Inside the Consumer Brain: How Neuroscience Can Predict Ad Enjoyment

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Video advertising continues to dominate digital marketing budgets; however, a fundamental question persists: What drives consumers to genuinely like an ad? How do consumer preferences and their psychological roots emerge when individuals watch video ads?

Traditional approaches to answering this question have relied heavily on self-reported preferences, which are prone to bias and offer limited insight into real-time psychological processing. Neuroscience provides a powerful new lens for understanding how consumers respond to advertising, offering real-time, high-resolution insights into the psychological processes that unfold during exposure to marketing stimuli.

In their 2024 Journal of Marketing Research article, authors Hang-Yee Chan, Maarten A.S. Boksem, Vinod Venkatraman, Roeland C. Dietvorst, Christin Scholz, Khoi Vo, Emily B. Falk, and Ale Smidts investigate how neural signals track and predict consumer liking of video advertisements. This neurophysiological approach reveals the critical moments in an ad that capture attention, trigger emotional responses, and lead to more favorable evaluations.

Connecting Neural Signals to Ad Enjoyment

The first part of the two-part study draws on data from three functional magnetic resonance imaging (fMRI) datasets to analyze neural signals during video ad exposure. These signals reveal how people process advertisements. The authors used neural measures related to perception, language, cognitive functions such as executive function and memory, and social-affective responses such as social cognition and emotion, to estimate self-reported ad liking. In the second part of the study, they examined how well these neural signals predicted aggregate ad liking.

The authors show that liking appears to be a cumulative process shaped by evolving neural states. The different measures displayed distinct patterns. Emotional signals were predictive of ad liking very early, starting around the third second of exposure, but they declined soon after. In contrast, social cognition signals became predictive after their peak and remained stable. Overall, they find that cognitive and social-affective responses during video ad exposure are strong predictors of how much people report liking an ad.

By bridging neuroscience and marketing, these findings offer new possibilities for marketers. The authors provide insights into how brands can optimize video content in an environment where competition is intense the audience’s attention is limited. Their findings can help marketers refine both the creative and structural elements of their ads, from the pacing of storytelling to the timing of marketing cues. As marketers aim to improve their creative strategies in a data-rich but attention-poor world, aligning with the brain’s temporal rhythm may be key to creating content that engages audiences and resonates with them.

In this interview, author Hang-Yee Chan discusses the implications for marketers: what this means for storytelling strategy, how neural patterns shift across platforms, and whether AI-generated content can ever feel human.

Q: Your study shows that emotion is an early predictor of ad liking, but its influence declines as the ad continues, while social cognition and executive function become more predictive. Why does this shift occur, and what does it reveal about how viewers process ads?

A: That early emotional peak reflects our brain’s intuitive reaction to new stimuli—it’s fast, visceral, and helps form immediate impressions. However, as the ad unfolds, viewers begin to process its deeper meaning. Initially, emotional elements grab attention and generate interest, an evolutionary adaptation that prioritizes the rapid assessment of stimuli. However, as viewers continue watching, they begin engaging more deeply in the reflective evaluation of the ad’s message, characters, and narrative through social cognition processes, while executive functions help them evaluate relevance, credibility, and value.

Q: Should advertisers delay complex brand messaging until viewers are emotionally engaged?

A: Yes, advertisers should strategically consider when to introduce complex information such as brand messaging or product features, but it goes beyond simply waiting for emotional engagement. Our research reveals that sustained engagement most likely comes from well-formed narratives—socially meaningful moments that encourage consumer empathy and perspective-taking.

While emotion serves as an important early hook that captures initial attention, social cognition elements sustain engagement throughout the ad’s duration. Rather than approaching ad design as a rigid sequence—first capturing emotion, then delivering information—advertisers should focus on seamlessly integrating product messaging within compelling storytelling. The sustained predictiveness of social cognition signals suggests that when viewers connect with characters or scenarios meaningfully, they remain receptive to information for longer periods. In essence, our neural findings support what many creative advertisers intuitively understand: stories that foster social connection and meaning will likely lead to the best results, creating a receptive context where product information feels relevant rather than being intrusive.

“Stories that foster social connection and meaning will likely lead to the best results, creating a receptive context where product information feels relevant rather than being intrusive.”

Q: Your study highlights that moment-to-moment engagement plays a critical role in ad effectiveness. Should marketers prioritize optimizing specific segments of ads that generate the highest neural engagement rather than the full narrative arc?

