Reverse ETL

Definition

Reverse ETL is a data-integration tool that helps you extract customer data from your data warehouse, transform it within the warehouse, and copy it into whatever SaaS program you’re wanting to use.

You’ve probably heard of ETL and Reverse ETL in the context of data centralization. While both ETL and Reverse ETL perform important functions in powering your MarTech stack, not all Reverse ETL solutions are the same. Let’s cover the basics of these processes and where they fit in the modern data stack in 2023.

What is ETL?

ETL (or Extract, Transform, Load) is the process of taking data from multiple sources, transforming the format to gel alongside data formats from other tools, and streamlining it into a single data warehouse or other type of cloud data storage. The data warehouse houses all of your data in one place, which then requires Reverse ETL to extract the data so marketing, sales, and other teams can use it.

What is Reverse ETL?

As mentioned up top, Reverse ETL is a data-integration tool that helps you extract customer data from your data warehouse, transform it within the warehouse, and copy it into whatever SaaS program you’re wanting to use. Reverse ETL is the opposite of traditional ETL, wherein the data warehouse is the target of the data that’s being extracted from the third-party source. 

The information can be repurposed and used for marketing and sales, whether your company is B2B or B2C. Whatever core metrics you have stored, you can sync them back to your business processes. Common types of data used in reverse ETL include:

  • Churn rate
  • Recurring revenue
  • Daily active users
  • Customer acquisition costs

Why use Reverse ETL? 

Typically, data warehouses cannot load data directly into a third-party source because the data needs to first be transformed to meet the formatting requirements of that source. But once it’s collected into a single warehouse, it can be difficult to conform it into usable information. That’s where reverse ETL comes in. It allows you to activate that data at scale without manually creating CSV files.

Why would you do a Reverse ETL rather than a traditional ETL?

More companies are starting to use Reverse ETLs as their marketing operations are revolving around their data warehouse instead of the data warehouse being on the periphery of the process. With the data warehouse acting as the gravitational center of your marketing strategy, it makes sense for it to be the source of the data and for the SaaS tools to connect directly to it as a means of receiving the customer data.

What is the impact of Reverse ETL?

It operationalizes data, allowing teams across an organization to access the data they need within whatever system they use. With the decline of third-party data, a Reverse ETL is a great tool for getting first-party data into ad channels. When you combine a Customer Data Infrastructure (CDI) with a Reverse ETL, the foundational elements are there for a house-built CDP.

Reverse ETL vs CDPs

Customer data platforms (CDPs) are third-party data storage services that serve as both a mini data warehouse and data activation solution. These platforms are also created to give you identity resolution, audience management, and built-in data activation across your other tools.

 It can simplify the process of activating stored data at first, but there are drawbacks to using a CDP:

  1. Data Privacy – CDPs store your data outside your firewall, causing concerns around GDPR and CCPA, especially when working with PII.
  2. Inflated Costs – pricing models on CDPs can get really expensive, especially at the enterprise level. Storing and activating data points across a large record of customers can become cost prohibitive.
  3. Stale Data – Transferring data from your data warehouse like Snowflake to a CDP can take hours to ingest all the data. Having your CDP deploy this data to a SaaS solution like your ESP can take even longer. This makes the agility out of your marketing and creates a serious data lag. Flash sales and other timed events become a nightmare. Say goodbye to real-time data when using a CDP.
  4. Slow To Transition – Switching to a CDP can take months, if not a full calendar year, to phase in the new tech and get your marketing team versed in the new system. A warehouse-native solution like MessageGears cuts this time down dramatically.

In our opinion, the biggest downside is that you no longer own the data once you deploy a CDP. While you may still have copies in your company’s data warehouse, the CDP simultaneously hosts the data on its own server. This can cause major concerns, particularly if your data is subject to HIPAA or other privacy regulations. Other disadvantages include the inability to completely customize your data. And on top of that, the cost of using a CDP is extremely high.

How does MessageGears solve for the Reverse ETL?

MessageGears is a cross-channel marketing platform that connects directly to your data warehouse as a “connected application,” with no ETL (reverse or otherwise) necessary! Our Segmentation tool acts as a Reverse ETL purpose-built for non-technical marketers to segment and activate their customers’ data from their warehouse — live and in real-time. Create dynamic audiences that allow marketers to send highly personalized cross-channel messaging campaigns based on anything they know about their customers. See how we fit in the modern data stack.

Looking to talk with an ETL expert? Reach out or chat with a human at the bottom right of your screen, and we can help you find the right solution!