Salesforce Marketing Cloud is a marketing service used for digital marketing through various media, such as emails or social media platforms. You can use it effectively for customer data management, but it does not facilitate efficient data storage. To resolve this limitation, you can integrate Salesforce with data warehouses like Snowflake.

Snowflake It allows you to store customer data in an organized manner, which can then be accessed for in-depth analysis. Moreover, Snowflake also offers better scalability and flexibility, enabling you to perform advanced data analytics. 

This article explains the two methods for Salesforce Marketing Cloud to Snowflake integration to help you standardize your data workflow and analysis procedures. 

Why Integrate Salesforce Marketing Cloud to Snowflake? 

You should integrate Salesforce Marketing Cloud into Snowflake for the following reasons:

  • Since Salesforce Marketing Cloud is a digital marketing platform, it does not allow you to store or work with your data. Snowflake provides database and data warehousing solutions that facilitate effective data storage. 
  • Snowflake is scalable and easily compatible with various data sources, which allows you to use it for advanced data analytics. 
  • By integrating with Snowflake, you can avoid unnecessary storage of extra data in Salesforce Marketing Cloud beyond the frequently required campaign data. 
  • Integrating Salesforce Marketing Cloud to Snowflake can help store important data related to customers or sales at a central location. This consolidated data can then be used to analyze metrics related to customer behavior or revenue generation. 
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Salesforce Marketing Cloud Overview

Salesforce Marketing Cloud is a marketing platform of Salesforce that provides automation and analytics software services to streamline your marketing strategy. You can use it to market your products or services through different channels, such as email, social media, mobile apps, SMS, websites, etc.

To support your marketing efforts, Salesforce Marketing Cloud offers Studio and Builders modules. Studio manages content and marketing channels, while Builder manages enterprise data and campaign automation. Salesforce Marketing Cloud also helps you manage B2C and B2B relationships and allows Customer Retention Management (CRM). 

Snowflake Overview

Snowflake is a fully managed SaaS platform that provides data warehouse, engineering, and application development services. It also enables you to share and consume real-time data securely. Snowflake is a cloud-based service that allows you to access and maintain your data infrastructure from anywhere. You can upload data in a semi-structured or structured form to the Snowflake database before processing and analysis. Also, it provides optimized performance by separating computation from storage, which is not available in most databases. 

Methods of Salesforce Marketing Cloud

Here are two methods for Salesforce Marketing Cloud & Snowflake integration: 

  • Method 1: Using Hevo Data for Salesforce Marketing Cloud to Snowflake
  • Method 2: Using the Zero ETL Method for Salesforce Marketing Cloud to Snowflake Integration

Method 1: Using Hevo Data for Salesforce Marketing Cloud to Snowflake Integration

Hevo Data is a no-code ELT platform that provides real-time data integration and offers a cost-effective way to automate your data pipelining workflow. With over 150 source connectors, you can integrate your data into multiple platforms, conduct advanced analysis on your data, and produce useful insights.

Here are some of the most important features provided by Hevo Data:

  • Data Transformation: Hevo Data allows you to transform your data for analysis with a simple Python-based drag-and-drop data transformation technique.
  • Automated Schema Mapping: Hevo Data automatically arranges the destination schema to match the schema of the incoming data. It also lets you choose between Full and Incremental Mapping.
  • Incremental Data Load: It ensures proper bandwidth utilization both on the source and the destination by allowing real-time data transfer of the modified data.

Step 1: Configuration of Salesforce Marketing Cloud as Source


After ensuring that all the prerequisites are fulfilled, you can use the following steps to configure Salesforce Marketing Cloud as a source in Hevo:

  • From the Navigation Bar, click PIPELINES.
  • Click + CREATE in the Pipelines List View.
  • Select Salesforce Marketing Cloud on the Select Source Type page.
  • In the Configure your Salesforce Marketing Cloud Source page, specify the following:
Salesforce Marketing Cloud to Snowflake: Configure source
Configure Snowflake Marketing Cloud as Source

For more information on the configuration of Salesforce Marketing Cloud as a source, refer to the Hevo documentation

Step 2: Configuration of Snowflake as Destination


  • Ensure that you have access to an active Snowflake account.
  • To create a new role for Hevo, you must have the ACCOUNTADMIN or SECURITYADMIN role in Snowflake.
  • To create a warehouse, you must have the ACCOUNTADMIN or SYSADMIN role in Snowflake. 
  • You should assign USAGE permissions to Hevo on data warehouses and databases.
  • You should ensure that Hevo is assigned USAGE, MONITOR, CREATE TABLE, CREATE EXTERNAL TABLE, and MODIFY permissions on the current and future schemas.
  • To create the destination, ensure that you are assigned the Team Collaborator or any administrator role except the Billing Administrator role in Hevo.

