All about Composable CDP

Personalisation is an essential marketing lever. It involves creating unique experiences to enhance customer engagement. This means knowing your audience inside out.

Historically, companies have adopted Customer Data Platforms (CDPs) to centralise and operate their customer data. However, traditional CDPs are considered expensive and inflexible, and struggle to deliver a satisfactory return on investment.

Composable, or modular, CDPs offer a more flexible and tailored approach, by integrating with companies' existing infrastructures.

🤔 Find out why composable CDPs are increasingly being adopted. Understand how they work and how they differ from traditional packaged CDPs.

The very essence of a composable CDP lies in its ability to use existing data layers in the data warehouse. 

This approach eliminates the need for a new data storage or management tool. It enables customer data to be activated directly for marketing operations.

By doing so, it substantially shortens the time to value and reduces the complexity of data management.

More economical, simpler and more flexible, composable CDP offers a number of advantages. They are summarised in the following categories:

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. 

💡 Several players in the market validate the composable approach over the packaged approach. This is the case, for example, of Snowflake in its annual report on the Modern Data Stack (2024).

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!

If you'd like to see a demo of how this can be done, go here 👇

The different stages:

🌟 DinMo is the only European CDP with the Google Cloud BigQuery Certification, meaning that we integrate seamlessly with BigQuery for supercharged data handling.

❄️ If you chose Snowflake as a data warehouse, no worries! We also have a strategic partnership with Snowflake!

Find out more about how Ankorstore reduced its CAC (Customer Acquisition Cost) by 20%.

Take a look at our article on the differences between a traditional CDP and a Composable CDP, and download our comparison guide 👇

With recent changes to consumer privacy and increasing restrictions on 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 personalised experiences and remaining competitive. 

Traditional Customer Data Platforms (CDPs) have long been the backbone of customer data management and activation, offering a centralised 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.

Despite their centralised 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. 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 centralised 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.

With over 75,000 companies now using data warehouses, the approach to data collection, centralisation 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.

👉🏼 There is a growing preference among businesses to use a Composable CDP, given its flexibility and agility in adapting to various data sources and structures. This shift reflects a fundamental change in the CDP market, where companies no longer see the need to purchase standalone systems when they already have a robust data infrastructure and modern stack.

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.

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.

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.

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 prioritise 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 organisations need to solve use cases, but they often think too broadly about technologies. They fail to recognise that they simply need a method to utilise and activate their existing data. Implementing the right solutions can streamline campaigns and enhance organisational efficiency.

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 and marketing 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.

Hightouch or Census take the problem as an integration one. They address the needs of data teams (connecting platforms) more than those of the business and marketing team. It's not for nothing that their "no-code" features are exclusive to their premium plans. If you want to start small, with a few destinations and a few segments, without needing help from your data team, this is simply not possible with these tools.