Episode Details

What’s up everyone, today we’re taking a deep dive into customer data and the stack that enables marketers to activate it. We’ll be introducing you to packaged customer data platforms and the more flexible options of composable customer data stacks and getting different perspectives on which option is best.

I’ve used both options at different companies and have had the pleasure of partnering with really smart data engineers and up and coming data tools and I’m excited to dive in.

Here’s today’s main takeaway: The debate between packaged and composable CDPs boils down to a trade-off between out-of-the-box functionality and tailored flexibility, with industry opinions divided on what offers greater long-term value. Key factors to consider are company needs and data team size. But if you do decide to explore the composable route, consider tools that focus on seamless integration and adaptability rather than those who claim to replace existing CDPs.

The 8 Core Components of Packaged CDPs: What the Experts Say
Okay first things first, let’s get some definitions out of the way. Let’s start with the more common packaged CDPs.

A Customer Data Platform (CDP) is software that consolidates customer data from various sources and makes it accessible for other systems. The end goal is being able to personalize customer interactions at scale.

I’ve become a big fan of Arpit Choudhury of Data Beats, he articulates the components of a packaged CDP better than anywhere I’ve seen in his post Composable CDP vs. Packaged CDP: An Unbiased Guide Explaining the Two Solutions In Detail.

8 packaged CDP components:

1. CDI (Customer Data Infrastructure): This is where you collect first party data directly from your customers, usually through your website and apps.
2. ETL (Data Ingestion): Stands for Extract, Transform, Load. This is about pulling data from different tools you use and integrating it into your Data Warehouse (DWH).
3. Data Storage/Warehousing: This is where the collected data resides. It’s a centralized repository.
4. Identity Resolution: This is how you connect the dots between various interactions a customer has with your brand across platforms and devices.
5. Audience Segmentation: Usually comes with a drag-and-drop user interface for easily sorting your audience into different buckets based on behavior, demographics, or other factors.
6. Reverse ETL: This is about taking the data from your Data Warehouse and pushing it out to other tools you use.
7. Data Quality: This refers to ensuring the data you collect and use is valid, accurate, consistent, up-to-date, and complete.
8. Data Governance and Privacy Compliance: Ensures you’re in line with legal requirements, such as user consent for data collection or HIPAA compliance for healthcare data.

So in summary: Collect first party data and important data from other tools into a central database, id resolution, quality and compliance, finally having a segmentation engine and pushing that data to other tools.

I asked recent guests if they agreed with these 8 components.

Collection, Source of Truth and Segmentation
Boris Jabes is the Co-Founder & CEO at Census – a reverse ETL tool that allows marketers to activate customer data from their data warehouse.

When asked about his definition of a packaged CDP, Boris elaborated on the role these platforms have carved for themselves in marketing tech stacks. To him, packaged CDPs are specialized tools crafted for marketers, originally in B2C settings. Their primary utility boils down to three main functions: data collection, serv