How to Conceptually Think of a Customer Data Platform - CDP Architecture

by Swagatika B. Digital Marketer

A customer data platform (CDP) is vital for businesses today. It brings together many dimensions of customer information so that a 360-degree understanding of a customer can be created and enriched with information from multiple sources. The final aim is to generate insights and AI models that can be used to drive better customer experiences, commerce (purchases, cross-sell) and operational efficiencies.

However, enterprises often face the following two challenges:

CDP programs often tend to become too complex leading to delays in returning value to the business.

The systematically deployment of AI insights into operations as part of closed loop analytics remains a challenge for the industry.
A CDP can be thought of in terms of the following key functional blocks that span the overall data management lifecycle. It is helpful to think in terms of a functional architecture because it aligns the CDP more closely to its purpose.
Let’s go bottoms up and build it up to enable an easier understanding of the multiple layers.
Level 0: The core data repository
Level 1: Insights Generation Engine
Level 2: Program and Campaign Management
Level 3: AI Operationalisation
Level 4: Management Reporting
Today, a customer data platform (CDP) is a significant and vital investment for enterprises. However, when the Customer 360 mission overwhelms other components of the architecture, the vision of a CDP remains unfulfilled.
Read more on Conceptual Architecture of CDP here.