What is Behavioral Data Enrichment? 4 Things To Know


When it comes to one of the most important assets that a company can own that empowers departments to be able to drive forward customer experience, data is king. Every single interaction and key event in the digital world creates data of some kind and for many companies, data from one event or user can be created by several different tools. When it comes to the departments that use data, such as sales, marketing, customer support, and others, they all have unique SaaS tools that allow them to accomplish their goals. 


One of the greatest challenges that companies face is never creating data but instead being able to adequately and powerfully use it. This is a challenge for a number of reasons. When data is created but is either hard to access, or unusable, it forms a data silo. A data silo has limitless potential for how it can help a company, but there are barriers to this potential. For a long time, the ultimate solution to this kind of problem has been found in the data warehouse. 


This process of taking data from a silo and converting it to usable and functional data that is then stored in a warehouse or lake house is called ETL. ETL stands for Extract, Translate, Load, which is descriptive of the three steps it takes to make data useful. Even though using ETL to create data stacks that are useful to a company has been shown to be effective, there are always ways of improving the system. 


Not only that, but ETL and warehouses on their own oftentimes can create situations where data again becomes unusable or hard to access. The true challenge is to create systems and methods of accessing data that leverage a team’s time in a way that positions their department for success. One way of helping make this idea come together is data enrichment


If you have been wondering what behavioral data enrichment is, here are four things you should know you should know! 

1. What is Data Enrichment?

Technically, data enrichment could be described as the entire ETL process. Data enrichment involves taking data and making it more valuable by adding information to fields that may be lacking. Within ETL, data enrichment can be thought of as the ‘T’, creating a process that actually works to further transform data that’s already housed in your data stack. This could look like simply cleaning up data that is cluttered or duplicated, or linking specific pieces of data that are separated. Information like a first name, address, and even geographic location could all be part of data enrichment.


The more you are able to enrich your data, the better chances you have at creating a full 360-degree view of your customers and clients. 

2. What Kinds of Data Enrichment Are There?

As you can imagine, there are a lot of ways that data enrichment can help to purify and strengthen your source of truth that spreads out across your company. Getting a cleaner, more pronounced, and defined view of your customers can help give the various departments across your company the insight they need to improve the experience and drive the business forward. 


The three general types of data enrichment that exist are behavioral data enrichment, demographic data enrichment, and geographical data enrichment. Behavioral data enrichment concentrates on understanding the patterns and habits of your customers. This would record data that is relevant to key events that customers create. This could be information that regards their subscriptions, their shopping carts, support history, or how many times they frequent certain areas of your website.


Demographic data enrichment and geographic data enrichment simply refer to information about the customer such as age, gender, sex, etc., and then information geographically around the customer. Where do they live, work, and where do they interact with your brand? 

3. Where Can You Capture Data?

Data is created every time there is an interaction in the digital world. The main areas you can focus on capturing data enrichment are product data, sales data, marketing data, and finance data. These areas of interest help to build out a robust 360-degree view of your customer that can enrich your Wearhouse and strengthen your source of truth across a company. 

4. How Can Reverse ETL Help?

Lastly, reverse ETL is a powerful tool you can use inside your data stack to enrich data in meaningful ways. The concept behind reverse ETL is simple, in that it follows the same type of process of ETL to get information into your warehouse, except now it is pushing data back out to systems of record. This helps to make data in the warehouse accessible, and constantly enriches the data as it is moved through reverse ETL. 


Data enrichment is a powerful and necessary step to creating a profile of a customer that can be used by various departments to push your company forward. With tools like reverse ETL, this process can be integrated seamlessly into your data stack.