This is part one of the series titled It's Audience Data.
We need to talk about “customer data”, an overused, catch-all term that's used rather loosely, especially by vendors of data tools when describing their products — it's tiring and sometimes even frustrating. It’s about time we rethink the usage of customer data and maybe even replace it with a more accurate term — audience data.
In a series of guides, I'm going to dissect "customer data" into the tiniest possible bits, hoping to find some answers and share some ideas regarding personalization and privacy.
The first part of this series is an attempt to answer the following questions:
- What does customer in customer data refer to?
- What does data in customer data refer to?
Additionally, it covers the characteristics and the key differences between first-party data and zero-party data — the two types of audience data.
I don't intend to make any proclamation here — my goal is to initiate an important conversation and find a conclusion that benefits the industry at large.
Let's dive in.
The "customer" in customer data
The definition of "customer" as per the Oxford Dictionary is "a person or an organization that buys goods or services from a shop or business."
However, when people use the term customer data, they essentially refer to data about visitors, prospects, free users, partners, and of course, paying customers. And that's not all — customer data also includes data about inactive users and past customers.
B2B organizations in particular no longer deal with a homogenous set of people who either become customers or don’t. They deal with diverse audiences, each with a different set of needs, preferences, and expectations.
Therefore, audience data is a more appropriate term than customer data. I ran a poll on LinkedIn where almost 70% of the audience that voted agreed that the data referred to as customer data isn’t just about customers.
In order to deliver content and experiences that are always personalized, organizations need to understand one's audiences — understand their needs, priorities, workflows, and constraints, and understand why they come and why they leave.
Understanding the preferences of these “other audiences” and engaging with them in an authentic manner is probably the only way for organizations to build thriving practitioner communities that last. And doing so is the best way to attract partners and turn industry experts into advocates.
The "data" in customer data (audience data)
Hereon, I'm going to use the terms "audience data" and "customer data" interchangeably.
I've described customer data before in quite a bit of detail albeit with a deep focus on product analytics.
Now, I'd like to offer a universal definition that has a much broader scope.
Customer data or audience data refers to data that individuals share with an organization or brand implicitly or unintentionally as well as explicitly or intentionally.
It helps to keep in mind who the two parties are when we talk about the two types of audience data:
- The organization or brand that collects the data is the first party
- The end user who shares the data is the zero party
Data collected implicitly by organizations is first-party data, whereas data shared explicitly by the end user is zero-party data.
It’s also worth mentioning that the term ‘zero-party data’ hasn’t seen wide adoption yet and it’s common practice to stick to ‘first-party data’ even when referring to zero-party data. There are several points of confusion here but before we get to those, I’d like to describe the key characteristics of these two audience data types.
Understanding the distinction between first-party data and zero-party data is not only helpful, but also important in the privacy-first era.
The data collected by an organization or brand from a user implicitly is first-party data.
It includes any piece of information that a user (the zero party) shares with a brand (the first party) unintentionally or implicitly when they interact with an app or website, and through other touchpoints such as opening an email or clicking on an ad.
Brands collect audience data implicitly across different touchpoints to understand user behavior and build better experiences across the customer journey.
First-party data has the following characteristics:
- First-party data is easy to collect since it's done by machines, without any intervention from people whose actions generate this data.
- First-party data is easy to store in a structured manner since data formats are specified when tracking is implemented.
- First-party data is easy to analyze using purpose-built product analytics tools.
- First-party data is not always accurate since it’s not shared by the user directly. It’s also prone to implementation errors and bugs as well as interference by VPNs and ad blockers.
- First-party data is ideally owned by the brand collecting it.
It’s important for brands to make it easy for users to understand what data is collected implicitly and enable them to opt out anytime so that their actions are not turned into data.
The data collected by an organization or brand from a user explicitly is zero-party data.
It includes any piece of information that a user (the zero party) shares with a brand (the first party) intentionally or explicitly by inputting details into a form, or via communication channels like email and chat.