After ensuring that all prerequisites are fulfilled, follow the steps given below to configure Snowflake as a destination in Hevo:

  • Click DESTINATIONS in the Navigation Bar.
  • Click + CREATE in the Destinations List View.
  • In the Add Destination page, select Snowflake as the Destination type.
  • In the Configure your Snowflake Warehouse page, you can specify the following:
Salesforce Marketing Cloud to Snowflake: Configure Destination Settings
Configure Destination Settings

For more information on the configuration of Snowflake as a destination, refer to the Hevo documentation

Method 2: Using the Zero ETL Method for Salesforce Marketing Cloud to Snowflake Integration

You can use the zero ETL integration method for Salesforce Marketing Cloud Snowflake integration. It leverages Snowflake’s Iceberg Tables and Secure Data Sharing features for data integration. 

First, ensure you have access to a Snowflake account and a Salesforce Data Cloud account. You can follow these steps to integrate Salesforce Marketing Cloud with Snowflake: 

  • Log in to the Salesforce Data Cloud instance and select Salesforce Marketing Cloud as an application cloud object to create a Data Share
  • Select the Snowflake target account and perform an OAuth against it. You should then validate the target and create a Snowflake Data Share target.
  • Now, connect the Salesforce Data Cloud Data Share object with the Snowflake target inside the Salesforce Data Cloud experience option. 

After completing the process, the Data Share automatically becomes available to the Snowflake target account as secure views. You can accept this shared data and start analyzing it securely in Snowflake. 

Limitations of Using the Zero ETL Method for Salesforce Marketing Cloud to Snowflake Integration

There are some limitations associated with the zero ETL integration method, such as:

  • Absence of Standard System: Gathering data from multiple sources makes it difficult to create a standardized zero ETL solution that can efficiently handle different data sources. Also, the cost of zero-ETL integration from varied sources is higher than the usual ETL process. 
  • Data Security: The zero-ETL method can pose potential security threats to your sensitive data. It does not facilitate encryption at rest and in transit, access control mechanisms, or audit trials provided by traditional ETL solutions. 
  • Expertise: You are expected to have expertise in managing distributed systems, data streaming, and real-time analytics while implementing the zero ETL method. 

Use Cases of Snowflake Marketing Cloud to Snowflake

Some of the use cases of Salesforce Marketing Cloud Snowflake integration are:

  • Optimized Performance: You can use SnowSQL to enter manually curated trade data directly into the tables. Snowflake’s Snowpark libraries can help you create user-defined functions in various programming languages like Python or Java. These functions can speed up data processing by transferring a significant amount of workload to native systems. You can also use Snowflake to access a multi-cluster warehouse and run several high-load queries simultaneously. 
  • Business Intelligence: Snowflake can be easily integrated with BI tools like Looker, Power BI, or Tableau. This enables you to create interactive reports and gain useful business insights. 
  • Machine Learning: Snowflake’s zero-copy cloning function can collect data to deploy machine learning algorithms. It also supports programming languages used for machine learning, such as Python, Java, C++, etc. 


This blog comprehensively explains how to sync data from Salesforce Marketing Cloud to Snowflake and provides two methods for data integration. While you can use the zero ETL method, it does not have a standard format and may result in data security issues. To eliminate these limitations, you can use Hevo for Salesforce Marketing Cloud to Snowflake data integration. Hevo’s zero-code and real-time data pipeline-building capabilities, extensive library of connectors, and monitoring features make it one of the best data integration platforms. You can schedule a demo to leverage these Hevo features for data ingestion from Salesforce Marketing Cloud to Snowflake and optimize your workflows. 


  1. How can you use Salesforce Marketing Cloud for customer retention?

Salesforce Marketing Cloud allows you to centralize your data, which can be analyzed to create targeted marketing campaigns. This can help you increase customer engagement, understand their needs, and enhance your product, resulting in increased customer retention

  1. What are the disadvantages of using Snowflake?

The primary disadvantages of Snowflake are its high costs, absence of support for native cloud integration, and limited acceptance of unstructured data. 

Shuchi Chitrakar
Technical Content Writer

With a strong background in physics and journalism, Shuchi has an avid interest in writing about the latest happenings in the technological world, especially data science. She has written several articles related to data engineering and data analytics. To broaden the scope of her knowledge, Shuchi constantly strives to learn new skills related to data science and AI.

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