Not all Attention is the same

Mar 11, 2022

ADELAIDE, LONDON – March 11, 2022

As you build your attention knowledge base it’s worth remembering that not all attention is the same. There are different levels of attention which signify different things happening in the human brain. Humans have a default state of sub-consciousness, or pre-attentiveness. It’s a zombie state where we have a broad and un-specific focus to everything around us. Possibly the only good thing about zombies. Without a zombie state, all of the information in our environment would flood into our brains and overwhelm us.

To bring our attention into focus, something needs to stimulate our brain. It could be anything in our environment, including advertising. There are two types of triggers that flip us out of the zombie state: top-down and bottom-up. We’re not just making this up, these types of triggers are found in literature.

Top-down triggers are personal and goal-oriented. When we deliberately search for something online or see a personally relevant ad on a digital platform, it’s a top-down trigger and we pay high and controlled attention.The ad becomes our primary focus and requires us to think on a fully conscious level.

Bottom-up triggers are external and stimulus-driven. When an ad catches our attention with unexpectedness, such as high emotion, animation or high sound. It’s a bottom-up trigger and we pay low and automatic attention.

This is one of the reasons digging into levels of attention is so important. We want to understand and categorise attention according to the experience of the human looking at the screen. Seems like an obvious point, but real human experience is what we want to understand and real human experience is a complex thing.

With our machine learning models we can divide attention data we collect into three levels. Truly valuable insights live in the granularity of this attention data. We collect:

For mobile–

Active (eyes-on-ad) attention

Passive (eyes-nearby) attention


For TV–

Active attention – looking directly at the ad on the TV screen

Passive attention – in the room but not looking at the TV

Non-attention – TV is on, person has left the room

No-one sits in one of these attention states forever. We know that humans switch between attention levels when viewing advertising. In fact, we switch all day. High attention is hard to sustain. The reality check for the ad industry is that humans aren’t paying the level of sustained high attention to advertising you think they are. Worse, they just don’t care about it as much as you do.

Sidenote: if you think you’re a great multi-tasker, doing three things at once, you’re not. You’re just a good switcher and there’s a cost to that (but that’s for another time). Sadly when we switch, we’re just clocking up more and more hours of divided attention practice.

When the information we are actively searching for turns out to be irrelevant we switch back to zombie (aka pre-attention). When the next ad blasts us out of our pre-attention state, we launch back into high attention.

Why is this useful to know?

Levels of attention, and what lies beneath this data at a truly granular level, shifts us from WHAT people are watching to HOW they are watching. And HOW they are watching is where the relationships with Mental Availability, memory, brand choice all start to reveal themselves.

Different levels of attention have different jobs, depending on what you are trying to achieve with your campaign. Different levels of switching tells us just how effective an advertising environment, platform, format will be at holding a viewer’s attention.

Understanding this helps you choose the best environments for brand building vs brand reinforcement. It helps you fine tune effective creative for different environments. And it helps you decide where the advertising money should be spent.

It brings you one step closer to understanding how humans interact with the increasing range of advertising environments that confront them.

Because ultimately, devices don’t buy things but humans do.