Data’s superpower emerges from its reusability. When your business releases a new product or service or wants to improve customer relationships, you can take the same data set, repurpose it, and enrich the data, generating new business insights.

This simple process, data enrichment, describes how to provide this better business understanding with good data quality. Enriching data works very well in new contexts, such as when your company or makes a change or your business environment evolves.

In this article, we will uncover the data enrichment definition and its role in data management. Let’s get started.

What Is Data Enrichment?

Data enrichment is defined as a type of data integration, filling in missing details to see a problem and its solution clearer. You do data enrichment by appending one or more data sets with other attributes and values from different data collections. 

While you do this activity, you standardize all the merged data to fit your data quality needs. That way, you get a refined, improved, and enhanced data grouping. For example, when you combine customer information obtained from sales calls with that online, you enrich data. 

Enriched data gives you more knowledge regarding your business and customers, thus offering you more ammunition to improve your brand’s presence.

Read on to discover the benefits of data enrichment below.

Benefits of Data Enrichment

#1 Lets You Collect Valuable Data

We have already covered the need and importance of data enrichment. You need it to make informed decisions. But data enrichment does not mean just adding more to your records. 

data enrichment Enriched data describes valuable data relevant to the problem and situation at hand and sharable among stakeholders, like customers, managers, and shareholders. When your company needs to find out more information, the enriched data guides you through generating good questions to ask your customer.

For example, many websites have chatbots built on artificial intelligence and machine learning technologies. Chatbots use enriched data to answer customer’s questions more efficiently and obtain feedback from their discussions with customers. 

#2 Improve the Accuracy of Data

Believe it or not, data decays every moment. Think about a simple contact list. About 30 percent of it will become useless, in almost a year, due to buyers or potential clients changing contact numbers.

Moreover, as you collect customer information from various formats, adding data from one group to another can be challenging. To truly enrich a data set, you need to make all the values you want to combine in a digestible format. 

Hence, it is important to keep your data clean and accurate; otherwise, your efforts will not produce good results. Let’s consider an emailing list. You prepare kickass emails and send them to the 1,000 people on your list, but 30 percent of the emails are not valid anymore because of data decay.

This data decay means only 700 people will receive your email. Furthermore, you may accidentally send an email twice to the same person because of double entries from the appended email. 

Good data enrichment procedures verify the information to ensure you have up-to-date data. Plus, they even correct typos and remove double entries to ensure you have reliable and correct data.

#3 Helps You Save Time

You would think that appending data would add more time as you already spend a lot of it logging maintaining data. The number “one challenge to CRM adoption is manual data entry.”

Contrarily, data enrichment reduces the time and effort one will need to do the job since it allows automation in smart ways. According to your requirements, data enrichment automation standardizes values, focusing on the most meaningful impact you can give to a target set of customers. 

You decide what kinds of data you to enrich and how to do so. Then a computer algorithm takes care of the rest by standardizing and enhancing your contact records in a short time. No manual manipulation of individual records required.


It’s understandable why someone may confuse data enrichment with data cleansing since they’re related to data hygiene.

Data cleansing involves detecting and removing inaccurate or corrupt data. On the other hand, data enrichment only refers to refining, improving, or enhancing third-party raw data to integrate with an existing data set.

A good data cleansing process involves cross-checking and validating already existing data, whereas data enrichment, by definition, focuses only on the data added. However, the line is getting thinner as many advanced tools offer a mix of both data enrichment and data cleansing services.

Data Enrichment Use Cases

Here’s how data enrichment is making business more manageable.

#1 More Useful Forms to Capture Leads

Every marketer wants to generate leads. An essential step in the process minimizes barriers to entry for visitors by shortening the process.

However, there is an opportunity cost because the more information marketers ask for, the longer it will take a visitor to fill the form. This information overload can cause users to turn away and not fill forms, seeing the questions as pointless, preventing marketers from accessing critical information.

Data enrichment tools improve the situation by helping both marketers and visitors stick to only relevant information. As a result, both avoid spending time on unhelpful details and get the data they need.

#2 Better Segmentation

No marketing campaign can be successful without proper customer segmentation, categorizing an audience to deliver more personalized goods and services. Data enrichment improves this task by providing valuable information regarding customers that businesses can use to segment them. Segmentation can give you an edge over your competitors by personally connecting with your customers and anticipating their needs.

data enrichment benefits

#3 Improved Lead Scoring

Your overall success rate depends mainly on how you score leads and how many of them convert. The job is to develop a healthy relationship between marketing and sales teams since they need to work together to find new buyers and keep them loyal.

However, manual processes can be troublesome and very tedious. For example, if all you know about a buyer is a full name and personal email, then your lead generation tool will assign a very low score to the user based on the available information.

But if you have a data enrichment tool, you will be able to link the information you have to more data, including a professional email. For example, you get to know where they live and the holidays they celebrate nationally. 

That type of personalized contact will help you improve your score getting leads, and increase your chances of finding success.

#4 Personalized Services

Customers want customized and personalized services. It makes them feel special. Back in the day, most emails started with a typical salutation like Dear Buyer or Hello Client. However, today’s customers expect to be directed by their name. 


An automated data enrichment tool refines data and removes errors to your specifications quicker.

As a result, you get data that are more useful and reliable to your customer relationships.

Such tools come in handy to deal with large volumes of data and get the specific business insights you need to plan a marketing campaign or expand your business. Should your business needs change over time, you can reuse your existing data set and add new details, to meet that context.

There are many data enrichment tools, but if you’re looking for one that’s affordable, reliable, and easy to use, then consider the many products from WinPure.

All our products come with a free trial and are easy to use. Whether you’re running a small agency or a big, multinational corporation, you can customize our tools for your enrichment


Written by Michelle Knight

Michelle Knight has a background in software testing, a Master's in Library and Information Science from Simmons College, and an Association for Information Science and Technology (ASIST) award. At WinPure, she works as our Product Marketing Specialist and has a knack for explaining complicated data management topics to business people.

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