What is a Composable CDP?

Professionals seeking to leverage customer data regularly express their frustration about the limits of existing CDP architecture. Vendors commonly promote themselves as the ultimate answer to the problem while overlooking the reality that addressing the diverse range of customer data use cases across numerous tools and downstream teams will require a collaborative ecosystem, not a single tool.

The legacy customer data platforms limits

Customer Data Platforms (CDPs) emerged to address two significant challenges:

1. Customer data ingestion at scale: Traditional marketing suites, such as Salesforce, Oracle, and Adobe, were not designed to accommodate different types of customer data on a large scale. This issue became particularly pressing with the rapid increase in first-party data sources and digital touchpoints –a dedicated data layer was necessary to gather and interpret this massive influx of information.
2. Multi-channel customer experiences: Initial marketing tools were primarily developed for delivering digital experiences through a single channel, mainly email. However, the rise of digitalization demanded the ability to engage customers across multiple channels, including email, SMS, mobile, and advertising platforms.

Traditional CDP vendors attempted to solve these problems, but being both a data layer and cross-channel marketing platform is extremely hard. The technology itself is complex, but the bigger challenge is that the buyer and user personas for each component are very different. Ultimately, these legacy CDPs failed to solve either problem.

Traditional CDPs struggled with Customer Data Ingestion at Scale because they were designed for marketing teams and implementations rarely included adequate involvement from data and engineering teams. Developing a data layer capable of ingesting data at scale and ensuring its accuracy requires advanced APIs, SDKs, pipelines, monitoring, and governance. These complex technical requirements call for tools specifically tailored for data and engineering teams.

When it comes to omnichannel experiences, Marketing suites and tools eventually evolved and became proficient here. These tools even branded themselves as CDPs, reducing the need for standalone CDPs. But these advanced marketing tools lacked robust data capabilities which prevented marketing teams from fully leveraging their potential. In the end, neither traditional CDPs nor these advanced marketing tools effectively addressed the core issue. If you ask marketing teams (or any other team) what their number one problem is, the answer almost always relates to data, regardless of the level of sophistication in the tooling they use.

Given these limitations, it’s no surprise that traditional CDPs have not lived up to the hype.

The Customer Data Platform needs a new, composable approach

The Customer Data Platform needs a transformation. Instead of attempting to be the single source of truth for customer data (problem #1) or competing with the UI/workflow/delivery layer (problem #2), the CDP should focus on addressing the core issue faced by all stakeholders: business teams lack access to a comprehensive view of the customer.

The widespread adoption of cloud data warehouses as the foundation for creating a 360º view of the customer (challenge #1) paves the way for an elegant solution: a "composable customer data platform" architecture that functions as the linking element between customer data, the cloud data warehouse, and the rest of the stack.

What is a Composable CDP?

A Composable CDP (Customer Data Platform) is an approach to customer data management that emphasizes flexibility, adaptability, and customization.

The Composable CDP makes it easy to collect customer data from every source, build your customer 360 in your own data warehouse, and then make that data available to your entire stack. The primary function of the Composable CDP is hydrating the warehouse and business tools with data—not serving as the data store or the data interface.

This modular approach enables businesses to create a tailored CDP solution that can easily evolve with their needs, providing seamless integration with various tools and platforms, and enabling efficient data management across diverse teams. By allowing organizations to build a custom, scalable solution, a composable CDP promotes agility and innovation while effectively addressing customer data use cases.

Unlike traditional CDPs, which may have a rigid architecture and limited integration capabilities, composable CDPs allow organizations to mix and match components, services, and features to meet their unique requirements. This leads to more personalized experiences.

The architecture of the composable customer data platform

The composable architecture addresses the shortcomings of traditional CDPs and other business tools in several ways:

• Data teams can avoid building costly in-house data infrastructure or relying on limited marketing tools while maintaining full control over data management and access to the customer 360. This allows them to concentrate on delivering value through analytics and machine learning use cases, rather than managing pipelines or cleaning data.
• Marketing (and other business teams) can utilize their preferred tools (their front-end 'interface'), regardless of their integration with the warehouse or the Composable CDP. With access to the full customer 360, they can maximize their tools' potential.
• No one is forced to use software that only addresses part of their needs or isn't designed with their specific team in mind.

This architecture establishes a separation of technological concerns in the tech stack among the various teams interacting with customer data. Data teams handle data ingestion into the warehouse or directly to APIs, run models (dbt/sql/yaml) to create the customer 360 in the warehouse and expose the data to the business teams that require it (hydration). Business teams (marketing, product, customer success, etc.) can focus on activating that data using their preferred tools and workflows.

A high-level diagram illustrating how the Composable CDP architecture hydrates marketing tools and other business tools is presented below:

The advantage of this architecture lies in its flexibility as it does not require data teams or business teams to conform to a single, dominant integration pattern for utilizing the customer 360 across downstream systems.

Take marketing tools, for example, there are various patterns for using both real-time data and data generated in the warehouse. Since the Composable CDP concentrates on collecting data and constructing the 360º customer view within the same warehouse, marketing teams can freely choose their preferred SaaS tool and connection type.

Here are a few specific examples:

• Tools like Salesforce and Braze are building direct integrations into the cloud data warehouse to pull data into their ecosystems. Over time, more vendors will develop these capabilities, making the Composable CDP increasingly popular because with a composable CDP teams can choose to leverage these native integrations while relying on their composable CDP for real-time data streaming when necessary.
• For tools that lack native connections to the warehouse or require first-party data sent directly to their APIs (typically for real-time use cases), the Composable CDP is responsible for managing the connection and delivering or syncing data.
• Lastly, a new generation of tools, such as MessageGears and SuperGrain, operate natively on top of the data warehouse. Current reverse ETL vendors like Hightouch and Census are likely to develop competing capabilities. The Composable CDP fully supports both patterns with the customer 360.

Conclusion

Existing data warehouses and data lakes (e.g. Snowflake, Amazon Redshift, Databricks Delta Lake) are effectively addressing the data problem, And business tools are better than ever. It’s time for a robust layer that solidifies the connection between the modern data stack and the business stack, which is precisely what we are creating at RudderStack.

We invite you to join us on this journey as our team of data engineers, data scientists, and business professionals bring the vision of a Composable CDP to life.