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Thought Leadership & Enablement
January 22, 2024

Data Enrichment: Your 5-Step How-To Guide

Discover how data enrichment can lead to better marketing, how it differs from data cleansing, and the steps and tools you can use to enrich your data.

Brittany Gulla
Director of Growth Marketing

You know what’s even better than data? Enriched data.

With enriched data, there’s a lot that you can do — create better customer profiles, refine your marketing strategies, boost conversions, create more personalized customer experiences, and more. You just need a thorough data enrichment process that helps you collect, sort, and use information as you get it.

So what exactly is data enrichment? Read below, where we’ll show you what it is and how you can use it to your advantage.

What Is Data Enrichment?

As a marketer, you’re well-aware that everything that you do is backed by data in some way. You’ve collected data to build buyer personas so that you can create marketing materials that speak to those buyers — and then you’ve sent those materials out into the world via social media or other marketing channels where you’ll collect more data so that you can analyze the performance of your marketing campaigns.

It’s no surprise, then, that the better your data is, the more successful your marketing efforts will be. And that’s what data enrichment is all about. It’s the process of improving and refining your customer data. The idea is to make it as accurate and reliable as possible so that the data provides a great representation of your audience.

The data enrichment process involves — surprise! — collecting yet more data so that you can add new insights from fresh analytics or supplemental information and so that you can verify your data against third-party sources to ensure accuracy.

What Is the Use of Data Enrichment?

Desktop view of a dashboard and mobile views of the ASICS online store

There are many uses for data enrichment — and we’ve already highlighted the primary one, which is to improve your overall marketing performance. 

But that’s a broad term that encompasses a lot of things. Here are some of the specific ways that you can use data enrichment to improve your marketing efforts:

  • Use enriched data to gain deeper insights into customer needs and expectations so that you can provide a better customer experience
  • Refine data to create more accurate customer segmentation models
  • Use data enrichment to learn how you can create more personalized, authentic marketing messages for your customer segments
  • Rely on data enrichment to help you discover which marketing and sales channels are most effective for promoting and selling your product
  • Save money on marketing and sales by using data enrichment to not only increase marketing campaign accuracy but also to identify the most efficient marketing and sales strategies
  • Enhance lead generation and lead nurturing efforts with refined data

What Is the Difference Between Data Transformation and Data Enrichment?

As you learn more about data enrichment, you’ll run into some similar terms that might prove confusing — namely, data transformation, which is also sometimes called “data cleansing.” What’s the difference? Let’s break it down.

Data Transformation and Data Cleansing

As a marketer, you doubtlessly collect vast volumes of data so that you can improve your marketing campaigns. But is all of that data accurate? Is some of it even relevant to what you’re trying to accomplish?

That’s what data transformation — or data cleansing — is all about. It’s the process of improving the usefulness and accuracy of your existing data so that you can use it to produce better and better results.

Data Enrichment

If data transformation is a subtractive process — pruning out inaccuracies or datasets that aren’t relevant to your objectives — you can think of data enrichment as an additive process. When you enrich data, you broaden and deepen your existing data with new, supplemental information. 

Think about it this way: Let’s say that your data says that one of your biggest target audiences is college students. Enriching that data would mean digging deeper. Are these students more likely to be business majors or STEM majors? Which colleges do they go to? Are they pursuing a master’s degree or more likely to finish with a bachelor’s degree? 

Enrichment is the process of learning additional, useful information that can help you achieve your marketing goals.

What Are the Steps in Data Enrichment?

Pepsi products on a laptop screen

Now that we have a grasp on the uses and benefits of data enrichment as well as how it differs from data transformation, let’s look at the steps you can take to improve your data quality. Keep in mind that these are just the basics. Every business has unique needs and data sets, so you may have to make adjustments to the steps below to create your own enrichment process that is better suited to your workflows.

1. Define Your Goals for Data Enrichment

Since there is virtually no end to the types and quantities of data to collect, this is the best first step. What do you want the data enrichment process to achieve?

Answer that question to define clear goals — and then use those goals to guide the rest of the process. For example, if your goal is to create more complete customer records or profiles, then you’ll likely focus on demographic data enrichment. 

But if you want to improve marketing performance on a particular social media platform, you’ll enrich your data with data points that are relevant to the platform and the consumers you are targeting there.

2. Identify the Gaps in Your Data

You could go out and collect every type of data that could be even remotely related to the goals you’ve established. But that is sure to become a messy, time-consuming process. And you’ll probably have to immediately do some data cleansing afterward so that you can sort the high-quality, relevant data from the rest.

The better approach is to examine your goals and then examine the data you already have. Look for the gaps and blind spots in your existing data. A cosmetics retailer, for instance, might realize that their products appeal primarily to women — but which products appeal to which groups of women? Are they older or younger? Trendy or timeless? Eco-conscious or not so much? 

In this example, there are lots of hypothetical data points you could learn — and closing those gaps will help this theoretical retailer create highly targeted advertising that markets specific cosmetics to the people who are most interested in purchasing them.

