What is Reverse ETL and How Does It Interact with your CDP?
Simplifying The Facts — CDP vs. Reverse ETL
Data Management — It’s A Need, Not a Want
It’s becoming common practice that businesses are relying heavily on their customer data to inform strategy and decisions. As tech stacks and data scale proportionally, organizations must focus on managing them. Additionally, as we unravel the complexity of data management within organizations, we uncover the importance of unifying data. More specifically, it is crucial to make it equally accessible to technical and non-technical teams. This shift has played a part in the rise of data management roles due to their focus on storing, analyzing, and activating business data. In this blog, we will examine what is Reverse ETL and how it can work in tandem with a CDP (Customer Data Platform) like Simon Data.
Reverse ETL platforms are one of the newer tools and entrants that frequently pop into the data space. Some well-known examples of companies in this space are Hightouch, Census, and Grouparoo. Below, we will dissect what a Reverse ETL is, how they play with CDPs, and use cases where they work in conjunction.
What Is Reverse ETL (… And How Does That Differ From a CDP?)
To understand Reverse ETL, we first need to step back and define what ETL processes are.
ETL is a data integration process that synchronizes multiple data sources into a single destination, such as a data warehouse. It stands for extract, load, and transform, which are the three steps that occur in the process —
Extract: Take the desired data from numerous tools and sources
Transform: Clean (or reorient) the data into a standard format to store it in
Load: Put the transformed data into organized tables that will live inside a data warehouse
Reverse ETL is (not surprisingly) the opposite of the traditional ETL process. Its goal is to take data from your data warehouse and send it back to business intelligence, marketing, sales, and operations tools. This process then makes customer data actionable.
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 data back and forth to your tools. However, Reverse ETL does not provide an interface to activate data into personalized, cross-channel customer experiences. This gap is where a CDP comes into play, presenting an opportunity for Reverse ETL and CDP to work complementary.
Let’s do a quick refresher on what a CDP is. CDPs focus on unifying customer data from numerous disconnected tools and sources, making single profile views of each customer. Therefore, downstream marketing orchestration and business analysis can be more targeted, personalized, and effective.
How Do CDPs and Reverse ETL Play Together?
Are they friends or foes?
Reverse ETL and CDPs have overlapping functionality but can complement one another in organizational tech stacks. While many CDPs have built some reverse ETL functionality into their data management system, they go a step even further. Orchestration CDPs activate data through identity management and cross-channel orchestration in marketer-friendly workflows. Although CDPs often overlap with Reverse ETL functionality, they may be more limited in their integration capabilities.
Aside from facilitating the bi-directional flow of data between data warehouses and various end channels, CDPs uniquely provide strong customer identity models. They create a single profile customer view that comprehensively combines user data that lives across disconnected tools. Without a CDP, you have two options: maintain customer profiles in each end channel, which risks fragmentation. Or, build that logic in your data warehouse, which sacrifices significant time and engineering resources. Though certain Reverse ETL tools like Hightouch allow marketers to filter data, either solution ultimately requires engineering teams. CDPs, on the other hand, make data accessible to marketers with no-code workflows, improving overall time-to-value and efficiency.
In addition, CDPs provide dynamic orchestration functionality that allows marketers to create highly personalized, cross-channel customer experiences. Because all of the actions are defined in the CDP and built on a single customer profile, it drives complete and powerful cross-channel marketing orchestration. This orchestration is responsive to historical and real-time customer behavior thus, optimizing engagement and ROI.
Although there are some distinct differences between CDP and Reverse ETL functionality, they can complement one another in tech stacks. Given their overlapping focus on data management, they have aligned capabilities that make customer data bi-directional and consistent across tools and sources.
Common Use Cases
Now that we’ve gone over what reverse ETL is vs. what CDPs are and how they work, you might be wondering what marketers can do with them.
Here are some of the top use cases for why businesses may want to utilize a CDP and Reverse ETL process together:
Access to Unified Customer Views
One of the most prominent use cases for why an organization needs a CDP and Reverse ETL capabilities is having a comprehensive view of every customer. Businesses spend excessive time and resources engaging with customers across different endpoints, which means collecting customer data across countless channels. Reverse ETL solutions enable data to be moved from collective data warehouses to downstream tools. However, many companies still face challenges identifying customers across their multi-channel endpoints like mobile, web, & offline. Users remain siloed without an identity model to stitch different identifiers together, such as device IDs, cookies, and physical addresses. Ultimately, this results in marketing campaigns that are not personalized, relevant, or targeted.
Marketers need access to single profile views to better segment and target audiences, personalize messaging, and build effective cross-channel campaigns. With a CDP, marketers have access to unified customer views that allow them to build dynamic and highly personalized content. By utilizing real-time customer data and behaviors, marketers can drive campaigns that are much more relevant, targeted, and personalized, resulting in better engagement and increased ROI.
Cross-Channel Customer Journeys
Moving data across end channels is an integral part of data management. However, seamlessly making data accessible within orchestration tools is necessary for data to become actionable to marketers. Having unified, complex data integrated within marketing tools allow marketers to create highly personalized customer experiences through relevant cross-channel journeys, targeted messaging, and timely content delivered how users prefer.
While Reverse ETL alone will consistently maintain data across systems, building consistent experiences across channels can be problematic. Reverse ETL solutions focus solely on data orchestration, which is contained primarily in maintaining and moving data from data warehouses to Saas applications.
On the other hand, CDPs also have data orchestration capabilities. Still, they focus primarily on marketing channel orchestration that allows users to manage their data, but they also make it actionable within downstream marketing orchestration tools. Together, CDPs and Reverse ETL solutions can work harmoniously to control the bi-directional flow of data and allow marketers to build impactful cross-channel customer experiences.
Marketing Team Reliance on IT
Marketing orchestration is slowed down when marketers must rely on technical teams for data management support. Technical teams must also allocate their own time and resources, which takes away from their own initiatives.
CDPs work to enable marketers to be autonomous by providing no-code workflows that allow non-technical users to manage customer data. This data is built directly into marketing orchestration that connects to every end channel for a personalized, cross-channel customer experience, all within one platform. By CDPs either having or partnering with Reverse ETL solutions, marketers can do everything they need to their data in one place, quickly and easily.
Simon Data — Your Complete Cross-Channel Marketing Platform
Simon Data makes it easy to build the right relationship with your customers by enabling users to think like data scientists but act like marketers.
The product is a cross-channel marketing platform that enables marketing teams to transform data into outcomes. Powered by its industry-leading CDP, Simon integrates real-time and historical data into unified customer profiles that enhance sophisticated identity models and predictive capabilities. It surfaces that data in a comprehensive, no-code UI where marketers can build hypersegmented, personalized, and relevant cross-channel experiences within the ease of one platform. Through more targeted messaging and personalization, Simon Data customers get better results built with ease and at scale.
Digitally native businesses rely on Simon to automate growth and results. Simon’s customers include ASOS, Equinox, Venmo, WeWork, Tripadvisor, Vivino, Casper, and Vimeo.