Data enrichment is part of the larger data hygiene process, which is the continual practice of ensuring that data is accurate, reliable, and up-to-date.

Enrichment focuses specifically on the addition of new and supplemental information to existing datasets. Teams then verify this information against third-party sources to increase overall value. Then, we’ll dive into best practices and data enrichment tools that can help you deliver on data potential.

Data enrichment involves enhancing the precision and dependability of your original customer data. Teams achieve this by incorporating new and supplementary information while validating it against third-party sources.

Data enrichment, also known as data appending, guarantees that your data comprehensively and accurately reflects your audience.

As sales professionals, we unanimously recognize the importance of precise data. This data empowers us to gain deeper insights into our customers’ preferences, enhance their experience, and tailor our sales strategies to cater to their specific needs effectively.

The Benefits of Data Enrichment

Data enrichment holds the potential to significantly enhance the customer experience. Notable research underscores the importance of personalized customer interactions:

• 66% of customers desire brands to comprehend their individual needs and expectations.
• 52% prefer all brand offers to be personalized.
• 54% of customers engage in both in-store and online purchases, prompting 53% of brands to invest in omnichannel strategies.
  
  

Accurate, enriched data serves as the cornerstone for crafting targeted, personalized customer experiences. Conversely, the absence of such data can deter customers.

Moreover, data enrichment contributes to cost reduction. Here’s how: By implementing a robust data enrichment strategy, focus shifts to maintaining pertinent data like customer contact details or transaction histories.

Less relevant data can be either eliminated or transferred to more cost-effective long-term storage platforms. Furthermore, enrichment aids in identifying and eliminating redundant data, thus curtailing overall expenditure.

Data Cleansing vs. Data Enrichment

While data enrichment primarily involves supplementing your CRM with additional data to enhance its strength, data cleansing focuses on eliminating inaccurate, irrelevant, or outdated data.

Both are integral for maintaining a robust, dynamic database, but data cleansing typically precedes data enrichment to make space for the updated, supplementary information.

This principle applies to various aspects of your CRM data, including demographic, geographic, and psychographic information. The objective of your CRM isn’t to accumulate as much data as possible; rather, it’s to gather the highest-quality data that accurately represents your leads and customers.

When should you prioritize data cleansing? For instance, if your email list is expanding but your engagement rate is declining, it signals the need to clean up your data. The same applies to other information used for engaging with leads and customers.

Monitoring your engagement rates (such as opens and click-throughs) versus your total subscribers offers insight into the health of your database.

Beyond assessing data performance, data cleansing should occur at least every six months. It’s worth noting that over 50% of organizations dedicate more time to cleaning data than utilizing it. Given the importance of accurate data (and the consequences of using outdated or erroneous data), this statistic isn’t surprising.

Data Enrichment Best Practices

Although the enrichment process may vary across companies based on the data they collect and their strategic objectives, several common best practices can benefit brands regardless of their approach.

Create clear criteria.

The initial step is to establish clear criteria. This involves aligning your data enrichment goals with specific metrics that allow you to assess progress.

For instance, if the objective is to enhance the completeness and accuracy of customer data, you could set a target of achieving 90% or higher accuracy in customer profiles when verified against a third-party source.

Failure to meet these targets indicates the need for further refinement.

Make processes repeatable.

The subsequent step involves establishing repeatable processes.

Recreating and implementing new procedures repeatedly can be inefficient and costly. By devising consistent and dependable frameworks for data analysis, you can apply them to multiple enrichment endeavors.

For instance, consider the process of validating customer profile data through standardized third-party sources. By establishing a procedure that automatically verifies data types across these platforms, you can effortlessly reapply the function as needed.

Ensure efforts can scale.

As your data volumes expand, it’s essential to deploy enrichment strategies that can scale accordingly. This involves prioritizing automation to minimize manual interventions, which could otherwise introduce complexities or unforeseen errors.

Prioritize general applications.

Lastly, consider prioritizing processes that have broader applications across various datasets.

For instance, if you establish a procedure to validate customer data obtained from desktop website forms, it’s advantageous to seek partners or services capable of extending this process to mobile users as well.

Data enrichment is an ongoing process.

Data enrichment isn’t a one-time task; rather, it necessitates ongoing attention to guarantee that collected data remains pertinent, accurate, and timely.

This approach aligns with the dynamic nature of data flow within and outside your organization. Continuous enrichment ensures that you extract maximum value from your data sources, adapting to evolving data environments effectively.

Data Enrichment Services

After understanding data enrichment and data cleansing and identifying the appropriate times to engage in these activities, it’s crucial to delve into the implementation process. However, the prospect of manually sifting through hundreds or thousands of data points can be daunting, particularly for larger databases.

To alleviate this challenge, we’ve curated a useful compilation of data enrichment tools designed to facilitate the cleaning and management of your data. Explore the options below.

Vainu

Vainu serves as a B2B business database and sales intelligence software. With Vainu, users gain access to a vast database of millions of companies, enabling them to pinpoint prospects that align with their ideal customer profiles.

The platform facilitates easy data access and seamlessly integrates with various platforms, including HubSpot, Salesforce, Pipedrive, and over 1000 other tools.

Clearbit

Clearbit specializes in providing updated company and contact information for sales records. It focuses on B2B lead enrichment, qualification, and scoring, offering access to a database of over 200 million contacts.

Clearbit ensures data accuracy by continuously updating and enriching contact information automatically.

Reverse Contact

Reverse Contact offers a Reverse Email Lookup tool, allowing users to instantly retrieve real-time information about individuals and their companies using their email addresses. It’s ideal for enhancing, qualifying, and scoring B2B inbound leads. Unlike systems reliant on pre-existing databases, Reverse Contact prioritizes fetching real-time data that complies with CCPA and GDPR regulations.

LeadSpace

LeadSpace unifies multiple data sources with contact databases and customer relationship management systems to enrich data and ensure its up-to-date. Leveraging artificial intelligence (AI), LeadSpace gathers data and targets leads based on online user behavior, enabling more accurate lead targeting and customer preference tracking.

Datanyze

Datanyze facilitates quick identification and connection with potential customers. It enables data capture while browsing social media to engage with prospects and allows tagging of contacts and companies to create segmented lists. Datanyze integrates with various CRMs and provides data on millions of companies worldwide.

LeadGenius

LeadGenius offers B2B lead information verification to ensure teams reach out to accurate, engaged prospects. It provides personalized datasets to help teams make better connections with potential customers.

Trifacta

Trifacta provides an open and interactive data engineering cloud platform, enabling the preparation and management of data for analytics and machine learning. It allows sales teams to monitor the quality and sources of their data enrichment workflow.

Maintaining high-quality, accurate data through data enrichment is essential for keeping prospects and customers interested and engaged in sales outreach efforts.

Delivering on Data Potential

By implementing data enrichment best practices alongside appropriate tools and services, you can enhance the accuracy and reliability of lead and customer data. The outcome? Heightened value that empowers teams to fully capitalize on their data potential.