What Is Data Enrichment?

DEFINITION
Data enrichment is a process that allows companies to gather raw data about customers and leads by matching the data in their database with third-party data. This results in updated and enriched data, giving relevant information about contacts.

đź’ˇUnderstanding Data Enrichment

At its core, data enrichment is a methodology that involves integrating customers’ raw data from internal sources with third-party data from external sources.

Companies go through this procedure to get deeper insights, improve their contacts’ data quality, and make informed decisions based on that enriched data. 

Data enrichment works across multiple teams for different goals. For instance, your marketing department can create resources and touchpoints explicitly designed to attract users based on enriched information.

However, data enrichment can also be effective with lead scoring, as accurate lead scoring relies heavily on quality, enriched, and relevant-to-you data. 

I.e., you can enrich demographic data. In this case, the data received is about your existing customer or lead base, like their age, income levels, education, job title, or marital status. After this exercise, you’ll have more information about existing leads, which is direct and actionable, allowing you to improve your marketing, sales, and messaging.

đź–‹ Takeaway

Data enrichment can help identify niche areas of great value overall and can be useful for lead scoring across your revenue-generating departments.

Several things can be learned through data enrichment that can help rank leads. This information includes demographic information about the age or education of individuals, the size of a business, industry, income level, geographical information, or purchase history.


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What Is Data Enrichment?

Data enrichment merges your data from internal sources like Google Analytics or customer surveys with third-party data from external sources. 

Data enrichment is not purchasing data. Instead, it takes the form of acquiring new demographic data about the existing customer data or lead base; this allows for a more personalized marketing experience.

Why Is Data Enrichment Important?

It is challenging to identify solid leads without adequate, up-to-date information. A name and email alone won’t be enough; thus, relying on third-party data sources to enrich the original dataset makes it a more valuable asset and more actionable.

The key benefits of data enrichment are:

  • Improved data quality & data accuracy. Believe it or not, data decays fairly quickly (research from Hubspot found that email addresses decay at around 22.5% annually, phone numbers at 17%) so it’s crucial to have data that is reliable and up to date.
  • Optimized email marketing efforts. Including: controlling your marketing costs by removing inaccurate or false contacts, preventing email blacklisting due to high bounce rates, and complying with GDPR, CASL, and CAN-SPAM.

How Does Data Enrichment Work?

Data enrichment involves combining third-source data with unrelated raw data from external sources. Enriched data is a valuable asset to any organization and makes the data you have more useful.

Data enrichment services own specific types of data, whether they bought it or extracted it from external or third-party data enrichment tools. They use this data to fill in the blanks.

How Do You Enrich Customer Data?

Enrichment is done through a process starting with identifying the problem and why you’re looking to enrich the data. It then combines the sources of data that exist with internal data (aka data coming from internal sources like rewards systems) and brings in 3rd party data. 

Third-party data like online behavior, social media activity, and email tracking are useful marketing measures themselves but are even more valuable when they are added to other customer information. 

Websites that use cookies to track user behavior usually contain features to connect data to user records. Even simple messaging platforms have the option of displaying which opens a message or clicks on a link.

When employed for lead scoring, you can use data enrichments to add demographic, background, interests, and purchase history information for leads, enriching the primary data that already exists with new and up-to-date data.

What Is Data Cleansing And Enrichment?

Data cleansing (often referred to as data cleaning) identifies if your contact data is still accurate and current, while, as we have seen, data enrichment adds additional information to existing contacts in order to get more complete data.

The process of B2B data cleansing may include: validation and standardization of data, cleaning up duplicates, filling missing data and erasing incomplete ones, and detecting conflicts in your database.

An example of B2B data enrichment may include personalizing the marketing experience of a user based on the information already collected on their company.

What Are Data Enrichment Tools?

Data enrichment tools draw data from various sources, including third-party sources. A data enrichment tool merges that raw data into a single stream. This provides a direct and detailed analysis, data that would not have been obtained from primary sources alone.

These tools often merge preliminary data collected directly from the contacts themselves or analytics platforms with third-party data from other platforms. Here they have accurate data that help manage customers and relationships. These tools are handy for processing massive amounts of data and getting the specific business insights needed to plan a marketing campaign or grow a business. 

Some popular tools include Clearbit, insideview, and Zoominfo. A more thorough list of our reviews on data tools can be found here

Getting Started With Data Enrichment

At Breadcrumbs, we take data (and data quality) very seriously. This is why we created our free email verification tool and, work with data enrichment services to give you always relevant and updated data about your leads and customers.

Your sales team won’t have to spend time crunching numbers or sorting through data; they’ll instantly know which leads to target, so they can focus all of their time and energy on that. 

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