3. Create a Repeatable Data Enrichment Process

Ready for some Greek philosophy? Don’t worry — it’ll be quick! Here goes: The Greek philosopher Heraclitus is credited as the first to push the idea that “the only constant is change.” 

It’s super easy to see how that philosophy applies to marketing. Everything — customer needs, trendy items, most used social media platforms, most effective marketing techniques, and so on — is always changing.

As the marketplace shifts and evolves, your data needs to evolve with it, and that’s why you need to create a data enrichment process that is repeatable. It shouldn’t be a one-and-done effort, but rather, a constant process that you use to stay on top of your marketing game. Create workflows that you can repeat as needed, and invest in data enrichment tools that you can use again and again for data collection. 

4. Be Ready to Scale

No matter what your data enrichment goals may be, the end result should be some type of growth: expanding your reach, increasing numbers of leads generated, increasing sales, and so on. As your marketing efforts improve, your business will grow, and so will the amount of data that needs to be enriched. 

Thus, however you design your workflows and whatever tools you choose to use for validation, data management, and data collection, make sure that they can scale up to accommodate ever larger volumes of data.

5. Collect Data, Apply It to Customer Segments, Then Rinse and Repeat

The final step is the data collection itself. With your processes and data collection tools in place, garner the data that you need to fill the gaps in the knowledge you possess about each customer segment.

And then start all over again! Except this time — provided that you created repeatable processes — you won’t have to create new processes. 

So, once you’ve collected your data and applied it to your customer segments, take a look at the profiles for each segment. The gaps may be smaller, or as market shifts occur, there may be new gaps that need to be filled. Identify them, make any adjustments needed to improve upon your process of enhancing data, then start collecting and testing new data.

What Data Enrichment Tools Should You Use?

Data enrichment: entrepreneur looking at her business dashboard

So how do you go about collecting and managing the data you need to make better, more informed decisions? There are lots of different kinds of tools out there. Let’s explore a few of them.

1. Jebbit

Data enrichment: Jebbit’s 4 On Ramps

There are a few platforms out there that offer tools to help marketers collect first-party data directly from their customers — and Jebbit is the top choice. With this platform, you can create quizzes, surveys, lead forms, and other types of interactive experiences that engage customers while gathering information you can use to make better business decisions. 

In fact, data enrichment is one of Jebbit’s 4 On Ramps, which is a roadmap for a first-party data strategy. You can leverage this On Ramp to create “golden” customer profiles that allow you to deliver highly personalized content.

2. Customer Data Platforms

Customer data platforms (CDPs) are kind of like data warehouses. They’re designed to help you collect, manage, and organize all of the customer data that you’ve collected from any number of sources — social media, customer relationship management (CRM) platforms, customer engagement tools, and elsewhere.

Often, these platforms use automation to collect and organize data in real time, and they also often offer integrations with other software and systems that your marketing or sales teams might be using. That’s what makes a CDP a good investment — not only do these platforms manage data, but they make it more accessible to you and your team so that you can put it to work.

3. Built-In Analytics

Marketing and sales software, social media platforms, and other vital systems like CRM tools usually offer their own suite of analytics (in other words, data that the software, platform, or system collects for you). Leverage these analytics to collect vital information about customer relationships, geographic data, demographic information, income level, and other details you can use to enhance your targeted marketing efforts.

4. Third-Party Data Platforms

With recent changes in data privacy rules and regulations, third-party data is becoming less reliable as a primary source of customer data. However, you can still leverage it to an extent, as a way to test the data that you’ve collected or to fill small gaps in your data. 

Just be mindful that some types of third-party data can be filled with inaccuracies. Thoroughly research platforms before choosing one that is right for your needs, and make sure that these platforms are compliant with both CCPA and GDPR regulations.

What Is a Data Enrichment Example?

JCPenney Beauty's online quiz

Ready for some examples of data enrichment in action? We’ve got a great case study featuring Jebbit and JCPenney

This retailer is using outreach in the form of quizzes and rewards to engage customers and collect data for enrichment. Part of the reason why is because Apple, Google, GDPR, and CCPA are eliminating third-party cookies — and that means brands won’t be able to rely on this data source anymore.

Through Jebbit, JCPenney is able to go straight to the source. They’ve rolled out quizzes that ask people about lifestyle preferences and shopping habits. Customers get rewards points for completing the quizzes, and JCPenney gets information they can use to enrich data and improve decision-making. 

JCPenney has also leveraged quizzes to learn more about customer pricing preferences, and to help match customers with the right products.

The benefits have been big. Among other things, the product match quiz brings in lots of new customers, with a 60% lead capture rate. All the while, JCPenney has been gathering data that they can use for enrichment, which lets them further improve their messaging and content.

Want to see more? Check out our additional case studies that highlight how you can use Jebbit for data enrichment and other use cases.

Jebbit: The Ideal Solution for Data Enrichment

Ready to start improving your marketing and sales efforts with accurate, refined data? Jebbit is here to help you get consumer data directly from the source. Create engaging interactive experiences and collect information so that you improve the customer journey and your conversions.

To learn more, book a demo with a Jebbit Experience expert!

Brittany Gulla
Director of Growth Marketing

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Jebbit Grid Decorative
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