In the ever-evolving landscape of customer data platforms (CDPs), terms like “data-in-place CDP” and “composable CDP” are increasingly being used, often interchangeably. While these concepts overlap, they are not synonymous. A data-in-place CDP, which is often used to describe a CDP that runs on a data cloud warehouse (data cloud), is only one aspect of what a composable CDP can be.
Sometimes referred to as a “zero-copy CDP” or even a “data cloud CDP,” a data-in-place CDP is one in which all customer data remains in a centralized data warehouse or data lake, like Snowflake, Google BigQuery, or Amazon Redshift. The data does not leave this central repository; instead, tools and applications access and process the data where it resides. This approach is becoming more and more popular as companies seek to leverage existing data storage investments and avoid duplicating or moving data.
The Concept of a Composable CDP
The idea of a composable CDP revolves around modularity, flexibility, and agility. It allows businesses to build a CDP by selecting and integrating best-of-breed components that suit their specific needs. These components might include data ingestion tools, identity resolution, segmentation and activation systems, real-time interaction modules, and more. The key is that pieces can be added, swapped out, or customized as requirements and business strategies evolve.
While a data-in-place CDP can be a composable CDP, a composable CDP doesn’t have to be data-in-place. A composable CDP can be deployed multiple ways. True, one way is data-in-place. Another is on-premises (“on prem”) or within a “private cloud.” This on prem option gives organizations complete control over their data, often a requirement for industries with strict data governance or compliance requirements.
A composable CDP can also run as a comprehensive, full-featured SaaS solution that includes composable models. Here, the software vendor controls the built-in database, management, security and operational components, but gives the user the ability to select only the functionality that is needed to meet their composable workflow. This setup eliminates the need for a separate sign-on for each process.
Why Composable is Often Interpreted as Data-in-Place
One reason for the misconception that a composable CDP must run in a data cloud is because software vendor Hightouch evangelizes the notion that a composable CDP must centralize all customer data within Snowflake, Google BigQuery, Amazon Redshift or a comparable data cloud. Hightouch makes this claim because of its strength in reverse ETL. They excel at syncing customer data from a data cloud and activating it across various marketing and operational tools. It stands to reason that if your entire business model is built on offering reverse ETL to activate data in a data cloud that you would consistently claim that a composable CDP must run on a data cloud.
But a composable CDP encompasses much more than that. You can have your composable CDP without being data-in place. As an example, the Redpoint CDP can run in any data cloud environment – and in fact is the only CDP that natively operates on the Snowflake Marketing Data Cloud using Snowflake as its primary customer database (without any data replication). But the Redpoint CDP can also be deployed on-premises, in a private cloud, or in a SaaS environment depending on the customer’s needs. Those differing customer needs also require Redpoint to offer flexibility in component functionality and the ability to operate with other tech solutions.
Remember – composability is broader than where the data resides. True composability is about control, flexibility, and agility. Control your data, your MarTech stack, and your component functionality. Customize your foundational setup and your workflow according to your data storage needs and have the flexibility to connect your preferred, “best of breed” point solutions. Move with agility and respond to new opportunities or changing strategies with a setup that’s not just customized to your needs but allows different components to work well together.
Data Cloud or No, Don’t Forget About Data Quality
Data cloud or no data cloud, make sure your customer data is fit for purpose – for any intended use case. Wherever the data resides, and however you define composability, every CDP should take meticulous care that data is cleansed, accurately matched, dynamically segmented and ready for use. Whether you’re running on Snowflake or a legacy data warehouse, there are various tools and data pipelines that build out a Customer 360 and tools that activate it for your downstream marketing use cases.
The Redpoint composable CDP goes beyond data activation to include robust data ingestion, identity resolution, data hygiene, and segmentation capabilities. Starting with clean data yields the most accurate segmentation and analysis, and ultimately the best results.
Redpoint’s expertise in data quality as a core component of perfecting a company’s first-party data predates the concept of composability. Since well before the rise of the data cloud, Redpoint has prioritized choice and agility without creating an artificial limitation on the meaning of composability. Your data can reside anywhere. Whatever you choose, the composable Redpoint CDP provides you with the flexibility to select the functionality you need and get the most value out of your customer data.
