CDI vs CDP: What’s the Difference?

In recent years, the landscape of customer data management has undergone a significant transformation. For over a decade, Customer Data Platforms (CDPs) have been the go-to solution for enterprises building this crucial data asset. But now we’re seeing a new player entering the fold: Customer Data Infrastructure (CDI). As organizations strive to harness the full potential of their data, understanding the differences between these two platforms has become crucial.

Let’s dive into the world of CDI and CDP, exploring their unique roles and how they’re shaping the future of data-driven businesses.

Defining CDI and CDP

Customer Data Infrastructure (CDI):

At its core, CDI is a real-time software system designed for ingesting, governing, and delivering behavioral data observed across a company’s digital estate. It’s a critical component in building a composable CDP stack, specializing in data governance, metadata logging, and data modeling—all from within your data warehouse or lakehouse. The data and technology teams typically purchase, own, and operate your CDI and it can serve other parts of the organizations, such as Product, Data Science, Customer Support, etc.

Packaged CDP (Customer Data Platform):

CDPs historically are packaged software solutions that create a persistent, unified customer database accessible to other systems. Packaged CDPs contain standalone proprietary customer databases used primarily for customer engagement use cases, such as segmentation, campaign management, and personalization strategies. They are typically owned and operated by the marketing and growth domain of your business given their main objective is to drive better conversion rates, reduce churn, optimize ad costs, and serve other business functions.

Composable CDP

This modern approach to architecting a CDP has grown in popularity since the rise of the data warehouse and lakehouse. It does the same things as a traditional packaged CDP except it’s backed and underpinned by your own data warehouse or lakehouse (like Snowflake or Databricks). Warehouse-native Composable CDPs are still owned by the marketing and growth teams, but they complement the investments of the data and technology domain, including CDI.

Why are CDI and CDP Important?

CDPs have long played an important role in helping businesses effectively manage and activate their customer data. They’re particularly useful for customer engagement use cases and driving business value in the form of revenue, reducing costs, etc.. Organizations use them to understand customer interactions on their digital channels and tailor messaging and advertising strategies based on this insight.

Now, we’re starting to see a rise in composable CDPs and CDI. This rise coincides with the growing confidence and data maturity within organizations and additional investments in central sources of truth such as the warehouse and lakehouse. Companies today are doing more with their data, thanks to the advanced AI features within platforms like Snowflake and Databricks. As a result, they’re looking for more flexible and powerful customer data solutions that break free from the confines of a traditional packaged CDP, and reduce any unnecessary data silos or tech debt.

CDI, as part of a composable architecture, offers several design and operational advantages. It enhances technical productivity and efficiency, reduces the risk of technical debt, and provides better data privacy and compliance options. CDI also allows for more control over data assets, treating behavioral data as intellectual property that is crucial for customer-centric organizations. Not only can these data assets be used in marketing and growth domains, but they can also serve the Product organization, Customer Support, Fraud, Data Science, and other areas of the organization.

CDI and composable CDPs play key roles in harnessing AI- and BI-ready data, accelerating the adoption of new advanced use cases. They also play pivotal roles in creating a single customer view, which is paramount to many modern business strategies and operations.

5 Key Differences Between CDI and Packaged CDPs

1. Architecture and Design

Think of packaged CDPs like all-in-one appliances. They come with everything built in. You get data storage, processing, and analysis tools all within one package. If one aspect of the monolithic system falters, it could impact other parts of the system. In contrast, CDI is part of a modular, composable system feeding off a central source of truth. This modular approach allows you to pick and choose different tools or replace parts as needed, giving you more flexibility. This is a really important architectural decision as new vendors arise (including AI agents), and you want to future-proof your stack.

2. Data Ownership and Control

With traditional CDPs, your customers’ data lives within the CDP vendor’s system. It’s like renting a storage unit—convenient, but you don’t own the building. In a CDI setup, your data stays in your own data warehouse or lakehouse. This is more like using storage space in your own house—you have full control over it.

3. Capabilities and Scalability

Packaged CDPs are fantastic for marketers looking to store and activate their customer data. But they may struggle with the more advanced workflows and data requirements. They’re like a Swiss Army Knife—handy for many things, but not ideal for specialized tasks. CDI, being part of a more flexible system, can handle a wider range of jobs for additional stakeholders. This includes the most complex tasks such as machine learning or real-time data processing. It’s more like having a fully equipped toolbox where you can add specialized tools as and when needed.

4. Data Quality Approach

CDI focuses on improving data quality right from the start. It’s like carefully sorting and clearing ingredients before cooking. This “shift left” approach means you deal with data issues early, saving you time and effort later. In contrast, packaged CDPs might need more work to clean and prepare data after it’s collected. This is more like having to sort through and clean your ingredients while you’re in the middle of cooking.

5. Integration with Data Platforms

CDI is designed to integrate seamlessly with modern data platforms, feeding high-quality event data directly into your data warehouse or lake. Packaged CDPs may require additional steps to integrate with your existing data infrastructure.

3 Considerations When Choosing Between Composable and Packaged Approach

1. Your Current Data Setup

Think about your existing tools. Are you already using modern data platforms like Snowflake or Databricks? If so, a composable architecture with CDI may be a better fit for your data needs. If not, you may be better suited to a packaged CDP. But if you’ve invested in best-in-class solutions like Snowflake or Databricks, it makes sense to choose components that integrate with them well, such as CDI and composable CDPs.

2. Data Privacy Needs

Data privacy is critical in today’s world. For organizations operating in regions with strict data protection laws (e.g., GDPR in the EU), CDI offers better control over data regionalization and ownership.

3. Long-term Costs

Consider the “engineering tax.” With CDI, you may need to spend more time setting things up initially, but it could save you effort in the long run. While packaged CDPs are easier to set up, they often need ongoing work when it comes to data governance and usability across domains

So there you have it. CDI and packaged CDPs differ in how they’re designed, handle your data, and adapt to your needs. For smaller, medium-sized businesses with limited IT resources, packaged CDPs could be your best bet. They’re also better for organizations with simpler data needs and those just starting their data-driven journey.

For larger enterprises with more complex, diverse data sets and requirements, CDI is most likely your best option. If you have a strong in-house data team and use Snowflake or Databricks, it may be worth exploring CDI if you haven’t already.

What’s clear is that as more businesses become increasingly data-savvy, many will start to move towards flexible systems that incorporate specialized platforms like CDI. Some are ready to make the leap today. Others may need more time. But ultimately, you need to assess your options now. Consider your setup, future plans, and desired data control. Then, you’ll be on the way to making the right choice for your business.

Learn More

If you want to learn more about the difference between Customer Data Infrastructure and Customer Data Platforms, check out this LinkedIn Live discussion: https://snowplow.io/events/cdi-or-cdp/

During the session, Lucas Stone, Senior Solutions Engineer at Snowplow, and John Bourous, Senior Partner Marketing Manager at Snowplow, de-mystify the concepts of CDI and CDP, highlighting their unique roles, capabilities, and use cases. By the end of the session, you’ll have a clear understanding of how to align your data strategy with your business goals, ensuring optimal data governance, integration, and utilization.

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