In today's data-driven business environment, companies rely heavily on data to make informed decisions and gain a competitive edge. However, managing and utilizing data can be a complex and challenging process.

Here are the 4 key takeaways from this article:

  • Reverse ETL helps businesses transfer clean, accurate data from source to destination in real time.
  • Businesses should consider factors such as speed, security, fallback/alert systems, and ease of use when selecting a reverse ETL tool. 
  • It helps automate certain tasks like finding customer data points and updating product information on websites.
  • Reverse ETL tools should be cost-effective to scale up, and pricing plans should be flexible.

One of the key challenges businesses face is transferring data from source to destination in real time while ensuring that the data is accurate, reliable, and secure. This is where Reverse ETL comes in - it helps businesses transfer clean, accurate data from source to destination in real time. In this article, we will explore what businesses should keep in mind when selecting a Reverse ETL tool.

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Extract, Transform, Load (ETL), and Extract, Load, Transform (ELT) pipelines are standard data management techniques among data engineers. Indeed, organizations have long been using these processes to create effective data models.

However, there has recently been a remarkable rise in the use of Software-as-a-Service (SaaS) based customer relationship management (CRM) apps, such as Salesforce, Zendesk, Hubspot, Zoho, etc., to store and analyze customer data. In fact, around 91% of organizations with at least 11 employees use a CRM system.

Organizations use these applications to get relevant insights for making data-driven decisions. They should have a foolproof solution to seamlessly integrate their data sources into SaaS applications. And this is where reverse ETL solutions come in.

What is Reverse ETL?

Reverse ETL, as the name suggest, reverses the ETL workflow. It is a process of transferring data from sources, such as databases, data warehouses, or lakes, to destinations like CRM and ERP apps or other SaaS tools that require data as input.

Reverse ETL vs. ETL and ELT – Which One to Use?

Organizations use data warehouses and data lakes as the primary source of truth, storing all their data from different sources. However, it requires data teams to use specialized business intelligence solutions to analyze the data in such data storage platforms directly.

As such, they use the CRM apps mentioned earlier to perform all their analysis and generate management reports for everyday usage.

However, the problem is that organizations have to transfer the data yet again from data warehouses and lakes to such CRM apps.

Traditional ETL and ELT solutions are not enough to carry out such operations. A typical ETL pipeline ingests raw data from several data sources, such as consumer apps, the internet, or internal business applications, and applies several transformations to clean, filter, aggregate, and merge the data. Finally, it loads data in a destination like a database or a data warehouse.

ELT is similar; the only difference is that it loads the data and then applies the necessary transformations.

Nevertheless, such typical pipelines are suitable for businesses whose data infrastructure involves bi tools and customized dashboards to view and analyze data. However, approaches like these become a bottleneck if business users mostly spend time working with CRM applications.

Organizations should therefore have a system that updates these applications in real-time with accurate data so that relevant teams can derive insights more conveniently.

Since Reverse ETL takes data from warehouses and lakes and delivers it to other saas apps, it is appropriate for organizations that want to make quick data-driven decisions without spending much time learning other bi tools.

Benefits of Reverse ETL

Before the time of reverse ETL, businesses used to build their own Application Programming Interface (API) connectors to integrate their data warehouses into operational applications. However, creating and maintaining such connectors is resource-intensive  and time-consuming.

So for one, reverse ETL allows companies to avoid the inefficiencies of such connectors and, instead, benefit from an out-of-the-box solution to establish streamlined data workflows. But there are other benefits to reverse ETL, as discussed below.

Increases Operational Efficiency

Through Reverse ETL, employees can work directly on business apps that let them get more contextualized insights rather than just detecting patterns and anomalies. Indeed, making predictions based on past trends without meaningful context is poor practice.

Sound predictions require subtle assumptions and domain knowledge that is only possible if domain experts can easily access and use the tools they have expertise in. In fact, the very practice of delivering data insights to downstream SaaS applications is known as operational analytics.

Operational analytics breaks the silos between the data and business teams by incorporating data-driven insights into day-to-day operations. 

Helps with Data Governance

Since reverse ETL helps build a more unified data workflow, it allows organizations to implement better data governance practices. Data governance ensures that different teams can easily access and use domain data while maintaining the security and integrity of several data sets.

The very purpose of reverse ETL is to provide wider accessibility of data to teams across organizations so they can work on platforms they are familiar with. 

Also, as reverse ETL processes use data warehouses or lakes as their source, they ensure data integrity by using a single source of truth. It allows data engineering teams to maintain security through centralized access management.

Provides Scalability through Interoperability

As a business grows, it may have to deal with an ever-increasing volume of data from various sources. Analyzing such a vast amount of data may require teams to have not  only access to domain-specific data but data from other functions as well.

For example, the marketing team may require financial data to understand the revenue impact of a particular advertising campaign. As such, it would require historical data on the profitability of similar campaigns in the past.

Such interoperability will only be possible if each team can access different data types through all the SaaS applications they use. By providing valuable data directly to business users, Reverse ETL will prevent the need to constantly send access requests to central data teams and wait until access is granted.

It will therefore help organizations to scale up business operations quickly as teams will be more agile. 

Allows for Product/Service Personalization

Organizations today must add an extra level of personalization to their products or services to remain competitive. For example, E-commerce sites may send product recommendations based on a customer’s purchase history.

Such personalization is possible only if the relevant teams have access to the latest customer data. They can then use it to identify useful patterns or pain points to provide better customer support and ensure a smooth customer experience.

Reverse ETL can make this happen as it involves automated pipelines that constantly update all the relevant systems to reflect the most current state of truth regarding customer behavior. 

Why Do Businesses Need Reverse ETL Now More Than Ever?

