What is Data Enrichment? Everything You Need to Know

Data enrichment is a crucial part of the larger data hygiene process, which involves continually ensuring that data is accurate, reliable, and up-to-date, inevitably leading to clearer consumer insights.

Enrichment specifically focuses on adding new and supplemental information to existing datasets. Teams then verify this information against third-party sources to enhance its overall value. In this article, you’ll learn the basics of data enrichment, explore its key benefits, and delve into best practices and enrichment tools that can help you maximize your data’s potential.

Data enrichment (also known as data appending) ensures your data accurately and thoroughly represents your audience. As salespeople, we can all agree on the importance of accurate data. This information enables us to better understand our customers’ wants and needs, improve the customer experience, and personalize our sales efforts to engage leads effectively.

The Benefits of Data Enrichment

Data enrichment can significantly enhance the customer experience. Here’s some notable research highlighting the importance of personalized customer interactions:

  • 66% of customers want brands to understand their unique needs and expectations.
  • 52% of customers expect all offers from a brand to be personalized.
  • 54% of customers are likely to browse items in-store and purchase them online (or vice-versa), while 53% of brands are investing in omnichannel strategies to accommodate this behavior.

Accurate, enriched data is essential for creating targeted, personalized customer experiences. Without it, customers may be driven away. Additionally, data enrichment can help reduce overall costs. Here’s how:

With a robust data enrichment strategy, your focus shifts to maintaining data that is crucial to your company, such as customer contact information or transaction histories. Less relevant data can be deleted or moved to lower-cost long-term storage sites. Enrichment also enables the detection and elimination of redundant data, further reducing overall expenses.

Data Cleansing vs. Data Enrichment

While data enrichment primarily involves adding supplemental data to strengthen your CRM, data cleansing focuses on removing inaccurate, irrelevant, or outdated information. Both are crucial for maintaining a healthy, vibrant database, but data cleansing typically occurs first to make room for the updated, supplemental information provided through data enrichment.

This applies to your CRM data, which includes demographic, geographic, and psychographic information. The goal of your CRM is not to collect as much information as possible but to gather the highest-quality data that best represents your leads and customers.

When should you invest in data cleansing? For instance, if your email list is growing but your engagement rate is dropping, it’s time to clean up your data. The same principle applies to other information you use to connect with your leads and customers.

Keep a close eye on your engagement rates (opens, click-throughs, etc.) versus your total subscribers. These metrics will indicate the health of your database. Besides monitoring data performance, data cleansing should be performed at least every six months. Over 50% of organizations spend more time cleaning data than using it. Given the value of accurate data and the cost of using inaccurate or outdated information, this isn’t too surprising.

Data Enrichment Best Practices

While each company’s enrichment process will vary based on the data they collect and their strategic business objectives, there are common best practices applicable to all brands.

Establish Clear Criteria

Begin by creating clear criteria. Define goals for your data enrichment efforts and establish criteria to measure these goals. For instance, if the aim is to enhance the completeness and accuracy of customer data, set a target of achieving 90% or higher data accuracy in customer profiles when compared against a third-party verification source. Failure to meet targets indicates the need for further work.

Develop Repeatable Processes

Next, focus on developing repeatable processes. Continuously designing and implementing new processes is inefficient. Instead, create consistent and reliable frameworks for data analysis that can be applied across multiple enrichment efforts. For example, design a process for verifying customer profile data using standard third-party sources. Automate this process to streamline verification tasks and ensure reliability.

Ensure Scalability

Ensure that enrichment efforts can scale alongside growing data volumes. Implement automation wherever possible to eliminate manual tasks that may introduce complexity or errors as data volumes increase.

Prioritize General Applications

Consider how processes can be applied to other datasets. For instance, if you develop a process to verify customer data submitted via desktop website forms, ensure it can also be applied to mobile users by leveraging partners or services capable of accommodating different data sources.

Data Enrichment is Ongoing

Remember that data enrichment is an ongoing process. Continuously invest effort to ensure that collected data remains relevant, accurate, and timely. Data is constantly flowing into and out of your organization, and the data environment is always changing. To extract maximum value from data sources, continual enrichment is essential.

Data Enrichment Tools

When it comes to data enrichment, utilizing the right tools can streamline the process and enhance the accuracy and reliability of your lead and customer data. Here are some top tools and services to consider:

HubSpot CRM

The HubSpot CRM provides comprehensive contact management tools, including custom properties, tasks and activities, and web forms for data collection. It offers sales-specific features such as live chat, email scheduling, tracking, and a centralized dashboard.

Customer Data Platform (CDP)

A CDP aggregates and organizes customer data from various sources across your organization, creating centralized customer profiles. CDPs ensure data consistency and accuracy, enhancing customer insights.

Data Enrichment Services

Consider leveraging third-party data enrichment services to enhance your data quality further. Some options include:


A B2B business database and sales intelligence software that allows users to filter through millions of companies and identify ideal prospects. It integrates with multiple platforms, including HubSpot.


Offers updated company and contact information for sales records, with access to over 200 million contacts. It specializes in B2B lead enrichment, qualification, and scoring.

Reverse Contact

A Reverse Email Lookup tool that provides real-time information about individuals and their companies using email addresses. It prioritizes fetching publicly available real-time data compliant with CCPA & GDPR regulations.


Unifies multiple data sources with contact databases and CRM systems to enrich data, ensuring it stays up-to-date. It utilizes AI to gather data and target leads from online user behavior.


Enables users to capture data while browsing social media to connect with potential prospects. It integrates with various CRMs and provides data on millions of companies worldwide.


Allows verification of B2B lead information to ensure accuracy and engagement. It provides personalized datasets to help teams make better connections with potential customers.


Offers an interactive data engineering cloud platform to prepare and manage data for analytics and machine learning. It allows sales teams to monitor the quality and sources of data enrichment workflows.

With the right tools and services, businesses can effectively enrich their data, ensuring high-quality information for successful sales outreach and customer engagement.

Delivering on Data Potential

By implementing data enrichment best practices alongside appropriate tools and services, businesses can enhance the accuracy and reliability of lead and customer data. The outcome? Heightened value that enables teams to realize the full potential of their data.