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Data Strategy8 min read

What's All the Hype About CDPs?

Customer Data Platforms have become essential infrastructure for modern businesses. But not all CDPs are created equal—and choosing the right approach can make or break your implementation.

What Is a CDP?

A Customer Data Platform (CDP) functions as a centralized, unified customer database that is accessible to other systems. At its core, a CDP handles three essential functions: data capture and ingestion from internal and external sources, data storage and transformation into unified customer profiles, and distribution to downstream tools.

Two Approaches

Packaged vs. Composable CDPs

Think of it like furniture: you can buy a packaged wardrobe that comes ready-to-use, or you can design and assemble one yourself. Both get the job done, but they suit different needs.

Packaged CDPs

Single vendors like Segment or mParticle manage all three CDP processes internally. Data collection, transformation, and activation happen within one platform.

  • Simpler to implement and maintain
  • Great for standard use cases
  • Faster time-to-value for small teams

Composable CDPs

Integrated tool sets that use your company's data warehouse for modeling and transformation. You own the data layer and connect best-of-breed tools.

  • Maximum flexibility and control
  • Better for complex B2B/SaaS scenarios
  • More economical at enterprise scale
Decision Framework

How to Choose the Right Approach

The choice between packaged and composable CDPs depends on five critical dimensions:

1. Simplicity vs. Complexity

Packaged solutions excel at standard use cases with predictable data structures. Composable approaches handle intricate B2B scenarios, complex e-commerce models, and SaaS businesses with unique data requirements.

2. Total Cost of Ownership

Small companies typically benefit from packaged CDP pricing. As data volumes grow, composable approaches become more economical—especially if you're already invested in a cloud data warehouse.

3. Data Flexibility

Composable systems enable richer data enrichment and reverse ETL capabilities. If you need to blend first-party data with third-party sources or run complex transformations, composable wins.

4. Time-to-Value

Both approaches have comparable implementation timelines when done right. The difference is in ongoing iteration: packaged CDPs are faster for simple changes, composable for complex ones.

5. Privacy & Data Residency

Composable CDPs minimize data duplication through warehouse-centric architectures. This can simplify compliance with regulations that require data to stay within specific boundaries.

The Bottom Line

Both packaged and composable CDPs come with their pros and cons. The right choice depends on your:

  • Technical resources and data engineering capacity
  • Business requirements and use case complexity
  • Existing data infrastructure investments
  • Growth trajectory and scaling needs

Need Help Choosing the Right CDP Approach?

We've implemented 400+ CDP projects across packaged and composable architectures. Let's find the right fit for your business.