How to capture your audience’s attention
Editor’s note: Francis Raho-Jeavons is a senior consultant at We Live Context.
This morning, the first thing I saw on Instagram was a dancing miniature hippo, followed by a heartwarming article about an 80-year-old couple giving life advice. Then came “Three types of love languages” followed by an ad for Amazon Prime.
This is the consumer’s life. A continuous stream of ever-changing content that flows in and out of our screens in an instant. It is indicative of what marketeers and advertisers have termed the “attention economy.” In a world where information is anywhere, everywhere, all the time, our attention is a scarce, finite resource every brand wants to capture. Even if it’s just for a second or two.
Despite this acknowledgement of the importance of attention, there is no universal agreement on how to measure it. And if we don’t measure it the right way, the customer’s attention will vanish before our eyes. So, how should we measure attention the right way in research to gain access to this all-important resource?
What is attention and why is it important in marketing research?
We know attention is about capturing and holding your target audience’s focus. But to really understand attention, we must dig a bit further into the detail. Just understanding whether someone paid “attention” leaves important questions unanswered, including what the quality of that attention is, how long it is being held and the effect it has on brand recognition, memory and impact.
There is a stark difference between quickly scrolling over something on Instagram and five-minutes of focused reading (a level of attention I am hoping this article can capture). Many of the ways we capture attention fail to make these key distinctions. For instance, a common way to analyze attention on Instagram is to check the number of impressions it gathers. Putting whether someone has paid attention on a binary scale is not enough. However, with a little help from behavioral AI there are more intricate ways we can measure attention to get answers to these nuanced questions.
Attention tracking: How behavioral AI helps researchers determine ad effectiveness
Tracking attention has long been possible with eye-tracking tools. However, AI tools have enabled this data to be predicted based on thousands of eye-tracking studies. Behavioral AI tools make predictions about what parts of ads are going to drive attention through attention heat maps.
These can be used to determine which parts of an ad or communication are attention grabbing, how much attention is dispersed and the intensity of it in different parts of the ad. The best part about using attention heat maps through behavioral AI is that designs can be continuously updated and tweaked until you get the desired distribution level.
How has attention changed?
When tracking the effectiveness of ads, it's essential to not only capture attention, but also understand how that attention is sustained or how it changes over time. By analyzing attention over time, brands can determine which elements of their content hold viewers' attention for longer periods and how those moments contribute to long- or short-term brand recall. This can give insight into what ad may work best in times where you need attention fast, like on TikTok, and where you may have more time to capture attention like in print media.
We can also look at how attention moves through an ad. For instance, we may want a consumer to look first at critical information about an event before moving to the call to action. This allows us to not only understand if they are paying attention, but what parts of the ad they pay attention to each second they engage with it.
Finding the link between attention metrics and emotional responses
Emotions play a key role in determining the depth and quality of attention. Ads that evoke strong emotional responses, whether joy, surprise or empathy, are more likely to leave a lasting impression in consumers' minds. Emotional responses help sustain attention and increase the chance that the viewer will recall the brand and the emotional connection they felt when making decisions.
By combining attentional metrics with emotional data, marketers can gain a more comprehensive understanding of how their content resonates, allowing them to craft messages that capture attention and evoke the right emotional response. We do this by testing the emotional triggers and association which are generated by ads in the split second after the ad is shown.
Testing the quality of attention
Finally, once the in-depth insight into the quality of attention has been gathered through attentional heat maps and emotional response testing, we can test the outcomes of that attention through comprehension testing. This can be used to test what information the consumer has managed to pick up on and their overall understanding of the ad. This acts as a final marker of what impact the attention has had on the viewer. You can even use comprehension testing in conjunction with attention maps to see how the grades of attention impact the final recall.
Where does this leave us?
In today’s attention economy, measuring views and impressions isn’t enough. To make a lasting impact, brands must focus on sustaining attention and evoking strong emotional responses that drive consumer behavior. AI tools now help marketers go beyond basic metrics like views, providing deeper insights into how attention is held over time and how emotions influence brand recall.
By leveraging these tools in conjunction with the right survey testing, brands can create more engaging, memorable content that resonates with audiences and drives long-term loyalty. The future of attention research lies not just in capturing attention, but in making it count.