Glossary

What is first party data?

Advertising
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Key visual for first-party data
Written by
Erin Lutenski
Published on
April 4, 2024

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Historically, brands often preferred to use third-party cookies to inform decisions about audience targeting. There are several reasons why: It was widely available, convenient, and offered large datasets that could supplement (or make up for a lack of) first-party data. 

And using first-party data raises a lot of questions about compliance — especially for brands in regulated industries. This can make it intimidating for brands to put this data to practical use for advertising purposes.

But since third-party data quality has sharply declined in recent years, brands are looking to use their first-party data in new ways. In this article, we’ll break down what first-party data is and how it differs from other types of data. Then we'll cover how brands collect it, what they can do with it, and special considerations that European brands need to take.

Person submitting first-party data by paying with a credit card on a website
Purchasing history and behavior are important components of first-party data

First-party data: Definition

Sometimes called "proprietary” or “own” data, first-party data is essentially information that companies gather directly from their customers. Depending on the company’s first-party data strategy, this dataset may include names, email addresses, customer journey details as well as demographics, purchase history, and website activity.

First-party data offers valuable insights into customer behaviors, preferences, and interactions, serving as the foundation for crafting personalized experiences and driving targeted marketing efforts. This data, which comes from sources such as mobile apps as well as online and offline purchases, plays an important role in enhancing customer experiences and refining marketing strategies.

You’ll likely have heard of second- and third-party data before as well. Here’s what those types of data are and how they differ from first-party data:

Second-party data

Second-party data is sourced directly from a trusted partner organization. This type of sourcing occurs when retailers share purchasing behavior and customer preferences with supplying brands, for example.

While it doesn’t give the same amount of control and ownership as first-party data, second-party data provides useful insights into specific audience segments. In comparison, third-party data that brands acquire from external sources typically lacks the depth of relevance and specificity found in second-party data.

Third-party data

Third-party data is information collected from external sources. These sources include third-party cookies, data brokers, market research firms, or similar organizations that compile and/or aggregate data.

This means that unlike both first- and second-party data, third-party data is usually collected from external sources that have no direct relationship(s) with data subjects or initial collectors. This can result in lower levels of data accuracy.

How do brands collect first-party data?

Brands collect first-party data when their customers interact with the brand's owned channels. This could include visiting a website, participating in a loyalty program, using a mobile app, or many other touchpoints.

Brands can collect data from each of these actions to enrich their understanding of customers. Some examples of this information include email addresses or purchase histories.

Brands can collect and analyze this data in tools like customer data platforms (CDPs) or customer relationship management tools (CRMs). These tools also assist in building customer profiles so that brands can personalize their customers’ experiences based on individual preferences and actions. This approach allows brands to refine their marketing strategies by basing them on current customer behavior and preferences.

At the same time, it's crucial for brands to be transparent about how they collect, store, and use first-party data. This includes clear explanations and opportunities for customers to control their data preferences.

What can businesses achieve with first-party data?

We’ve already highlighted the possibilities for personalized marketing and enhanced customer experience that first-party data can open up. In addition, it can enable data monetization, improve product development, increase customer loyalty and retention, and optimize media and ad buying.

But the data can’t just sit by itself in your CDP/CRM. Instead, you’ll need to collaborate with other parties to make these use cases possible.

Visit our article on first-party data activation for a thorough overview of how brands can put their proprietary data to use and what options are available for performance media campaigns.

The significance of privacy in the collection and use of first-party data

First-party data often connects directly to people because it includes transactional and behavioral details from users who are identifiable or currently logged in.

For this reason, it’s difficult to overstate the importance of privacy in the collection and use of first-party data.

Complying with privacy laws and following best practices reduces legal risks while preserving brand reputation and integrity. And respecting customers’ privacy builds trust and fosters better relationships between businesses and their clients. 

But not all regulations are the same. First-party data has different sensitivity levels depending on the type of information covered. We'll dive into these in the next section.

Differentiating data types

When starting to put your brand’s first-party data to use, it’s critical to understand the different ways it’s handled with regard to privacy. You’re likely to see the terms “anonymous” and “pseudonymous” quite frequently here, so let’s break down what they mean.

Anonymous data

Anonymous data is data that cannot be linked to a specific person. This includes data that can - theoretically - be linked to a specific person, but doing so would require a disproportionate effort that nobody could reasonably be expected to invest. This is because any identifying information has been removed from the data - or such information hasn't been collected in the first place.

Pseudonymous data

Data classified as pseudonymous keeps those identifying factors which are removed in anonymous data. However, that information is replaced by a pseudonym (hence the name of the term) or some other type of unique identifier. This could be an email address getting replaced by a hashed email, for example.

The key difference is — unlike anonymous data — pseudonymous data can still be used to establish tracking patterns and behaviors of the person behind the pseudonym.

What these data types mean for your brand’s first-party data use

While the differences in the terms described above can seem cut and dry, the truth is they are frequently used incorrectly — oftentimes by organizations that have an interest in your first-party data or its activation. Brands can be misled by terms like "anonymous IDs" — which are actually pseudonymous. It’s up to brands to look behind the curtain and see how their data will actually be handled instead of relying on product descriptions from vendors.

This is especially important for European brands, who will have particularly strict regulations around both types of data. We’ll cover these regulations in the next section.

European-specific considerations around first-party data 

When the topic of using their proprietary data for ad targeting comes up, most European brands will have one question above all others: “What about GDPR?”

The General Data Protection Regulation (GDPR) requires a legal basis for collecting and processing personal data. That legal basis may be the data subject's consent or an overriding interest of the brand, for instance. “Personal data” is anything that can be used to identify a person from their information. This ranges from email or IP addresses to physical location, biometrics, and more. You’ll recognize from earlier paragraphs that much of this data is what companies collect as first-party data.

GDPR applies to all companies operating in the European Union that process personal data. This means it doesn't apply to anonymous data, but it does apply to pseudonymous data, as the latter is considered personal data.

And the regulation doesn’t stop with the collection of data or permissions around it — it also lays out specific requirements for how data is stored and under what conditions (if any) data can be processed.

This is what makes brands operating within the EU quite cautious about collaborations involving their first-party data, even when they know they’ll need to collaborate in order to activate this data. Data sharing agreements and other legal proofing of data collaborations can slow down progress and make the collaboration process very difficult.

Using your brand’s first-party data effectively and securely without third-party cookies

Making use of their own data is quickly becoming an inevitable part of brands’ ad targeting strategies. But as we’ve covered in this article, you can't get insights on this data and activate it on your own. You’ll inevitably need to collaborate with another party — like a publisher — to do so. And as detailed above, depending on the type(s) of data as well as your organization’s location, you’ll need to comply with different regulations.

Decentriq’s data clean rooms use confidential computing to ensure that you can join your data with collaborators without them — or us, as the operators of the clean room — ever being able to see or access your brand’s data. And because our clean rooms come with such high security guarantees, the time required for the legal approval process is slashed.

Don’t leave your data sitting unused; it’s one of your most valuable assets right now. Contact us to find out how you can reach new and existing customers with your first-party data.

References

Recommended reading

Post-cookie prospecting playbook

Our playbook breaks down the current options available to brands for targeting audiences on the open web — and how they stack up when it comes to reaching net new customers.

Key visual for post-cookie prospecting playbook

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