As we launch into 2021 with the expectations of the external environment becoming more positive, it is a great time to explore an important topic, one that will certainly captivate companies in the process of digital transformation, as well as those that are preparing for a cookieless future – the difference in meaning and value between first-party data and authenticated audiences.
Join us for our upcoming webinar: Deconstructing the Cookieless Future
It’s always nice to have a common ground to start from and frankly, these buzzwords are getting mixed up in practice. That’s not surprising –it becomes especially confusing as a terms buzzworthiness increases (do you remember when terms like ‘value proposition’ or ‘engagement’ rose in popularity?).
So here is some clarification to achieve a shared baseline:
First-party data is a general term that describes data you or your organization has collected about your audience. Great examples of this include customer purchases, website activity, and social media accounts.
An authenticated audience is a group of users that have gone through some sort of validation process – in the digital world, this occurs through some sort of log-in process. For instance, your website may have a ‘My Account’ option where a Visitor signs up with their email address and other personal information like a phone number.
You might be thinking, ‘well they’re related’. Yes, they absolutely are, no doubt about it. Authenticated user data is a form of first-party data. And that’s the key – they are related, but not the same thing. For instance, you can have first-party data that is unauthenticated. What a great way to segue into our next talking point – understanding value.
It is quite likely that you can see or have directly experienced the benefits of using first-party data. Simple example – you have an email list of leads you have obtained from creating a webinar. You send a promotional email to that list informing them of a new product launch, which results in 20% of that list making a purchase. You have used first-party data to generate revenue!
But what if your email list consisted of 90% of the emails being fake? Unauthenticated first-party data is a real phenomenon. A good example of this is bots, which behave like real people in that they can visit your website, click on your ads and so forth. And there have been estimates that 60% of all online traffic is bots!
In a general sense, first-party data offers value to organizations but arguably authenticated first-party data is going to become the lifeblood of companies that operate in a digital context – especially as we move towards a cookieless future where digital marketers will not be able to rely on data extracted from website activities for personalization and advertising programs.
When data is authenticated, we can link information from multiple sources together, add to the single-customer view, and act confidently when strategizing on how to best attract and retain customers. In contrast, with unauthenticated data, our ability to act is hindered by uncertainty and our efforts result in wastage.
Marketers are used to creating business value – that’s one of our primary job requirements. However, whereas the notion of value creation is typically applied to customer acquisition and retention strategies, now marketers need to think about how they can create value in order to capture authenticated first-party data so that they can be more successful at their jobs in the future.
That is a topic for another blog post, but much like you have to consider your return on investment from planned marketing activities, you may have to start thinking about how to calculate the return on a program where the primary purpose is authenticated first-party data collection.
Sound fun? We look forward to exploring that challenge.
As consumers become increasingly digitally savvy, and more and more brand touchpoints take place online,…
Marketers are on a constant journey to optimize the efficiency of paid search advertising. In…
Unassigned traffic in Google Analytics 4 (GA4) can be frustrating for data analysts to deal…
This website uses cookies.