It seems like every time you turn around, there’s a new definition of a customer data platform (CDP). One common misconception is that a CRM and a CDP are the same thing. Another thing people get hung up on is thinking that reverse ETL is a CDP. When reverse ETL provider Hightouch came out with their since-retired “Friends don’t let friends buy a CDP” slogan, it really muddled the waters, since they also represent themselves as a “composable CDP”.
In an attempt to help you make informed decisions about your customer data strategy, let’s break down the differences between reverse ETL and a composable CDP.
What is Reverse ETL?
At its core, reverse ETL is the process of extracting data from a data warehouse or data lake and syncing it back into operational tools, such as CRMs, marketing platforms or customer support systems.
It was created to solve a problem that only existed because it wasn’t being solved upstream. Otherwise, it would be more of a “Reverse EL” than a “Reverse ETL”. The “T” (Transformation) is required when the data that resides in a data cloud is not fit for purpose, hasn’t been modeled correctly, or hasn’t got all the aggregates and insights packaged in, so they need to be created on the fly.
Reverse ETL is about activating the data you’ve already collected and making it actionable for various business functions. In the CDP world, the rise in popularity of a cloud data warehouse (data cloud) as a single source of truth for customer data is a major reason why reverse ETL has taken off as a valuable tool for enabling teams to leverage the full power of their data, but it is still just one piece of a much larger puzzle.
Why Reverse ETL Alone Doesn’t Equal a Composable CDP
A composable CDP, on the other hand, is a more comprehensive solution that goes beyond just moving data from point A to point B. It’s about building a flexible, modular architecture that can be tailored to your specific needs, integrating best-of-breed technologies across the data lifecycle. While reverse ETL may be a component within a composable architecture, a composable CDP needs to incorporate data ingestion, cleansing, enrichment, identity resolution, and real-time data processing capabilities.
Reverse ETL is a function, not a platform. It facilitates data activation, but it does not provide the full suite of tools needed to create a unified, actionable customer profile.
A true composable CDP offers unparalleled agility. It allows you to connect with and leverage existing tools and technologies, choosing the best solutions for each component of your data stack. It adapts to your infrastructure and scales with your needs, whether your data sits in a data cloud, a private cloud or even on-premise.
This flexibility is not just about where your data lives; it’s about how you can use that data to drive business outcomes.
Real-Time Capabilities: A Key Differentiator
Another critical aspect of a composable CDP is its ability to support real-time use cases. Unlike a system limited to batch processing or static data, a composable CDP should have the ability to provide up-to-the-moment insights, enabling you to respond to customer behavior as it happens. This is achieved through API integrations, event processing systems, and real-time data streams that ensure your customer profiles are always current and actionable.
The Importance of Data Quality in a Composable CDP
While reverse ETL helps you move data around, a composable CDP emphasizes the importance of data quality at every step. It’s not just about pushing data downstream; it’s about ensuring that data is clean, enriched, and ready for immediate business use. This involves advanced identity resolution, data hygiene, and the creation of unified customer profiles directly within your data environment.
The bottom line is that reverse ETL solves a problem that you would not have if you addressed data quality and data modeling upstream – where it belongs. It’s one thing to add some data ingestion and basic identity resolution just to tick a box, but there’s a difference between applying this to a Customer 360 that you’re required to provide vs. having data quality, data hygiene, advanced identity resolution and other features as critical parts of the CDP as it builds a Customer 360. In other words, reverse ETL solves the easy part – not the hard part.
Relying on reverse ETL as your composable CDP leaves a big hole in your CDP strategy … clean data. Most companies have multiple data sources, even if they all get stored in the same data cloud. That means you could have multiple records for individual customers, and each record could have name, address, email and other variations. You are then syncing data without the rigorous cleansing and enrichment processes that a true composable CDP provides.
From a marketing standpoint, skimping on data quality introduces friction into the customer journey. Duplicate or irrelevant emails or offers. Lost cross-sell or upsell opportunities. An inconsistent website experience.
Choosing the Right Solution for Your Needs
When evaluating your customer data strategy, it’s important to understand the roles of both reverse ETL and a composable CDP. While reverse ETL is a valuable tool for activating data, it doesn’t offer the full range of capabilities needed to create a holistic, customer-centric data ecosystem. A composable CDP, with its modular architecture and focus on data quality, provides a more robust and flexible solution that can grow with your business.
Reverse ETL and composable CDPs both play roles in the customer data landscape, albeit by serving different purposes. By understanding these differences, you can better evaluate your needs and choose a solution that truly supports your data-driven goals.
