Data Intelligence

What is Reverse ETL?: Concepts, Use Cases & Integration

Thalia Barrera
August 25, 2022
10 min read
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Typical Reverse ETL Use Cases

When building an ETL pipeline, data engineers usually don’t need to know precisely how stakeholders will use the data. Their main concern is to get all the required data to the warehouse in a performant and scalable way. 

With Reverse ETL, engineers need to be more familiar with the use-case of the data. “When writing to Braze, you have some use cases in mind. You're often writing a likelihood to churn score, lifetime value score, a segment the client should be in, or the latest product they bought. So, Reverse ETL generally is more collaborative with marketing, sales, and support”, says Brian.

Let’s talk about real-life examples illustrating how business teams use Reverse ETL. We got common use cases in marketing, sales, and support.


Personalization might be the most prevalent use case for B2C companies. Specifically, Reverse ETL helps with email personalization. Several companies are using newsletters to communicate with potential and existing customers, usually by creating data-driven email flows, which can vary in complexity and be a part of their lifecycle marketing strategy. “Starting with ‘hi, first name’ up to complicated workflows,” shares Brian.

Companies can enable personalized messages by sending customer data from the warehouse to Mailchimp, which allows them to do things like:

  • Sending the Spanish newsletter to the Spanish-speaking people and the English newsletter to the English-speaking people.
  • Identifying who has bought something and who hasn’t, so they get different emails.
  • Detecting who purchased a specific item and, 30 days later, they get an automatic email asking, “do you want to repurchase this item?”.


In the past, SaaS companies were offering their products, but to get them, you needed to talk to a salesperson as there was no sign-up feature. Those companies had everything they knew about a potential customer in Salesforce, and the account executives' entries would show a progression like “Called prospect at 5:00 pm, they’re very interested”, “Prospect had a demo meeting, it went well, we are negotiating a contract” and then finally “Signed them up.” And that could be the end of the story. 

As more and more companies are transitioning to product-led growth, which is self-serve, they’re interested in knowing more about the actual product usage. “They are essentially asking ‘how can we power Salesforce with data from the actual product’?” says Brian. 

With Reverse ETL, companies can get product usage data into Salesforce and merge it to have a complete product usage view. For example, they can see when a person signs up, does a particular action, or spends a certain amount of money. 


Another increasingly popular use case for Reverse ETL is customer support. By having a complete view of a customer, agents can provide more accurate help. 

“Get phone number data into Zendesk or similar so that when a client calls for support, the information can automatically come up on the agent’s screen, and they'll know that Brian is calling and he recently bought a razor, or he's on the premium sales package and can automatically get routed to the best support agents,” says Brian to exemplify a typical Zendesk Reverse ETL use case.

Best reverse ETL tools


Census is one of the best reverse ETL tools, boasting over 85 integrations with major data warehouses and sources. Its robustness enables the management of massive data volumes, automating data synchronization across multiple sources and providing a single source of truth.


Hevo emerges as a prominent competitor in the reverse ETL market, offering data activation solutions to companies. This cloud-based platform specializes in streamlining data transfer from data warehouses to various downstream applications, such as marketing automation tools and CRM systems.


Hightouch, a reverse ETL tool provider, syncs data from data warehouses to various structures, including CRM, marketing automation, and customer support tools. With connectivity to over 15 data resources, this tool offers a wide range of options for data integration, making it an excellent choice.


Dataddo, though relatively new in the reverse ETL tool landscape, offers approximately five options tailored to CRMs and finance management systems for destination integrations. The platform continuously expands its integrations to include new options.


DataChannel, a flexible platform, provides standard ETL features and offers reverse ETL capabilities. This allows users to transfer data to downstream applications for further analysis or action after extracting it from a centralized destination. Its robust functionality and user-friendly interface empower users to leverage their data for analytics, reporting, and decision-making.

Reverse ETL & The Data Hierarchy of Needs

The hierarchy of needs is a well-known psychological notion developed by Abraham Maslow. It states that individuals must first meet their fundamental requirements before focusing on more complex ambitions.

When comparing Maslow’s hierarchy of needs to a data stack, we realize that the most basic layers in the hierarchy have been addressed: data storage (with data warehouses), data integration (with ETL/ELT), data modeling, and reporting. Some mature platforms and tools fulfill the needs of the areas mentioned earlier. However, there’s an area that’s falling behind: data operationalization

The rise of a new generation data stack reflects an essential trend: companies must transfer data capabilities out of centralized silos (data warehouses) and embed them inside teams across business units. “You get to a point where marketers say, ‘thanks for the report on Metabase, but I'd like to get this data into”, says Brian.

In this sense, the future of the modern data stack includes Reverse ETL solutions that address data operationalization, or in other words, close the operational analytics loop.

In terms of tools, this is what the data stack we picture looks like:

  • Data storage: A data warehouse that can store data in one place like BigQuery, Snowflake, or Redshift.
  • Data integration: ELT tools like Airbyte to integrate your data sources into data warehouses.
  • Data modeling: A transformation tool like dbt.
  • Data reporting: BI and reporting tools like Looker or Metabase.
  • Data operationalization: Reverse ETL tools to pull data out of the warehouse, validate it, and load it into business applications.

Wrapping up

Empowering Business users' to take action requires having fresh, actionable data available whenever they need it in frontline applications like Braze, Salesforce, or Mailchimp.

In this blog post, you learned what a Reverse ETL is, how it is technically different from ETL/ELT, and where it fits in a data stack. The most important takeaways as to why companies benefit from Reverse ETL are:

  • Sending data to business apps may ensure that all systems have a consistent view of the customer.
  • Reverse ETL enables business teams to access the data they require within their apps, from sales to marketing to products.
  • Data operationalization is made possible through Reverse ETL.

If you enjoyed this blog post, you might want to check out Airbyte’s blog. You can also join the conversation on our community Slack Channel, participate in discussions on Airbyte’s discourse, or sign up for our newsletter. Furthermore, if you are interested in Airbyte as a fully managed service, you can try Airbyte Cloud for free!

Reverse ETL FAQs

  1. Why is Reverse ETL important for modern data architecture?
    Reverse ETL plays a crucial role in modern data architecture by facilitating bidirectional data movement between analytical environments and operational systems. This ensures that insights derived from data analysis can be seamlessly integrated into operational workflows, driving real-time decision-making and enhancing operational efficiency.
  2. How does Reverse ETL handle data synchronization and ensure data consistency across systems?
    Reverse ETL relies on robust data synchronization mechanisms and transformation capabilities to ensure data consistency across systems. By leveraging connectors and transformation tools, Reverse ETL platforms enable seamless integration of data from various sources while ensuring accuracy and consistency.
  3. Can Reverse ETL be used to integrate data from different sources and formats?
    Yes, Reverse ETL platforms are designed to integrate data from diverse sources and formats, including databases, cloud services, APIs, and flat files. They offer a wide range of connectors and transformation capabilities to support interoperability across the data ecosystem.
  4. How does Reverse ETL support real-time or near-real-time data processing?
    Reverse ETL platforms leverage efficient data processing techniques, parallelization, and optimization strategies to support real-time or near-real-time data processing. This enables organizations to ingest, transform, and load data with minimal latency, ensuring timely insights and actions.
  5. What role does Reverse ETL play in breaking down data silos within an organization?
    Reverse ETL enables organizations to break down data silos by facilitating bidirectional data movement between analytical environments and operational systems. By integrating analytics with operations, Reverse ETL fosters collaboration, drives innovation, and enhances data-driven decision-making across departments.
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