Hacking Audience Attention Is Every Advertiser's Top Issue

In a world of infinite scroll and algorithmic overload, attention has become one of advertising’s most contested, and misunderstood, currencies. For advertisers and agencies alike, the battle isn’t just about being seen; it’s about being remembered.

VCCP Media, in partnership with leading attention economist Dr Karen Nelson-Field and attention measurement company Amplified, set out to challenge prevailing assumptions about how attention really works. Their groundbreaking new report, 'Hacking the Attention Economy', delivers a compelling finding: just 1.5 seconds of attention can drive meaningful brand outcomes, if distinctive brand assets are deployed with precision and consistency. That’s a full second shorter than the previously accepted 2.5-second threshold for active attention.

This revelation carries profound implications for marketers navigating shrinking budgets, fragmented channels and performance pressure. Because short exposure isn’t wasted exposure, not when creative and media are aligned, and brand identity is made unmistakably clear. In fact, as Nelson-Field argues, attention is the fuel for brand growth, but it must be managed, measured, and invested in with greater strategic discipline.

The report also reawakens Ehrenbergian truths about brand building: that marketing must support the full funnel. not just performance nudges aimed at existing buyers, but awareness and trial to attract future ones. As Nelson-Field points out, over-investment in short-termism has led many brands into stagnation, with bland creative and shrinking relevance to show for it.

And in an era where some marketers believe they only have a single second to earn engagement, the research provides clarity: yes, you can make an impression in that fleeting moment - but only if your brand is already front-of-mind and creatively encoded in memory. It’s a strong argument against the minimalist “Blanding” trend, which strips away the very assets that make a brand recognisable.

VCCP Media’s attention work is not just academically robust—it’s commercially urgent. It offers a rare, data-backed guide to media investment that transcends metrics like viewability, connecting attention more directly to memory, brand outcomes, and ROI. And with the rising complexity of generative AI, creator content, and CTV ecosystems, the need for such clarity has never been greater.

In the following Q&A, Dr Karen Nelson-Field unpacks the implications of the report and explains why brands must stop taking attention for granted.

Creative Salon: The attention economy is perhaps one of the most complex problems that advertisers face today. Where would you place the difficulties around attention on the problem scale?

Nelson-Field: I think it's the number one issue for advertisers now and into the future, because we were buying on metrics that were our currency but meant very little to what they [advertisers] wanted, which was engagement and value. And so for me, call it ‘attention’, call it ‘focus’, call it whatever you want - attention is a measurement that relates to the value exchange that you get when you put an ad on and what do you get back? So for me, it's number one.

Where does this challenge stem from? What is the attention economy?

So the attention economy is not a new concept. It actually comes from other industries. Typical marketers stole it from other people many years later. The original attention economy comes from, in fact, World War Two, when they started to understand the impact of distraction on air traffic controllers. So, how do you understand the cause, the consequence, and the course correction of inattention on something?

It's been around forever… the attention economy then became about ‘how do you trade against it?’ It was originally in a different area, then the marketers started to realise that the value exchange with advertising was people engaging. People started to call it engagement, and then it went off with the viewability and the ad tech and the digital space and went awry. So why it's big now is because advertisers want to understand how much attention people are paying, but there's scalable technology. The short answer is, viewability came in at a time when we needed to scale measurement, but it failed to understand human interaction or human viewing.

A marketer recently told me that the average time they had to engage someone was now about a second. You've proven that 1.5 seconds is enough to create a memory with consumers.

What we've proven here with this work is that the average is 2.5 seconds. So, 2.5 seconds is a line in the sand and what I call ‘the attention memory threshold’, and we've seen that across many years. That's the point in time when people start to get it, and you'll be able to measure memory structure change. That is the line in the sand. What we've proven here is that if you have distinctive assets that are strong - obviously, distinctive assets are big brands that have strong, amazing, creative, branding assets - you can get away with 1.5 seconds because you already have memory structures around those brands. So we proved that you can create a memory with 1.5 seconds, but only if you're a brand that has distinctive assets, not generally speaking. So if you're a no-name, then no one will remember you at 1.5 seconds.

That's interesting then, because we've seen a bit of a trend with big brands turning to minimalism, where they lean on that familiarity, but they take out the branding and so forth. Is that, is a dangerous tactic then?

That's called ‘Blanding’. It’s not as much anymore. Some of the bigger brands are really recognising that, and our research has picked that up in previous work. We've even seen massive brands in other real-world experiences - not this research, specifically - where they're completely misattributed, someone like McDonald's, and no one even knows it's them, because they try and be clever on platforms like TikTok and things like that. So it's a massively dangerous game for any advertiser to think that people know you well enough that you won't be considered in the competitor set. It's a big, dangerous game that probably the half a percent of big brands this in the world still play. So, what happens is you lose your next set of generation category buyers. Even though we have grown up with Microsoft, for example, the next generation, I don't even know if my boys would know who they are if they advertised. So you've got to be really careful that if you stop investing in your distinctive assets, you ultimately will not train your next generation of category buyers, which is a scary future problem for a CMO.

