Why Data Enrichment Is So Important for Your Organization

Data is growing at an unprecedented rate. And it’s predicted to grow even more, surpassing 180 zettabytes by the end of 2025. But it’s not just the size of the data that has expanded; its complexity has increased, too. More systems and more sources are capturing data, making it difficult for organizations to keep their data clean and consistent.

While data unification, cleaning, and de-deduplication of a company’s existing data are critical, data enrichment is another key activity behind improving data quality. As organizations progress on their MDM journey, many have discovered that to achieve the best version of their data, they need to look outside of their company walls and tap into reputable external sources such as Dun & Bradstreet, Moody’s, and ZoomInfo. 

To successfully improve data quality, organizations must rethink their approach to data cleansing by linking valuable, internal data with trustworthy external data provided by third parties, vendors, or public data sources. This is data enrichment. And it’s an effective way to improve the quality of golden records and provide decision makers with the clean, accurate, complete data they need to drive the business forward. 

To learn more about data enrichment and how it helps organizations enhance their data to better support their business objectives, download our new ebook, Guide to Data Enrichment: What It Is, Why It Matters, and How It Enhances the Power of Your Data. 

Defining Data Enrichment 

Data enrichment is part of the master data management process that involves enhancing existing internal datasets with information from additional, outside data sources. These sources, for example, could include data about companies or people, and could be used to support sales and marketing, risk management, and more.

Improving data quality requires organizations to validate and standardize their data to identify gaps and common attributes. With data enrichment, they can take this process even further. Using unique IDs, data enrichment tools connect internal data with a third-party source to identify additional or missing attributes to add to each record. Together, data quality and data enrichment build on each other to help organizations deliver greater value from their internal data. 

3 Common Ways to Enrich Data

Companies can enrich their data in many ways. Below are three of the most common approaches:

1. Firmographic data enrichment updates or adds basic—yet critical—data elements to company records including name, location, industry, company size, number of locations, years in business, and ownership type. Firmographic data helps B2B companies to better segment and target their customers.
2. Demographic data enrichment updates attributes of people, including consumers, patients, and students. Companies can correct or complete fields such as age, gender, income, education, marital status, and ethnicity. Then, they can use this enriched demographic data to tailor campaign messaging, target relevant audiences, or better understand customer behavior.
3. Geographic data enrichment enhances data related to addresses, postal codes, coordinates, and geographic boundaries. Geographic data enables companies to deliver location-based services, as well as provide mapping and navigation functionality.

Common Use Cases for Data Enrichment

Data enrichment delivers value to companies in a number of ways, including: 

• Customer analytics: Data enrichment enables companies to better understand customer behaviors so they can target the right prospects. For example, companies can identify ideal B2B prospects and their lookalikes for their products using firmographic data, employment growth, and technologies that companies use. With this information in hand, the company can then personalize offers, which, in turn, helps to boost conversion rates.
• Improved decision-making: When companies have additional context from external sources added to their existing internal data sets, their data is more accurate and complete. As a result, they can make faster, smarter, and more confident decisions. 
• Duplicate reduction: Data enrichment preserves data integrity by preventing bad or duplicative data from entering systems and corrupting records.
• Risk management: Data enrichment enables companies to spot operational, financial, and reputational risks by identifying their key partners and collaborators. For example, a company can avoid supply chain disruption by identifying parent companies and seeing if they are sanctioned or located in geographical areas that expose the organization to risks.
• Regulatory compliance: Enriching existing data with trustworthy external information enables organizations to better meet regulatory requirements, reduce the risk of errors, and avoid costly penalties. 

Tamr’s AI-native MDM solution delivers the seamless data enrichment tools companies need to tap into third-party data as a key part of their data mastering process. Tamr validates and standardizes common attributes, links internal records to a vast corpus of third-party firmographic data using verified match capabilities, and offers pre-built integrations with leading data providers—making it easy for companies to deliver the trustworthy golden records needed to support both analytical and operational use cases.

To discover how data enrichment can help your organization deliver high-quality, trustworthy data, download our latest ebook, Guide to Data Enrichment: What It Is, Why It Matters, and How It Enhances the Power of Your Data.