By leveraging Reverse ETL, businesses can ensure reliable and consistent customer data across all systems in real-time, enabling teams to quickly identify trends and take action for a better customer experience. 

Reverse ETL helps businesses reduce time spent on manual processes and maintain data accuracy across systems. By streamlining and automating manual tasks, businesses can stay on top of their operations while also focusing their attention on other areas of the business. This helps them remain agile and competitive in today’s ever-changing digital landscape. 

Modern Data Stack

In today’s digital era, data is a valuable asset for almost every type of organization. Reverse ETL allows for leveraging this value through effective data automation that boosts productivity by breaking team silos and improving decision-making.

But that’s just the beginning. Traditional ETL and ELT pipelines are no longer suitable for working with the so-called modern data stack (MDS). MDS is a collection of products or services that companies use to unify data from myriad sources for quick use and analysis.

Unlike the traditional data stack, MDS focuses more on data integration, accessibility, and governance. The MDS architecture is usually cloud-native, which allows for scalability and operational efficiency.

One of the significant benefits of the MDS is that it allows organizations to have a deeper view of their customers’ profiles. In fact, MDS works with customer data platforms (CDPs), such as Insider, Bloomreach, Kalviyo, etc., to help marketing teams get a 360-degree view of the customer.

Together with CDPs, MDS helps improve operational analytics, which, as discussed earlier, allows teams to carry out daily operations based on real-time data feeds.

MDS components

A brief overview of the MDS components will help understand the role of reverse ETL. There are essentially six components, as listed below.

  • Data sources - This component involves the sources from which an organization fetches raw data. As discussed, it can include databases, data warehouses, or even SaaS applications.

  • Data Integration - This is the component where traditional ETL or ELT pipelines come into play to extract and load the data into relevant destinations. It may also cover data transformation depending on the processes that companies use.

  • Data Storage - Data storage covers centralized repositories like data warehouses or data lakes, such as Snowflake, Redshift, or Google BigQuery, where ETL processes load the data.

  • Data Transformation - As mentioned, data transformation may happen during integration. However, it is common for transformation to occur within data warehouses using data build tools (dbt) such as Apache Airflow or LookML through SQL commands.

  • Data Governance - The next component relates to governance, where the focus is on creating data privacy standards and data catalogs and establishing metrics to measure the effectiveness of data pipelines.

  • Data Usage - The main result of all components is to deliver the data in a shape and form readily usable by relevant teams. Business executives can use the data for business intelligence, whereas,   data teams can use it for analytics by directly querying the data storage platforms.

However, it is more efficient to put the transformed data back into SaaS applications so that operational teams like the sales, marketing or finance can use it in an environment they are most familiar with. And it is here where reverse ETL tools such as, Hightouch, or Census come into play which can sync data in warehouses with other applications.

Since reverse ETL allows for such an integrated approach to data usage, it has several use cases.

Other Use Cases of Reverse ETL

Driving Customer Success

Customer success managers can directly refer to CRM systems to get vital information on product usage and get an idea of customer churn rate. They can then use the data to reach out to such customers to up-sell and increase customer retention more effectively.

Marketing Automation

Marketing automation involves automating specific workflows such as sending emails, and newsletters, posting social ads, giving recommendations, etc. The purpose is to spend less time on repetitive tasks and give customers a more personalized touch.

However, automation tools use CRM systems as their source for directing a customer’s journey. For example, data points in the CRM may indicate that a customer needs help from a customer rep. The automation tool can identify this touchpoint and perhaps notify a customer rep to contact the customer.

However, for this to happen, the data in CRM must be accurate. Reverse ETL solutions can be a great help by ensuring that CRM applications receive clean and correct data.


E-commerce websites require constant updates to product information so that customers visiting the site across the globe do not face any inconvenience. For example, the website should reflect the unavailability of a product if it is out of stock.

It would be a hassle for a customer if the information is not present and they order the item only to find later that it is unavailable.

As such, organizations integrate their E-commerce sites with inventory management tools to ensure that everything is up-to-date. Reverse ETL solutions can help by loading the latest product information into these tools in real time.

Selecting the right Reverse ETL Tool?

Given the importance of reverse ETL, organizations should select a suitable reverse ETL tool to help them with their automation efforts. Below are some factors businesses can consider before purchasing a reverse ETL tool.


Businesses should consider the speed at which the reverse ETL tool syncs data from source to destination. The tool should connect easily with several data platforms and build robust connections for quick data transfer. It also means that the tool is compatible with the existing tech stack.


The tool should encrypt data while syncing is in process. Also, the tool itself should not store any data. Its only job is to move data from one point to the other. 

Fallbacks and alerts

No matter how reliable a tool is, it should always have a fallback mechanism. In the case of reverse ETL tools, they should immediately notify relevant team members when syncing fails and perhaps restore the data to its original state if the process stops mid-way.

Also, it should provide detailed event logs so that data engineering teams can identify the records that did not sync. Businesses should also see if the platform causes data loss during syncing.

Ease of Use

The tool should allow users to build reverse ETL pipelines quickly with minimal code. It should support common programming languages and allow the users to write simple queries to create custom pipelines.


Lastly, the tool should provide value for money. It should be relatively inexpensive to scale up, and pricing plans should be flexible to match specific organizational needs. for Reverse ETL is one tool that stands out in the reverse ETL market. It is a secure and affordable platform that is easy to use and allows users to integrate conveniently with popular CRM and data management platforms through its Representational State Transfer (REST) APIs.

It is a low-code solution that allows customers to build secure data pipelines within hours and lets them customize the platform through its rich expression language, advanced API, and webhooks.

So book a demo now and transform your business for success.