Increased customer demands, new competitors, and economic factors all require companies to act faster to remain competitive. Without access to real-time information to drive decision-making, the process is laboured, fraught with frustration, and often results in poor revenue numbers.
Reverse ETL is an emerging piece of the data stack that puts valuable customer data back into third-party operational apps to drive rapid and more accurate decision-making. This guide will cover what Reverse ETL is and what Reverse ETL is used for.
Reverse ETL in a Nutshell
Extract, Transform and Load (ETL) has been the standard data processing strategy since the 1970s. The core premise of ETL is to enable companies to extract information from siloed systems and merge it into a common storage mechanism commonly known as a data warehouse.
Reverse ETL is the opposite of this, where companies can copy synched, formatted information from the warehouse to operational third-party apps such as HubSpot, Salesforce, Zendesk, and more. The process synchronizes data on a recurring schedule or when triggered by a request from a third-party app through an API (Application Programming Interface) call.
This approach is a key operational strategy that helps close the loop on customer information by integrating it back to key operational systems. Putting more comprehensive knowledge back into the hands of front-line team members such as sales and marketing empowers them to make more accurate and more confident business decisions. It also improves the customer experience when these front-line personnel have the information necessary to provide a more tailored customer experience.
Why Would I Move Data Out of the Warehouse?
It seems backward right? You just spent all that time dumping data into the warehouse, why on earth would you want to move it anywhere else? The answer lies in the functional differences between the warehouse and the operational systems that rely on the data.
Historically, data warehouses have been used to analyze information for long-term trends to inform long-term strategy. But what happens when the business needs to make strategic decisions in real-time? Users can certainly use business intelligence tools and queries to analyze the data. However, this approach creates a barrier between the operational systems and the information on which they rely. The result is a slower response to day-to-day challenges which ultimately impact a company’s competitive edge and profitability. That’s where Reverse ETL comes in.
The Business Value Revealed
Organizations that can respond quickly to a rapidly changing market often see an increase in financial performance by 20-30 per cent and an increase in operational performance by 30-50 per cent. The key to such agility is access to real-time information that can transform immediate and accurate insights into customer information.
Reverse ETL’s strong focus on customer data puts key content from the warehouse back into the apps used by front-line people who need to make quick decisions based on the information.
What Can I Do with Reverse ETL?
Reverse ETL is about more than moving content from one system to another. The process supports a variety of use cases across the entire organization. Teams such as sales, marketing, product development, and customer support can benefit from having access to more comprehensive information to support their business functions. The use cases for this strategy are wide-ranging and include:
Day-to-day decision-making based on operational analytics means everyone in the organization can make smart business decisions. Operational analytics is instrumental in:
- Building More Comprehensive Customer Personas – Using a more comprehensive set of information sources helps teams plan effective strategies to ensure maximum revenue.
- Creating More Granular Audience Segments – When organizations combine multiple information sources, they have additional demographic information and important data to more accurately segment customers. As a result, companies can build more effective customer outreach programs.
- Better Lead Scoring – New leads are critical for growing a business. This strategy can provide sales reps with more comprehensive information needed to follow up on the most valuable leads.
- Improved Operational Reporting – Pulling content from multiple sources into an operational system provides more granular reporting options.
Consider the following example: a marketing manager plans a personalized marketing campaign. Rather than relying on one data source, they may leverage information from product, sales, and support to build a more personalized campaign. This approach helps them create a campaign that targets a customer’s specific needs rather than a generic campaign. The result is a positive customer experience and can cause a greater response rate to marketing campaigns.
It’s not always complex problems that benefit from this technique. Sometimes, the request can be as simple as pulling content into a CSV to process invoices from a cloud-based accounting system. Performing ad hoc requests and simple automation tasks can be performed through this process rather than bogging down the data warehouse.
In recent years, reverse ETL has become more than just a data extraction technique. Given the growing number of data sources and business needs, it is a strategy that is an emerging component in the data stack and a standard software development pattern.
Ensuring information is safe, usable, and accessible can be a challenge. Using reverse ETL provides a single framework for managing quality control, improving, monitoring, and maintaining the integrity of key decision-making data.
As organizations face increasing competition and customer demand, agility and speed are imperative to the business’s survival. Reverse ETL allows organizations to copy synched, formatted information from their data warehouse and send them to operational third-party apps such as HubSpot, Salesforce, Zendesk, and more. This emerging strategy enables companies to make the real-time data-driven decisions needed to maintain their competitive edge. The use cases for Reverse ETL include operational analytics, data automation, data infrastructure, and data governance.