A: I don’t see an inherent conflict between optimizing specific segments and focusing on the ad as a whole. Truly effective ads sustain engagement throughout, making it shortsighted to isolate and optimize only a particular segment of the ad. Our study supports what many creative professionals intuitively know: impactful advertising relies on a sequence of meaningful moments that build a coherent narrative arc. Rather than optimizing isolated segments, our findings suggest that marketers should focus on the temporal flow between early emotional peaks and sustained meaningful storytelling. This perspective enhances traditional ad creation approaches by providing a neuroscientific framework for structuring narratives that capture attention and resonate more deeply. It is not about abandoning holistic storytelling for neural “hot spots” but rather using our understanding of these temporal dynamics to create more effectively structured narratives.

Q: How well do these findings generalize to other formats, such as short-form social media videos, influencer content, or interactive ads?

A: Although our study focused on traditional video advertisements, the underlying neural mechanisms we identified likely extend across a wide range of video formats, albeit with important contextual variations. The temporal pattern we observed—early emotional activation followed by sustained engagement through social cognition, alongside suppressed executive function—reflects fundamental information processing dynamics in the brain rather than processes unique to traditional advertising.

That said, the specific dynamics may be adjusted based on the format characteristics. For short-form content such as TikTok or Instagram Reels temporal compression might accelerate these processes, requiring emotional hooks and social cognition elements to work almost simultaneously. Influencer content, which already leverages parasocial relationships, may show even stronger social cognition activation from the outset than brand-created ads. For interactive advertising, we might see enhanced executive functioning engagement throughout the experience as viewers make choices that require more deliberative processing.

Q: As AI-generated video ads become more prevalent, how do you anticipate the brain’s response to them might change? Could key psychological triggers of ad liking—such as emotion, memory, or social cognition—shift when viewers are aware or even just suspect that the content wasn’t created by a human?

A: There’s a fascinating tension in how our brains may respond to AI-generated advertisements. On the one hand, humans have a remarkable tendency to anthropomorphize; we instinctively attribute intention and emotion to nonhuman agents. Just think about how naturally we talk to our pets, as if they understand every word. This suggests that our social cognition systems might readily engage with AI-generated content if it presents recognizable social patterns.

On the other hand, our brains are exceptionally adept at detecting subtle artificiality. Neuroimaging studies examining the “uncanny valley” effect have shown that our brain’s valuation and social cognitive systems penalize stimuli that appear almost but not quite natural. These neural responses occur even when we cannot consciously articulate what feels “off” about the content.

The key psychological triggers we identified in our research—emotion, memory, and social cognition—might function differently when viewers sense artificial creation. The social cognition component could be particularly vulnerable, as this system has evolved specifically to interpret genuine human social signals and intentions. For marketers embracing generative AI for advertising, this raises an important caution: even as the technology improves, our neural architecture may continue to detect subtle inconsistencies that reduce ad effectiveness through diminished social cognitive engagement.

The most successful AI-generated content might need to acknowledge its nature rather than attempt perfect human mimicry or focus on elements where artificiality does not trigger the same penalties. The evolution of these responses will likely depend on how AI-generated content develops and how exposure to it shapes neural expectations over time.

Q: Based on your findings, how do you think the neural processes you identified relate to the factors driving viral video success?

A: In a separate study (PNAS, 2024), my collaborators and I explored the neural mechanisms behind information sharing and found strikingly similar patterns: brain activity in regions associated with reward and mentalizing predicted whether the content would go viral. In other words, the same psychological processes that drive ad liking—emotion and social cognition—also contribute to content-sharing behavior.

We share cat videos because they make us feel good (emotional response) and help us relate to others (social cognition). This neural understanding raises important considerations regarding how information spreads online. The dominance of emotion in early processing explains why emotionally provocative content often spreads rapidly, sometimes at the expense of accuracy and nuance. Furthermore, the social cognitive component suggests that people share content not just for its inherent value but as social currency to signal group belonging, values, or desired identity. This implies that we may share information without fully considering its broader impact or unintended consequences.

Understanding these neural mechanisms gives content creators tremendous responsibility. The same techniques that make ads likable and shareable can be used to spread both beneficial and harmful content. As our understanding of these neural processes deepens, it becomes increasingly important to consider the ethical implications of creating highly optimized and emotionally engaging content in our hyperconnected media landscape.