Best Practices

CDPs vs. Reverse ETL tools for customer data management | Census

Nicole Mitich
Nicole Mitich June 12, 2023

Nicole Mitich is the content marketing manager @ Census. She's carried a love for reading and writing since childhood, but her particular focus is on streamlining technical communication through writing. She loves seeing (and helping) technical folks share their wisdom. San Diego, California, United States

Welcome to the showdown of the decade, folks! 

In one corner, we have the customer data platform (CDP), claiming to be the ultimate tool for organizing and managing customer data. And in the other corner, we have the relative newcomer, Reverse ETL, the fresh face powering Data Activation in moving customer data from your data warehouse to your desired tools.

Who will come out on top in this epic battle of data management? 🥊 Let's find out! 🔔

Round 1: The CDP at work

Marketing copy for CDPs regularly claims they offer a single source of truth, but in reality, all they offer is headaches.

Due to their rigid data models, long onboarding times, and redundancies across analytics and marketing tools, only 1% of companies believe CDPs are actually meeting their current and future needs. 😬

However, the biggest problem with CDPs is that they don't (and can't) store the breadth of customer and company-level information your data warehouse does. Only the data warehouse holds the complete information needed to power your analytics. 

In fact, CDPs copy the data they've collected to the data warehouse to be used in analytics, diminishing their claim as a "single source of truth." Some CDPs have started to import data from the data warehouse to bolster their claim, but doing so results in data latency and only papers over the fact that the CDP is yet another silo of data, not a credible source of truth. With this fragmentation, you simply can't trust the data inside the CDP to be as credible or fresh as in the data warehouse.

The CDP at work

In many ways, CDPs were a stopgap in the journey of centralizing and activating customer data and were most useful in the times before cloud data warehouses became common. Now, they are lumbering dinosaurs with low flexibility in their data models, less effective data governance, and a high risk of vendor lock-in.

Round 2: The more nimble Reverse ETL

In the ten years or so that CDPs have been around, the face of the data space has changed enormously.

Like most companies today, you’re probably loading your data into data warehouses like Snowflake or BigQuery and transforming it with tools like dbt. In that case, you already have many of the components of a CDP inside your stack. All that's missing is Reverse ETL to move that data from the warehouse to the desired tools and start your data activation journey off on the right foot.

Data teams can add this layer of Data Activation by using a platform powered by Reverse ETL, like Census. Census is designed for both data and business teams, offering unique features like robust version control, logging, and observability for data teams and a visual segmentation interface for business users. 

This alternative approach of transforming your existing data platform into a CDP is known as a composable CDP. Rather than rely on a single platform to do everything well, you compose multiple “best of breed” applications (e.g. data collection, data transformation, data activation) that use your data warehouse as the source of truth for customer data and activate data where it already lives.

Build a composable CDP, the more nimble Reverse ETL

While a CDP acts as a middleman, collecting customer data from various sources for processing and activation with other tools (creating yet another data silo), a composable CDP powered by Reverse ETL nimbly and efficiently loads business data directly from its source (your data warehouse) into applications.

Knockout Round: CDP vs. Reverse ETL

The intention behind a CDP – to use data to create a clearer picture of who customers are – is still as relevant as ever. But, as a product, CDPs are quickly becoming irrelevant. 

They may have initially gained popularity by marketing themselves as an all-in-one solution to collect, unify, and activate customer data. But let's be honest: They aren’t solving anything. 😵

Now, with the rise of the modern data stack and Data Activation platforms powered by Reverse ETL, like Census, companies can access best-in-class solutions for each component of an off-the-shelf CDP and build a composable CDP more cost-effectively and with much more flexibility than traditional CDPs. 

So there you have it. A hard-fought battle, but in the end, Reverse ETL has emerged victorious as the ultimate solution for managing and activating customer data. 👑

CDP vs Reverse ETL

💡 Learn more about how Census can help you activate your customer data where it already lives — the data warehouse. Book a demo with one of our product specialists to learn how we can help you build granular segments and sync customer data to all of your marketing and advertising tools, without any code. 💪

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For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: