We Need To Talk About Customer Data
And probably replace the term altogether
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.
Having spent the last 3 years thinking and writing about customer data, I too have contributed to the excessive use of this term in my content and to be honest, have cringed a little every time I’ve done that.
It’s about time we rethink the usage of customer data and maybe even replace it with a more accurate term — audience data.
My goal is to initiate an important conversation and find a conclusion that benefits the industry at large (and maybe take some credit along the way)! 😀
So, here’s my attempt to dissect the term customer data.
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.
Therefore, you must keep in mind that you’re not dealing with a homogenous set of people — you're dealing with multiple audiences, each with a very different set of needs and expectations from your brand.
I believe audience data is a more appropriate term here; a good first step before embarking on data collection efforts is to understand one's diverse audiences — their needs, priorities, workflows, and constraints, to understand why they come and why they leave.
The "data" in customer data (audience data)
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 implicitly or unintentionally as well as explicitly or intentionally.
It’s useful to think about these two types of data in terms of first-party data and zero-party data where the organization is the first party and the end user is the zero party.
The term ‘zero-party data’ hasn’t seen wide adoption yet and people often just stick to ‘first-party data’ even when referring to zero-party data. One of the factors that cause confusion is that giving consent to be tracked is not the same as handing over data explicitly.
However, I believe the distinction is not only helpful, but also important in the privacy-first era.
Hence, data collected implicitly by organizations is first-party data, whereas data shared explicitly by the end user is zero-party data.
Let’s unpack this.
A user shares data 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.
In other words, brands collect audience data implicitly across different touchpoints to understand user behavior and build better experiences across the customer journey.
Implicit data or first-party data can be further broken into three types: behavioral data, entity data, and identity data.
Any piece of information that an end user (the zero party) shares with a brand intentionally or explicitly — by inputting details into a form, or via communication channels like email and chat — falls under zero-party data or explicit data.
In other words, users share data explicitly with brands in order to receive personalized experiences, communication, and offerings.
Zero-party data or explicit data can also be broken into entity data and identity data.
The diagram below illustrates the different types of audience data.
I’m no teacher and don’t intend to proclaim what’s right and what’s not. As mentioned earlier, I merely wish to initiate a discussion about an important topic that I care about and together, find a conclusion.
So what do you think about the need to replace or at least limit the usage of the term “customer data”?
Does the definition of audience data resonate?
And does the delineation of first-party data and zero-party data make sense to you?
In the next issue, I dig deeper into the two types of audience data — first-party and zero-party — and describe their characteristics and what causes confusion between them, check it out.
Work with us
We’re trying to solve a fundamental problem that I’ve seen numerous companies struggle with — the ability to deliver hyper-personalized communication by understanding the specific needs of one’s diverse audiences.
We hope to bring order to the communication chaos that exists today, especially between B2B brands and their audiences, and in the process, enable them to understand the changing needs and preferences of their audiences to deliver content and experiences that are always personalized.
At astorik, we’re building a full-stack solution to make this happen.