Reverse ETL Explained: Turning Data Insights into Action

Reverse ETL Explained: Turning Data Insights into Action

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ETL vs ELT, Reverse ETL, as the name suggests, is the process of transferring data from a Data Warehouse and sending that data to numerous operational applications, business tools and destinations. This allows you to extend the usage of your Data Warehouse beyond just analysis.

Reverse ETL has gained considerable traction in recent times as companies continue to leverage more tools that need customer data. For instance, say your Sales teams are using CRMs like Salesforce and HubSpot to track all their deals and leads.

As they try to improve their Lead Acquisition Rate, they would need richer data in Salesforce and HubSpot to properly understand who these customers or leads are, whether they’re likely to churn, how they’re using your products, and everything in between.

With Reverse ETL you can also sync groups and profiles across your tools.

Understanding the Need for Reverse ETL

an illustration of etl

Reverse ETL becomes necessary as your Data Warehouse, in the process of eliminating Data Silos, runs the risk of becoming a Data Silo itself. Without Reverse ETL, your business’ core definitions only reside within the Data Warehouse.

Reverse ETL has emerged as an essential cog in the Modern Data Stack to close the gap between analysis and activation/action. This practice is called Operational Analytics (the practice of taking your data and turning it into action).

Armed with more trustworthy and better data in your Marketing tools, you can easily drive better growth, build better experiences for your users, and have more targeted communications and emails.

It also allows sales teams to better personalize their Sales discussions based on how their accounts and leads are using their product.

Key Use Cases of Reverse ETL

Here are a few key use cases of Reverse ETL:

1) Data Automation

In any organization, there are various manual data requests floating around for CSVs and other files. As with any other manual process, there lies the question of effectively automating it to improve efficiency.

With Reverse ETL, SQL is all you need to extract data from the Data Warehouse and sync it to external tools. This makes Reverse ETL the simplest solution for Data Automation in the workplace.

2) Data Infrastructure

Reverse ETL is also emerging as a general-purpose pattern in Software Engineering and Data Infrastructure. The two use cases that have emerged in this field are accessing disparate data sources and personalization of customer experiences.

For instance, your data team crunches a score on top of the Data Lake or Data Warehouse that describes the user’s likelihood of buying a product. Now your Product team wishes to drive more purchases by providing discounts to users who are deemed unlikely to make a purchase.

Here, your Data Warehouse is too slow to serve user-facing experiences which poses a problem. An easy solution to this problem would be to use Reverse ETL, to move the propensity score to a production database to serve customers’ tailored in-app experiences in real-time.

Reverse ETL can also sync relevant CRM information from your Data Warehouse into the production database that fuels your app or product. Your product or app can then show your customers their billing information just like any other data.

This is a use case of Reverse ETL providing a novel solution to accessing disparate data sources. By choosing to use Reverse ETL, you don’t have to redo the complicated work of integrating with the APIs of tools like HubSpot and Salesforce.

You can also reuse the business definitions you’ve already created in SQL.

3) Operational Analytics

Every team wishes to be more data-driven, but this quest has two main components. Deriving Insights from data and “Analytics Enablement”, or translating those insights into action.

A traditional approach to analytics enablement is to train the Sales Reps on how to leverage BI reports as a part of their day-to-day workflow.

But this is tough to implement. This is where Operational Analytics can come to the rescue. As opposed to the traditional approach, the Data Analyst can operationalize their analysis by entering lead scores from the Data Warehouse into a custom field in Salesforce.

Operational Analytics provides your reps with key insights from your analytics that lets them take the necessary actions more effectively.


This article gives a brief overview of the concept of Reverse ETL. It talks about the need for Reverse ETL and the key Use Cases of Reverse ETL in detail.

A fully managed No-code Data Pipeline platform like Hevo helps you integrate and load data from 100+ Data Sources (including 40 Free Data Sources) to a destination of your choice in real-time in an effortless manner.

Hevo further supports a Native Reverse ETL solution called Hevo Activate. It helps you directly transfer data from Snowflake, Amazon Redshift, Google BigQuery, etc., to SaaS applications,

CRMs such as Salesforce, HubSpot, etc., Support tools such as Zendesk, Intercom, and a lot more, in a completely hassle-free & automated manner.


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