The Evolution of the Customer Data Platform | RudderStack

By neub9
3 Min Read

There are numerous strategies for fulfilling the promise of a customer 360. With a history of Customer Data Platforms (CDP) solutions coming with their own drawbacks, the challenge is evident. Legacy SaaS CDPs posed limitations that led many companies to consider building their own capabilities in-house. However, the engineering capital and maintenance required to do so proved to be overwhelming.

Recently, the market saw the emergence of the Composable CDP as a happy medium between legacy SaaS CDPs and in-house built capabilities. While a step in the right direction, the composable approach does not fully address the complete picture.

The future of CDP is rapidly evolving, with a central role expected to be played by the data warehouse (data cloud, data lake, data lakehouse). However, the surrounding system is yet to be clearly defined. This article aims to unpack the current prevailing customer data platform approaches and introduce a new approach that could deliver the end goal – easy activation of complete customer profiles.

The Legacy SaaS CDPs initially presented themselves as a response to the SaaS boom, seeking to aggregate data from data silos into one place. However, these systems ultimately created another data silo and were mostly beneficial to marketing teams for specific use cases. While today’s CDPs are more flexible, packaged SaaS CDPs are primarily designed for marketing users and still suffer from data silo issues.

In response to the limitations of legacy CDPs, some companies opted to build their own in-house CDP capabilities. However, this option proved to be overwhelming, costly, and not scalable. The Composable CDP emerged in 2022 as an alternative to inflexible, packaged systems and cumbersome in-house builds. While it solves some challenges, it still presents drawbacks such as fragmented systems and incomplete and incompatible data.

The Warehouse Native CDP is a platform that runs directly on the data warehouse and helps data teams deliver value at every stage of the data activation lifecycle. It places the data warehouse at the center of the customer data stack, eliminates data silos, and allows for the use of preferred tools. This approach is flexible, supports real-time and batch use cases, and provides automated identity stitching and customer 360, among other features.

Overall, the Warehouse Native CDP architecture provides flexibility, complete and trustworthy data, control and visibility, privacy and security, and readiness for machine learning. As modern data leaders rapidly adopt this approach, it leverages the best ideas from both legacy CDPs and in-house builds to deliver a combination of benefits that no other approach can.

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