Users share data explicitly with brands in order to receive personalized experiences, communication, and offerings.
Therefore, zero-party data is ideally owned by the end user sharing it.
Zero-party data has the following characteristics:
- Zero-party data is difficult to collect as it relies on the whim of the user who may choose to not share any data in the first place.
- Zero-party data is difficult to store in a structured manner since the data formats are not consistent (people who design surveys and forms don’t often think about data structures).
- Zero-party data is difficult to analyze since it requires manual interpretation.
- Zero-party data is deemed to be accurate since it's shared by individuals directly; however, it might not be factual because an individual can provide false information too.
- Zero-party data is ideally owned by the end user sharing it.
It’s also important for brands to make it easy for users to decide what purpose their data is used for, and easily take back whatever data they wish to.
The confusion between first-party data and zero-party data
There’s a fair bit of confusion regarding what exactly zero-party data is and how it’s different from first-party data and as a result, the term ‘zero-party data’ hasn’t seen wide adoption yet.
I’m hoping that the differences mentioned above are helpful but I’d also like to address the various issues where the confusion stems from.
A specific data point can either be first-party or zero-party
Depending on how it was collected, a piece of data can fall under either bucket.
For instance, if a user shares their location with a brand explicitly by inputting their city or country in a form or via another communication channel, that piece of data is essentially zero-party data.
On the other hand, if the brand derives the same piece of data implicitly using the user’s IP address, that’s first-party data.
Similarly, in a B2C context, if a buyer mentions explicitly that their favorite variety of cheese is Cheddar, that’s zero-party data. Conversely, if the brand infers the buyer’s preference based on their past orders, that’s first-party data.
One can differentiate between zero-party data and first-party data by asking, “where did the data come from?”
Doing so also enables one to understand who should ideally own the data and decide how it’s used.
Providing consent is not the same as sharing data explicitly
By accepting a consent notice, a visitor simply agrees to be tracked by cookies, tags, and analytics tools which results in the collection of first-party data.
Providing consent to be tracked is not the equivalent of handing over zero-party data via a form or another channel.
Data acquired from external vendors is third-party data
Data obtained from a reseller or via an enrichment vendor is always third-party data since it’s not collected by the first party — neither implicitly nor explicitly.
Additionally, second-party data is just a subset of third-party data acquired from an external vendor. In my humble opinion, the term “second party” in the context of data serves no purpose other than that of causing more confusion.
The ownership of first-party data and zero-party data
Data ownership is a complicated topic and privacy regulations like GDPR and CCPA, still in their infancy, can be misunderstood or misinterpreted.
Which party owns what data is also very subjective and can vary based on how data is collected and what level of consent has been given by the audience.
Therefore, what follows is a logical explanation of who should own what data keeping privacy and the end user experience in mind.
But first, what does it mean to own the data?
Right to collection and storage certainly doesn’t give an organization or brand ownership of the data they collect and store.
Therefore, data ownership boils down to usage — who gets to decide how certain data is used?
Considering the above as an acceptable statement, here’s who should own what data:
- First-party data should be owned by the brand that collects it
- Zero-party data should be owned by the end user who chooses to share it with a brand
In other words, as long as they adhere to privacy regulations, brands should be able to use implicitly collected data to improve the audience experience without necessarily explaining how the data is used.
Conversely, when it comes to explicit data, the end user should be able to decide what purpose their data is used for and easily be able to retrieve whatever data they wish to.
Conclusion and what’s next
It’s certain that a combination of first-party data and zero-party data can unlock new possibilities both for brands and the end user.
However, with so many changes taking place in the world of technology and privacy, and with the changing needs and preferences of their audiences, brands really need a data strategy that incorporates both first-party data and zero-party data.
Head over to part two to learn about the subtypes of first-party data and zero-party data.
I’d like to thank Luke Ambrosetti and Glenn Vanderlinden who provided early feedback and helped shape this guide.