Rethinking Audience Targeting In A Signal-Loss Era (With The R.E.M. Framework)

Do you know who your audience is and what they want?

Over the last 20 years or so, we used to rely almost purely on data to answer that question. But as cookie tracking and user signals declined and analytics shifted toward sampling (what we refer to as the “signal-loss era”), we’ve lost some of that superpower. On top of this, we’ve handed over control to hyper-personalized platforms with “black box” targeting algorithms to find our audiences, leaving us less able to truly understand what is going on. And in doing so, we have lost track of the user.

In a way, the abundance of data made us complacent: “Data-informed” became the standard, while “user-informed” strategies progressively faded.

The problem with that over-reliance on data is that it made it “okay” to forget we are fundamentally communicating with humans and creating connections. We focused on the outcome and lost the drive to know who we’re connecting with and what leads us to acquire certain users or lose some.

And while signal loss and AI targeting might be perceived as a constraint, in reality, it is actually a great opportunity to go back to basics of marketing. It means we can focus on really understanding the user as a person, and not as trace fragments of data they leave in our web analytics.

Ultimately, getting to know them means we can serve them better – and find stronger, long-lasting ways to connect.

The Opportunity: Understanding Users And How We Reach Them

Even if we still had the data we had before, would it even be enough? I don’t think so, because it assumes user behavior is limited to what we can observe. In reality, behavior is shaped by a series of small, automatic decisions that happen below the surface, often driving outcomes before any action is even initiated – let alone tracked.

On top of this, when we talk about “understanding the user,”  this is often reduced to understanding their needs and a rough demographic, but that’s only part of the picture. Users are people, with unique needs and patterns of thoughts at every stage of their consideration journey.

Now more than ever, we need to truly know who we are talking to and interacting with. What makes them favor us over a competitor? What media and channels are they using so we can reach them? What emotional triggers are really relevant to them? What is important to them at every stage of the journey? Only after answering these questions can we claim to have at least scratched the surface.

I’ve said before that human decision-making is inherently imperfect, shaped by cognitive biases and heuristics that help us navigate complexity without analyzing every option in detail. And that’s the reason why knowing what they want is often not enough to get the full picture – you need to know how they make decisions too.

When we fully understand the user, we can shape our approach ahead of outcomes, inform testing and platform targeting, and even anticipate results before…