Reverse ETL: What Is It & Why It’s Important

Since the 1970s, organizations have recognized the benefits of the ETL (extract, transform, load) process for consolidating data from disparate sources into a centralized platform such as a data warehouse. 

Traditionally, this data has been used to power business intelligence (BI) dashboards for reporting. But today, it is more valuable to analysts, business teams, and marketing teams if it’s accessible to the frontline tools that drive their day-to-day operations, such as HubSpot and Salesforce.

This is where Reverse ETL comes in. Reverse ETL technology moves cleaned, optimized data from a data warehouse into third-party frontline tools. This gives you access to accurate, real-time customer data to power your workflows and marketing campaigns.

Here we’ll discuss the ins and outs of Reverse ETL and how it transforms marketing strategies and decision-making.

What is Reverse ETL?

Reverse ETL is a process by which data is extracted from a data lake or warehouse and sent to SaaS applications, like customer relationship management (CRM), marketing automation, advertising, and customer experience tools. 

Data in a data warehouse is an aggregation of an organization’s most accurate, up-to-date data. It serves as a “single source of truth.” But this data is often only accessible to technical users who know how to write SQL and Python scripts. 

The Reverse ETL process replicates data from the data warehouse into the third-party systems employees use daily. This process allows them to get the data and insights they need faster, instead of relying on IT teams or data engineers to process the data. 

Why Reverse ETL?

Without Reverse ETL, valuable data and insights can remain locked away within your data warehouse. This is data that marketers need to create personal, data-informed strategies to improve your customer relationships. 

A Reverse ETL solution offers three main benefits:

  1. Operationalizing data: Reverse ETL allows you to operationalize relevant data by sending it to SaaS applications—for example, importing consolidated customer data from the data warehouse into Salesforce. A Reverse ETL pipeline is the key to improving your sales processes and making your data usable for marketing campaigns.


  1. Reducing reliance on IT: Reverse ETL technologies offer no-code, easy-to-use plug-and-play features. This allows sales and marketing professionals to access the data they need without relying on IT or data teams.


  1. Improving the customer experience: Reverse ETL transfers data in real time. Having access to the most up-to-date data enables sales and marketing teams to make the best decisions based on current customer needs. 

The ETL process 

To better understand the Reverse ETL process, let’s first take a step back and look at ETL.

ETL is a data integration process that allows you to extract data from different applications and import it into a data warehouse. The process takes raw data from several tools and data sources, transforms it into a usable format, and loads the transformed data into the target data warehouse. 

The three steps of the ETL process are extract, transform, and load: 

1. Extract

The first step in the ETL process is to import and consolidate structured and unstructured data into a single repository. Data is extracted manually or with automated tools from a wide variety of sources, including existing databases, legacy systems, sales and marketing applications, CRM systems, and analytics tools. 

2. Transform

The transformation phase of the ETL process ensures data quality, integrity, and accessibility. During this process, the data can go through several stages:

  • Cleansing: Removing inconsistencies and missing values 
  • Standardization: Conforming to specified formatting rules and naming conventions
  • Deduplication: Excluding or discarding redundant data
  • Verification: Flagging anomalies and removing unusable data
  • Organization: Sorting and grouping according to data type

3. Load

This step in the ETL process loads the transformed data into a new data repository such as a data lake or data warehouse. Data can be loaded in full or incrementally. With full loading, the transformed data is stored in unique records in the data warehouse. Incremental loading compares incoming data with existing data in the data warehouse and only creates additional records if it finds unique information. 

Advantages of ETL

There are several advantages for organizations using the ETL process to consolidate data:

Timely access to data: ETL merges data from multiple sources into a single repository and transforms it into a useful format. As a result, it improves access to valuable information that drives strategic and operational decision-making. Instead of piecing together siloed data, business leaders have access to useful data aggregated from multiple sources.

Data quality: The ability to remove data inconsistencies, redundant data, and unusable data during the transformation stage makes data more consistent. Data has increased quality and integrity. 

