A Comprehensive Guide: Data Enrichment

Enriching existing first-party data with third-party datasets is called data enrichment. For example, your customer web journey records are available altogether. When you clean, structure and append valuable & complementary details from an external resource to the existing database, it’s a data enrichment journey. This process integrates more value into existing records so that you can have deeper insights.

Why is Data Enrichment Important?

The data enrichment services & process is vital because of the following reasons.

  • It enables you to have answers to all related and subsidiary customers’ queries.
  • You win an opportunity to easily draw in-depth insights. They let you make decisions that are beyond any limit.
  • With a deeper understanding of what your clean and rich database conveys, you can define an enhanced customer experience. This practice helps your business to foresee customers’ requirements. Later on, you may come up with refined resources to heal their pain points. This is how this data transformation method lets you deliver an enhanced experience. 

Various Types of Data Enrichment

However, it completely depends on the type of data. Mainly, there are three types of data enrichment that are popular.

Let’s get started to learn what these types are.

  • Behavioral Data

This is the most complex area. It requires the thorough observation of behavioral patterns by using users’ profiles. Discover their likelihood, interest, or whatever that leads to a purchase decision. Many eCommerce and business enterprises prefer to enrich behavioral records to effectively tap ideas. These ideas are inspired by the history of purchase decisions, pain points, etc. With this understanding, the marketers design ad campaigns for increasing conversion rates at a low cost.

  • Demographics

Demographics refer to the target audience or specific demographic groups. It is actually related to a particular population and its purchase decisions. Unlike behavioral data, it is meant to derive insights into a group of people. On that basis, business intelligence can be developed. It is actually helpful in creating ads and messages that customers relate to. Also known as demographic data enrichment, this practice guides you to customise messages as per customer intentions and sizes.

Data Enrichment Practices
Data Enrichment Practices
  • Geographical Data

Geographical data is concerned with location-based records. This knowledge can hook outstanding results via geo-location-based customer data. This record ensures the end-user would be from the target location, country, time, and city. It may require your support to look up IP addresses and scrape location-based data. Thereafter, you can engage them through personalised content wherever they revisit.

Benefits of Enriched Data

There are multiple advantages that leveraging enriched records can bring, especially in data mining & cleansing. Take a roundup of them below:

  • Save Money

This process involves integrating only useful details from external resources that your database lacks. You can draw value from the enriched records, which eventually attracts monetary benefits. Besides, you can save money on the web or data extraction, which can be pricey.  

  • Build & Enhance Customer Experience

This process provides an opportunity to personalise promotional messages and communications. You can filter their preferences, pain points, and requirements. Then, personalise campaigns. It gives out the message that you understand them. This happening betters the chances of building great relationships with customers.

  • Maximize Conversion Rate

With this process, you can easily segment customers with the potential for conversion. Explore their historical event to figure out situations when they made a decision to buy. Accordingly, offer discounts and complementary products or services. It can translate them into your consumers.

  • Successful Target Marketing

It’s obvious that one-size-fits-all marketing campaigns can hardly impress customers. With this type of rich data, you can easily achieve target marketing goals. You may segment the target audience on the basis of their behavior, location, or demographics. Segmentation makes it easy to attract more sales. 

  • More Upselling & Cross-selling

Enriched data is a set of complete information. You can have complete & fresh details of your target audience, which lets you build and run personalised campaigns. The success rate of these ads would certainly be high, which results in high upselling and cross-selling.

  • Benchmark Quality

This enrichment benefits through valuable details. It means that there is no scope and place for redundancies, which often ends up in loss. Besides, you can easily integrate data enrichment tools and techniques to automate this process. This is how you eliminate the overburden of managing useless details. The scope of verifying and validating data entries would be more and better.

Process of Data Enrichment

There are mainly three steps to follow during the enriching process. Let’s get through it.

Step 1. Set up Data Enrichment Goals

  • Preset what you are going to achieve through this data enrichment process. It should be concerned with accuracy and quality.
  • Start with deciding the key performance indicators (KPIs). Collect information accordingly.
  • Ensure that your data collection has relevant and fresh datasets. For this purpose, define the motive, insights, and value to be drawn to your team.
  • Apply logic to make it smoothly run. Decide if it is to be undertaken in real-time or in the warehouse. Brainstorming about what to sell in a specific season, conditions, or series of events can help in making wise decisions. 

Step 2. Prepare Information to Integrate with Tools

It is pivotal to think about what tools to choose for this process. Understanding goals can help with making this decision accurately.

  • Think about the utility that you require. It should be concerned with accurate collection, organisation, and cleansing steps of data in a specific format.
  • Look up them in the preferred tools, which can be Leadspace, Beam Enrich, LeadGenius, Clearbit, etc.
  • Compare utility and accuracy to have high-quality data.

Step 3: Frequently Update at the Point of Entry

Enrichment of data is an ongoing process, which is necessary to make accurate decisions and derive values from the collected information. Ensure that you have fresh and up-to-date datasets to keep up their value. To achieve breakthroughs, ensure

  • You have a provision to update data at the point of entry. Migration may infuse errors, typos, & oddities in your database. This practice helps to combat this challenge. 
  • Deploy automated systems or tools to directly enrich data.
  • Schedule the cleansing process in your database.