Book Image

Automating Salesforce Marketing Cloud

By : Greg Gifford, Jason Hanshaw
Book Image

Automating Salesforce Marketing Cloud

By: Greg Gifford, Jason Hanshaw

Overview of this book

Salesforce Marketing Cloud (SFMC) allows you to use multiple channels and tools to create a 1:1 marketing experience for your customers and subscribers. Through automation and helper tasks, you can greatly increase your productivity while also reducing the level of effort required in terms of volume and frequency. Automating Salesforce Marketing Cloud starts by discussing what automation is generally and then progresses to what automation is in SFMC. After that, you’ll focus on how to perform automation inside of SFMC all the way to fully running processes and capabilities from an external service. Later chapters explore the benefits and capabilities of automation and having an automation mindset both within and outside of SFMC. Equipped with this knowledge and example code, you'll be prepared to maximize your SFMC efficiency. By the end of this Salesforce book, you’ll have the skills you need to build automation both inside and outside of SFMC, along with the knowledge for using the platform optimally.
Table of Contents (20 chapters)
1
Section 1: Automation Theory and Automations in SFMC
5
Section 2: Optimizing Automation inside of SFMC
11
Section 3: Optimizing the Automation of SFMC from External Sources
17
Section 4: Conclusion

What is ETL?

ETL has its roots in the rise of central data repositories. With the dawn of data warehouses around the 1990s, tools began being made specifically focused on extracting data from siloed systems, transforming it into the destination format, and then loading it into the new destination (or ETL). Over the years, ETL has grown to become stronger and stronger with the increase in demands during the data age of marketing.

ETL tools typically do all three of the steps and are a critical part of ensuring that data is prepped completely and accurately for things such as reporting, analytics, and other data-driven actions, including machine learning. The following is a basic definition of each of the three steps in ETL:

  • Extract: Retrieving and gathering data from siloed or individual data sources
  • Transform: Manipulating and altering data to fit inside the proper format/structure
  • Load: Taking the final data and pushing it into the target system, database, and...