What is a Composable CDP?

Learn why Composable Customer Data Platforms (CDPs) are rapidly adopted by leading companies in their data infrastructure, how they work, and why we prefer the term “Modular CDP” to define our vision

Personalized marketing demands an in-depth understanding of your customers. Traditionally, businesses have relied on Customer Data Platforms (CDPs) to gather, store, and utilize customer data. However, the evolving complexity of customer interactions and technological advancements have exposed certain limitations in traditional CDPs, particularly their extended time to value. With the advent of the Modern Data Stack, many companies are now integrating the creation of a comprehensive Customer 360 view directly into their cloud data warehouses. That leads to a pivotal question: Is there still a need for a standalone CDP?

In this blog post, we will cover:

This discussion aims to shed light on the evolving dynamics of customer data platforms and their impact on marketing strategies.

With the recent changes around consumer privacy and looming demise of third party cookies, the ability to effectively capture and harness first party data has become more critical to survival than ever and quite frankly, is now table stakes in driving highly personalized experiences and remaining competitive. 

Traditional Customer Data Platforms (CDPs) have long been the backbone of customer data management and activation, offering a centralized repository for various data sources (behavioral data, first party attributes, customer insights, etc.).

These platforms primarily focus on aggregating and unifying customer data from disparate systems, thereby providing a single customer view. This unified data is then made accessible to marketing teams for various use cases and analytics.

Here is a typical functional diagram of a CDP and its main components:

Despite their centralized nature, traditional CDPs often come with significant challenges. A primary concern is the rigidity of data storage within predefined models. This one-size-fits-all approach can be limiting, as each business has unique data needs and structures. We highlighted this issue when launching our Knowledge Store at DinMo. At DinMo, we are convinced that companies must use tools with adaptable data models that cater to their specific business and teams requirements.

Furthermore, many data teams have already centralized their customer data (in a data warehouse, a data lakehouse, or another storage solution). It creates a potential issue of data duplication when implementing a traditional CDP. This duplication not only complicates data management but can also lead to inconsistencies, with the data warehouse and the CDP potentially serving as conflicting sources of truth.

Another critical point to consider is the high cost and complexity associated with implementing traditional CDPs. These platforms often require significant investment, both in terms of financial resources and time (with the implication of marketing and data teams). The complexity of integrating various data sources into a rigid, vendor-specific architecture further adds to this challenge, leading to a prolonged time to value. This delay can be particularly problematic in a fast-paced business environment where agility and quick adaptation to data insights are crucial for maintaining competitive advantage and customer satisfaction.

With over 75,000 companies now using data warehouses, the approach to data collection, centralization and customer journey mapping has significantly evolved. Cloud data warehouses have become the richest sources of customer data, meticulously capturing both online and offline customer interactions. This evolution sets the stage for a new paradigm in customer data platforms and Modern Data Stack: the composable CDP.

What is a Composable CDP?

The essence of a composable CDP lies in its ability to utilize existing data layers directly from the data warehouse. This approach eliminates the need for additional data storage or separate management systems, enabling direct activation of customer data for marketing purposes. By doing so, it substantially shortens the time to value and reduces the complexity of data management.

Here are the key Benefits of a Composable CDP:

Traditional CDPs only understand clickstream data, ignoring the complexity of your business. Various offline actions, data science prediction models, and unique user attributes are overlooked and inaccessible with a packaged CDP. 

A Composable CDP offers more flexibility to address complex use cases. Its architecture, free from traditional CDP limitations, provides greater control and specificity in building audience cohorts and powering complex marketing scenarios.

If you want to understand all the differences between Traditional and Composable CDPs, check our 2-pages guide below 👇

The composable CDP can be thought of as an intermediary layer that bridges your data warehouse with your business tools. It does not store data independently but leverages the rich data environment of the data warehouse.

The core components of a Composable CDP are comparable to the one of a Traditional CDP:

You're surely convinced about the importance of data activation. Yet, you're hesitating between buying a Reverse ETL platform or building your own API connectors between your data warehouse and operational systems.

To be clear, there's little value in your data team building and maintaining pipelines for Reverse ETL:

Yet, turning your existing data infrastructure into a Composable CDP is really easy with DinMo. You can implement your first marketing use cases in minutes!

At DinMo, we adopt the term "Modular CDP" to better encapsulate our approach towards what is traditionally known as Composable CDP. This preference stems not just from the feature set, but more so from our overarching vision and strategy. This is where we differ radically from our competitors such as Hightouch and Census.

The concept of a composable CDP often revolves around a technical framework, anchored in the idea of a "Best of Breed" model. This approach typically involves assembling an array of features and platforms, each intricately designed for specific functions. However, while the technical capabilities are important, at DinMo, we prioritize the business application and its impact.

The modularity of our architecture allows you to focus on your marketing use cases rather than on "technology stacks." Many organizations need to solve use cases, but they often think too broadly about technologies. They fail to recognize that they simply need a method to utilize and activate their existing data.

We believe that the journey to becoming data-driven should be pragmatic and ROI-focused from the outset. This means enabling clients to start small. Companies can start by focusing on immediate and tangible benefits, such as optimizing customer exclusions from acquisition campaigns. From there, the system can evolve in complexity and scope, seamlessly adding more data, functionalities, and user personas. This modular approach ensures that the tool grows in tandem with the company's maturity, continuously delivering value at each stage.

A Modular CDP with DinMo allows for a gradual expansion of capabilities to support marketing teams to activate their customer data. Begin by establishing fundamental audience strategies, then progress to incorporating conversion events. As the system matures, integrate more advanced features and use cases like scoring models and eventually, predictive analytics. This progression ensures that each step is beneficial and aligned with the current needs and capabilities of the business.

🚀 To understand more about how our Modular CDP aligns with your business needs and our vision of democratizing access to CDP functionalities, we invite you to explore further and contact us to get a free demo of our solution.