Can you explain the difference between ‘trial’ and ‘nudge’ and what brands should be thinking when looking at those?

On trial and nudge, it's awareness, trial, reinforcement and basically that is basically the Hierarchy of Effects model, but the AIDA (awareness, interest, desire and action) one is the most famous. it suggests that it happens in a linear fashion. It doesn't.

So, awareness, trial, reinforcement is a model of effects that basically says that people will jump in at different times depending on if they've bought the brand before. I don't always need awareness for Apple because I'm an existing buyer, but I might need to trial a new product before I'm interested in buying it.

So it's this concept that you're always having to train new category buyers through awareness. You get them to trial something, and then the reinforcement - or the nudging - is to get them to buy it again. It's a classic Andrew Ehrenberg Hierarchy of Effects model, which means you should be advertising for every part of the funnel, which is why brand assets are really important, because if you start to remove them, you are only appealing to those who know you very well. If you take your brand away, then the next generation won't know who you are.

Supporting all parts of the funnel is a very difficult thing for marketers to do when budgets are being squeezed. Everything needs to be justified, and they are having to cherry-pick, surely?

They do, but they cover the wrong end. My friends Peter Field and Les Binet always talk about the wrong 60/40, and we just saw that in ‘The Cost of Dull Work’ that I did at Cannes. But ultimately, brands do account for the whole funnel or the whole buyer experience, but usually the emphasis is on the wrong end, and they spend more on a nudging piece. But what happens is you're already nudging existing buyers, whereas the trial piece and the awareness piece are easier to grow your brand. That's a classic Andrew Ehrenberg principle.

I've heard that from quite a few marketers in the last couple of years, saying that it's becoming very performance-centric, which is understandable when the revenue they need to drive revenue quickly.

It’s a complete false economy, because these people are going to buy anyway. I mean, it's important to what they call ‘maintain them’, but not to overinvest in them. It's a false economy. I just read a big piece of work that asked most of the CPG brands ‘What's happened in the last 10 years of their life?’. Since 2010, they're all struggling because they all started to focus on performance, and so their profits dropped, their growth dropped, and they're in a world of pain because they did exactly what you just said. They went to Blanding and went to performance, and now they’re not growing.

Has TV been written off too soon?

I don't think it has been written off. You might hear that in the digital space but TV has its role. I'm a big fan of CTV because of the nature of the ability to target and what I like about CTV is the personal nuance - it's just like digital, but on a big screen. I've seen the attention data, I know what being able to control your experience means from a TV perspective. TV is often quite local. I don't think it's been written off and I've done plenty of work to show that. The value exchange is higher than a lot of people think.

What do you think the advent on Gen AI will mean for the quality of content and its impact on attention?

I think we've all started to recognise the patterns in Gen AI from a writing perspective. I think that the creative development models will improve over time. We're just not used to it. It was a bit of a novelty, and now we can tell who's using it, but I think it will improve. And the learning language models out there, that's the first pass of the future. The creative type of AI is going to play a much bigger role than your ChatGPT-type stuff, where you can pick out the patterns.

And what about the Creator Economy as a solution for marketers when it comes to gaining attention?

So what we have seen is that creator - or influencer content - does render higher than average within the constraints of each different format. It's not new news to me, because the Creator Economy, the old influencer-type ads, are really a form of relevance. And relevance is a long-noted metric or a long-noted factor of engagement, because it's something when it's personal. So there are two types of attention triggers: one is called top-down, and one is called bottom-up. And bottom-up is usually unintended circumstances, like if someone screams at you all of a sudden, ‘Look!’ Or if a bright colour comes on the TV, you'll stop and look. But the top-down ones are about relevance and resonance and things that you've purchased before. So that's not new news that the Creator Economy will cut through engagement, but only to the point where the format allows it.

What surprised you from conducting the effectiveness research?

There are some really amazing nuggets in there, more than just one. I probably wouldn't say anything surprised me, but what I did learn was about the 1.5 seconds, the hypothesis that we set out to consider, not to prove, but to consider, was, ‘Could good branding mean that you could get away with less attention?’ And the short answer was ‘yes’.

Now I think that's the only circumstance that I see in all the data that we've ever had around the nuance around this 2.5-second mark. So I think that was pretty fun for me. And then obviously the other piece that we did was, we built multipliers between the good and bad twin [see chart above], meaning that, from a return on investment perspective, we built the cost as it relates to the outcome. So, a multiplier, like an ROI multiplier. Then we translated the gap, the differential, into a tariff. So if you do this, what does it actually cost you per dollar? If you've done that, then you spent your dollar well. But if you do this, that is your cost, or your tariff. All of it made sense. Nothing shocked me, but it was amazing to be able to quantify robustly what I hadn't thought to consider before.