Ease of use: Most ETL applications are no-code and provide graphical user interfaces (GUIs) that allow business users to create ETL processes without programming knowledge. Users operate a drag-and-drop interface and specify rules to map the flows of data in a process.

Capacity for big data: Today’s ETL tools handle massive amounts of big data without compromising process and sync speed.

What does this have to do with Reverse ETL?

Reverse ETL is how you make use of all this data. Where ETL prepares the data and moves it into a central location, Reverse ETL moves it in the opposite direction—from the source (e.g., data warehouse) into third-party business tools and applications.

This means you can create a data pipeline from modern data platforms like Amazon Redshift, Snowflake, and Google BigQuery to Salesforce and other frontline applications. With Reverse ETL, you can make use of both structured and unstructured data.

Common use cases for Reverse ETL

Here are some ways businesses are taking advantage of Reverse ETL:

Customer service

Customer service employees represent your company’s brand and significantly impact customer satisfaction. But they need access to the right information to deliver personalized customer experiences. 

A Reverse ETL pipeline syncs customer data from your data warehouse to various support channels, such as Zendesk and Help Scout. This gives customer success teams access to important metrics related to customer profile data and service history. With up-to-date, actionable customer data, support teams can more successfully engage with customers. 


Sales teams often have to navigate multiple tools and platforms to gather product usage data. This makes it more challenging to get the detailed information they need to nurture potential leads and identify high-value accounts.

With a Reverse ETL solution, sales teams import aggregated customer data from several data sources into their CRM software. Having all the data in one place enables them to make more meaningful connections and increase their conversion rates. 


To deliver a great customer experience, marketers need to bring together information about the customers’ behavior through the entire marketing funnel. Using Reverse ETL, marketing teams can send customer data from product, sales, and customer support to their own marketing automation tools, like HubSpot.

With all this data gathered into one platform, they can identify which content or channel triggered the customer journey, view customer purchase history, and segment leads based on demographic and behavioral data. A holistic view of the customer journey enables marketing teams to create more personalized and effective campaigns.

Why you still need a CDP

At first glance, Reverse ETL may appear like the perfect solution to completing your data stack. You have a warehouse that stores data and, now, a solution that moves all that data back and forth to your tools. 

However, Reverse ETL does not provide an interface to activate your data into personalized, cross-channel customer experiences. This gap is where a customer data platform (CDP) comes into play. 

A CDP unifies all your customer data and consolidates it into a single profile view for each customer. This results in downstream marketing orchestration and business analysis that are targeted, personalized, and effective

How does Reverse ETL interact with your CDP?

Reverse ETL and CDPs have some overlapping functionality, but they complement each other in organizational tech stacks. Their aligned capabilities make customer data bi-directional and consistent across tools and sources.

Besides facilitating the bi-directional flow of data between data warehouses and various end channels, CDPs uniquely provide strong customer identity models. By creating single customer views, they combine all the user data that lives across disconnected tools into easy-to-access customer profiles.

Without a CDP, you would have two options:

  1. Maintain separate customer profiles in each end channel, risking data fragmentation.
  2. Build that logic into your data warehouse, sacrificing significant time and engineering resources. 

Though some Reverse ETL tools allow marketers to filter data, this solution still ultimately requires the work of an engineering team. CDPs make data accessible to marketers with no-code workflows, improving overall time-to-value and efficiency.

In addition, CDPs provide powerful, dynamic orchestration functionality that allows marketers to create highly personalized, cross-channel customer experiences. All the actions are defined in the CDP and built on single customer profiles, based on each customer’s behavior. This translates to optimized customer engagement and ROI.

Simon CDP: Your complete cross-channel marketing platform

Simon Data enables marketing teams to transform data into outcomes. Powered by an industry-leading CDP, Simon integrates real-time and historical data into unified customer profiles that enhance sophisticated identity models and predictive capabilities. Through more targeted messaging and personalization that are built and scaled with ease, Simon Data customers get better results.

Request a customized demo to find out how Simon Data can help you align your CDP with Reverse ETL capabilities for consistent, bi-directional customer data across all your tools and data sources. 

Case Studies

Request a Demo