order whatever they want off the menu — no strings attached. The trick now is understanding which dish best suits their needs.
Composable CDPs are the future. But to guarantee success, data and IT teams must choose tools they can plug and play into their existing martech stack to maximize power, control and performance. To discuss how to select an option for your data strategy, reach out to our team.
FAQ on Composable CDPs
What is a Composable CDP?
A Composable CDP is a customer data platform that allows organizations to apply marketing applications and capabilities like audiencing, orchestration and activation from their CDP solution directly into their existing data warehouse. With a composable approach, companies can select the tools and capabilities they need and integrate them together with a centralized customer data infrastructure.
How Does a Composable CDP Work?
A Composable CDP works by tapping into the brands’ source of truth—the centralized data store like a cloud data warehouse to support a unified customer 360 database. Tools for segmentation, orchestration, etc. can then query the centralized data to power use cases like audience building, campaign management, real-time personalization and analysis.
How to Build a Composable CDP?
To build a Composable CDP, organizations typically start by centralizing their customer data in a cloud data warehouse or data lake. They can then layer on additional tools and applications for activities like data transformation, identity resolution, audience segmentation, journey orchestration, etc. The key is using technologies that can plug into the central data repository and integrate together for a seamless CDP solution.
Traditional CDP vs. Composable CDP
Traditional, pre-packaged CDPs provide an all-in-one customer data platform as a single product bundle. In contrast, a Composable CDP allows companies to build their own customized CDP using separate best-of-breed tools for different requirements like data ingestion, identity resolution, segmentation, etc. This provides more flexibility than traditional CDPs.