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Just as quickly as businesses collect data, data can change. Data enrichment is a practice that helps to keep your data up-to-date. It’s an important data step because raw data must be accurate to be of use.

Let’s take a look at how data enrichment works, how you can keep the process working, and the various ways that automation tools can aid in transforming your data into valuable insights.

Coming Up

1. What is Data Enrichment?

2. What are the Types of Data Enrichment?

3. How to Keep Data Enrichment Process Working?

4. What are the Benefits of Data Enrichment?

5. What is Data Cleansing?

6. What is the Difference Between Data Cleansing and Data Enrichment?

7. How do Data Enrichments Tools Work?

8. Examples of Data Enrichment

9. Wrap Up

What is Data Enrichment?

Data enrichment is a process that combines data from various sources to enhance, refine, and update raw data. It may mean that your business collects raw data from customers or website visitors and stores such data in a centralised database. Data enrichment will combine information from third party data (external sources) or even pull internal data from various systems to complete the raw data’s fields.

Additionally, data enrichment works to incorporate updates into existing data so that it reflects reality in real-time. For example, if a company is acquired, then the company name will need to be updated in your database. Data enrichment takes care of something like this.

What are the Types of Data Enrichment?

Data enrichment exists across different categories of information. The two most common types of data enrichment are demographic data enrichment and geographic data enrichment.

Here’s what they are:

  • Demographic data enrichment: Demographic data is broad. It can span information like how many kids your customer has, income level, marital status, the type of car they drive, and more. It works to create a full picture of a customer and can be very valuable in marketing efforts.
    For example, if your business offers credit cards to people, then it’s useful to attain creditworthiness to develop offers. Personalised marketing is highly dependent on this type of demographic data enrichment.
  • Geographic data enrichment: As the name implies, geographic data enrichment is all about location. It could be adding postal codes, latitude or longitude data, for example. This kind of data is more readily available. In fact, retailers are keen to attain this data because it can play a large role in big decisions.
    To illustrate, if a retailer wants to offer localised pricing, they’d be more willing to lower prices in areas with high demand/reach. Additionally, geographic data enrichment can help save on marketing costs on items like printed mailers purchased in bulk.

How to Keep Data Enrichment Process Working?

When approaching data, one of the primary facts to keep in mind is that it’s going to change– constantly. Having data that’s stuck in a certain point of time renders itself useless because it no longer can perform the function you intend.

As such, data enrichment is a process that must be ongoing and constantly executed. Think about just one customer. Their address may change, their marital status could go from married to divorced, their income level may rise or call, they’ll adjust purchasing decisions over time, etc.

Now, think about how you use your data to communicate with said customer. If you send them information that’s meant for a segment that they used to be part of, it will prove ineffective and be costly to your bottom line.

Your business’ efforts need to remain in line with your customer’s needs. With demographic and geographic data shifting, data enrichment provides a sense of security over your data’s accuracy. Most businesses will spend more time cleaning their data than actually using it. This also ends up being a complete waste of valuable resources.

Think about your staff. Rather than having them manually search to fill in data fields and update spreadsheets, they could spend that time providing creative business solutions and better serving customers.

But, you can’t let your data go stale. To solve for this, businesses implement automation software into their toolstack. Automation software can take care of many processes within your business, including data enrichment, data cleaning, and data management. This way, data is securely stored and ready to use to help you achieve your business goals.

What are the Benefits of Data Enrichment?

Having accurate and complete data is of utmost concern for any business looking to optimise their operations and customer experience. Here’s a quick snapshot of the benefits of data enrichment:

  • Save money: Storing data comes at a cost. If you’re storing invaluable and inaccurate information, you’re basically throwing away money. With data enrichment, you can rest assured that your data is accurate and of use, so it’s worth the cost of storage.  
  • Build better relationships: Knowing your customers better means that you can communicate with them better. When you are able to meet and anticipate their needs, you can establish and build better relationships.
  • Enable targeted marketing: Traditional and mass marketing efforts are becoming a thing of the past. To remain successful, businesses are segmenting audiences based on data and creating tailored campaigns and product offerings to retain customers.
  • Boost sales: You don’t want to reach out to people who aren’t receiving your messages. That’s a waste of time and money. With data enrichment, you know that your contact list is fresh and up-to-date so you can increase sales by reaching people who are interested in your product.
  • Remove redundancies: Redundant data is a risk. It’s a risk to your bottom line and your reputation. With data enrichment, you can rid your database of duplicate records.

What is Data Cleansing?

Data cleansing is another important and necessary practice in data management. It’s a process that goes through your database to detect and remove any inaccurate records. It finds where raw data is missing (incomplete), wrong (inaccurate), or not useful (irrelevant).

Data cleansing also impacts a business’ bottom line. You want to make sure that data is in its best shape to be used by any department, from marketing to sales to compliance and finance. Automation can be leveraged for data cleansing as well. They can take care of data sourcing and inputting information so that human errors are avoided.

What is the Difference Between Data Cleansing and Data Enrichment?

Both data cleansing and data enrichment are processes to increase the accuracy and relevance of existing data. However, they are slightly nuanced in their approach. Data cleansing is about removing inaccurate records. Data enrichment is focused on amending and updating raw data.

Data cleansing helps to achieve data enrichment. Before performing data enrichment (or adding any fields to raw data), you’ll first want to make sure that it’s data you even want or need to keep in the first place. Data cleansing can also be something as simple as removing a typographical error (like an extra space or period in a field). Data enrichment would be the addition of new information or updated points.

How do Data Enrichments Tools Work?

Data enrichment tools are powered by automation. Robots work behind-the-scenes to pull data from various sources, compare existing records, update records accordingly, and safely secure the information for your business’ use.

The process of a data enrichment tool can be broken down into three steps, namely:

  1. The tool accesses and pulls data from countless external and internal sources in real-time.
  2. The tool is connected to your business’ database through an API or directly.
  3. The tool updates your existing data with any missing information it has captured. By running this process continuously, you can make sure that your data is always updated and relevant.

Data automation tools add a lot of value to any type of organisation. Beyond preparing and maintaining your data, you can utilise such tools to run processes so that your data gets used and reviewed in real-time.

Automation reduces compliance risk by eliminating the chance for human error and standardising organisational processes. By adding this level of transparency and visibility into your organisation, internal and external stakeholders have everything to gain.

Examples of Data Enrichment

There are many examples of use cases of data enrichment to consider.

Think about how you collect data from your prospective customers. It’s likely that your website has a form to complete for inbound visitors. It’s been shown that the longer the form field, the higher the rate of drop-off (people rarely have time or motivation to submit a lot of information without receiving anything in return).

As such, you can ask for the bare minimum (i.e. name and email address) and then leverage a data enrichment tool to fill in the rest of the blanks. This way, you can build your prospect list more efficiently while expecting less from those visiting your site.

Or, if you’re a bank or financial institution, your offerings aim to meet the financial needs of your diverse customer base. The more information you have about your customers, the better you can assist them to meet their financial goals.

You can provide personalised dashboards with savings goals and tailored insights of your customers’ spending which provides them with a lot of value and reason to stick with your business.

Wrap Up

Data enrichment software provides your business with better data. Businesses collect massive amounts of data each day from a variety of sources. Data enrichment provides your organisation with a way to pull accurate data and improve the quality of each record.

Automation tools complete these necessary steps while allowing your team to focus on high level tasks in the foreground.

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