< BACK TO BLOG

What Is Data Enrichment: A Short Guide

Published on: 2022-04-16

If you’re looking for a more insightful way to look at customer data and sharpen your decision-making, a data enrichment solution might be the last stop on your quest.

Thousands of companies worldwide are scouring internal and external data sources, searching for a reliable way to improve customer experience and consumer targeting. If you’re one of them, a data enrichment process will allow you to enhance the accuracy of your data analytics, handle third-party data with unparalleled robustness, and put a better funnel on your data acquisition techniques. Data enrichment helps market research teams and executives process only meaningful data, discarding factors that might skew decision-making with the help of machine learning.

In this explainer, our data enrichment experts from Ful.io will outline what makes data enrichment essential for businesses that want to remain competitive and why paying for data enrichment services is always worth it for CIOs and CTOs.

We’ll start by defining what data enrichment processes are for people with no marketing or data gathering experience.

What Is Data Enrichment?

The internet grows by over 24,000 gigabytes per second, and inside that vast ocean of raw data lies consumer geographic information, postal data, customer reviews, sentiments, and more.

Through automated data collection, business users harvest customer data to determine the viability of future products, investment decisions, and even the screening dates of the movies you watch in theaters. For business owners and market research firms, data is the most valuable asset they can find, and high-quality data is essentially as valuable as gold.

Data enrichment processes enhance data accuracy by combining information from two or more sources into a unified codex.

For example, if you own a lending company and have been in business for a long time, you could combine existing data sources from previous customers with new ones to increase your profit margin. Credit scores and sources of income form your raw data repository. If you add social media profiles, purchasing behaviors, and employment histories to your existing database, you can create enriched data that paints a more accurate and holistic picture of creditworthiness.

Today, data enrichment is the leading data management methodology that leads to higher data quality, broader research coverage, and better processing efficiency of raw data for commercial data consumers.

Why Is Data Enrichment Important?

Every data effort that can enhance the quality and value of an internal data repository of a business is invaluable in today’s hypercompetitive environment. Consumers are unpredictable, and relying on a single data source is seldom enough. Business owners need an objective view of their markets, so they enrich data with as many relevant sources as possible.

If you don’t use a data enrichment tool, your insights and decisions will yield unreliable results. You might formulate many invalid conclusions and have no idea where you went wrong until you’re several business processes deep. It might be impossible to recover by the time your errors present themselves.

The most profitable companies owe a large part of their success to data enrichment, meaning if you miss out, your competitors will always have a leg up on you. Knowing your customers is essential for growth, and data enrichment tools allow you to do it fast and cost-effectively.

The Two Types of Data Enrichment

If you’ve been searching for the best complete data enrichment service for your business, you might already be familiar with the technical terms “demographic data enrichment” and “geographic data enrichment.”

Enriching data is unique for every industry. It’s a methodology that’s only a few years old, and people are combining new data sets, creating new techniques, and selling them to the market every month.

However, you can find two primary data-enriching methods that nearly all business owners use.

Demographic Data Enrichment

This method allows business owners to look at their customers as statistical sets to determine their future purchasing patterns and behaviors. It quantifies their lifestyles into data sets that statisticians can profile and understand. Demographic data refers to marital status, educational attainment, income bracket, employment type, etc.

Banks look at their clients through credit scores, outstanding debts, and repayment histories. They use this information to decide whether they should grant them a credit card or a reverse mortgage.

Geographic Data Enrichment

This kind of data enrichment marries incomplete data from a data warehouse with a geographic location to help you accurately predict which products will sell well in various countries and states.

Geographical information includes latitude and longitude, ZIP codes, office and home addresses, and ZIP codes. Businesses that leverage this method can localize discounts and provide a more personalized service to consumers. It allows them to create promotional programs with higher turnouts and products that become staples in a locale.

Data Enrichment vs. Data Cleansing

It’s a newbie mistake for market researchers to confuse these two processes as both of them can make data more accurate and consumable.

● Data enrichment adds data to your database for improved accuracy and coverage.

● Data cleansing verifies whether the information in your repository is still valid and removes out-of-date data for more efficient research.

Learn More about Data and SaaS with Ful.io

So, what is data enrichment? Discover how improved data security, more efficient data enrichment, and data appending can help you create better business decisions by contacting our experts at Ful.io. Become a subscriber today and track over 2,500 content technologies in real-time.


Made with in India