With just over two decades of existence, neuromarketing is arguably one of the most innovative approaches in modern marketing. By leveraging neuroscientific methodologies, it enables the analysis and understanding of how individuals respond to visual, emotional, and sensory stimuli. This discipline aims to measure the effectiveness of advertising messages and communication strategies by assessing users’ attention, memory, and emotional reactions.

However, its practical application has so far been rather limited due to the high costs involved and the necessity of conducting laboratory-based research-a process that is often time-consuming and difficult to scale.

The advent of artificial intelligence (AI), however, has brought about a radical transformation in the field. Thanks to predictive algorithms and the vast availability of data, AI makes it possible to simulate and anticipate users’ emotional and visual responses without requiring their physical involvement. This evolution has made neuromarketing more accessible and scalable, unlocking new opportunities for optimizing advertising campaigns and communication strategies.


Thanks to AI, neuromarketing is overcoming the limitations of traditional research, enabling large-scale analysis of consumers’ emotional and cognitive responses. This shift has made the field more accessible, efficient, and capable of delivering increasingly personalized marketing experiences.
The evolution of marketing is moving from the attention economy, which focuses on capturing users, to the intention economy, which aims to understand and anticipate real consumer needs. AI plays a crucial role in this transition, allowing for data-driven strategies and predictive responses.
As neuroscience, AI, and big data become more integrated, ensuring transparency and regulation is essential. The International Neuromartech Observatory seeks to establish clear standards, ensuring that neuromarketing is used ethically and scientifically to build a more reliable and sustainable ecosystem.

The birth of neuromarketing: from its origins to a scientific revolution

Neuromarketing is a relatively young discipline, emerging from the intersection of neuroscience and marketing with the goal of better understanding consumer decision-making. Although the term was coined in 2002 by Dutch professor Ale Smidts, the idea of applying cognitive science to consumer behaviour has much deeper roots.

Interest in how the human mind works and its influence on decision-making dates back centuries. However, it was with the rise of experimental psychology that the foundations of neuromarketing were laid. German psychologist Hugo Münsterberg, considered the father of industrial psychology, recognised as early as 1913 the importance of understanding the consumer’s mind. His vision was strikingly modern:

Businessmen will eventually realize that customers are merely bundles of mental states and that the mind is a mechanism that we can affect with the same exactitude with which we control a machine in a factory.”

However, for decades, the practical application of neuroscience to marketing was constrained by technological limitations. It was only in the 1990s that research took a significant leap forward, thanks to advancements in neuroimaging technologies such as functional magnetic resonance imaging (fMRI), which allowed scientists to observe brain activity in response to marketing stimuli.

One of the first researchers to bring neuromarketing into practical use was Gerald Zaltman, a marketing professor at Harvard University. In 1998—four years before the term “neuromarketing” was formally coined—Zaltman patented an innovative research method known as ZMET (Zaltman Metaphor Elicitation Technique).

His approach was based on the idea that most purchasing decisions happen at an unconscious level. ZMET used carefully selected images to evoke deep emotions, stimulating memories and unconscious associations in consumers. This method demonstrated that marketing could no longer rely solely on consumers’ self-reported opinions but needed to explore the hidden psychological processes underlying their choices.

Zaltman himself explained this concept with remarkable clarity:

«A lot goes on in our minds that we’re not aware of. Most of what influences what we say and do occur below the level of awareness. That’s why we need new techniques: to get at hidden knowledge-to get at what people don’t know they know».

This insight paved the way for a new era of marketing, where neuroscience plays a fundamental role in designing more effective strategies.

The first neuromarketing experiment: Pepsi vs Coca-Cola

One of the most famous experiments in the history of neuromarketing was conducted in 2003 by neuroscientist Read Montague at the Baylor College of Medicine. His study was inspired by the classic Pepsi Challenge of 1975, a blind taste test in which participants sampled two soft drinks without knowing the brand. The results revealed that most people preferred the taste of Pepsi over Coca-Cola—yet, paradoxically, Coca-Cola remained the market leader.

Montague decided to replicate the experiment but introduced a groundbreaking element: participants underwent functional magnetic resonance imaging (fMRI) to monitor their brain activity during the test.

When subjects were unaware of which brand they were drinking, their ventral putamen—a brain region linked to pleasure and reward—was activated, confirming their preference for Pepsi. However, when they were told they were drinking Coca-Cola, a different brain region was stimulated: the medial prefrontal cortex, an area associated with higher cognitive functions and memory.

In other words, Coca-Cola’s brand evoked such a strong emotional response that it altered participants’ perception of taste, leading them to prefer it—even when their sensory reaction suggested otherwise. This experiment proved the profound impact of branding on unconscious consumer decisions and marked the beginning of a new era in neuromarketing.

Today, neuromarketing has evolved into a well-established field, widely adopted by companies worldwide to refine their communication strategies. Advanced technologies such as EEG (electroencephalography), eye-tracking, facial expression analysis, and fMRI allow researchers to collect increasingly precise data on how consumers respond to advertising stimuli.

These insights help marketers gain a deeper understanding of consumer behaviour, enhance product design, and optimise advertising campaigns to maximise their impact. As technology continues to advance, neuromarketing is set to play an even greater role in shaping the future of marketing and consumer engagement.

The evolution of neuromarketing: integrating neuroscience, AI, and Big Data

As mentioned earlier, the future of neuromarketing is increasingly driven by a new approach that integrates neuroscience, artificial intelligence (AI), and big data. The goal is to enhance the consumer experience and make commercial communication more personalised and engaging.

Giovanni Pola, Director of the International Neuromartech Observatory, explains:

Giovanni Pola, direttore dell'International Neuromartech Observatory

«Thanks to AI, we can now predict human behaviour with unprecedented accuracy, without having to bring millions of people into a lab. This completely transforms the landscape of neuromarketing, making it scalable and far more efficient

While traditional laboratory techniques provide highly precise data, they are expensive and difficult to implement on a large scale.

AI is now breaking these limitations through:

  • Predictive Analysis: AI leverages historical data to forecast how users will respond to specific stimuli, eliminating the need for direct participant involvement in laboratory studies.
  • Remote Data Collection: Advanced technologies enable the remote collection of biometric and behavioral data, making the process more flexible and scalable.
  • Automated Analysis: Machine learning algorithms can process vast amounts of data in real time, identifying patterns and trends that would be difficult to detect manually.
  • Advanced Personalization: AI-driven models use real-time data to create tailored consumer experiences, increasing engagement and relevance..

Giovanni Pola highlights:

«Artificial intelligence is allowing us to combine the best of neuroscience with the speed and efficiency of digital marketing. This is creating a new paradigm where emotional and cognitive data become central to strategic decision-making.»

Current applications and future perspectives

Neuromarketing is now being applied across various sectors, from advertising and retail to entertainment and education.

Neuromarketing helps assess the effectiveness of TV commercials, digital content, and social media campaigns. Technologies like eye-tracking and facial expression analysis measure users’ emotional engagement, enabling advertisers to refine their messaging for maximum impact.

Applied neuroscience is used to design commercial spaces, product packaging, and physical goods that capture attention and evoke positive emotions in consumers. Cognitive and emotional response analysis also plays a key role in user experience (UX) design, improving website, app, and digital platform navigation to boost engagement and conversions.

Neuromarketing techniques are used to test audience responses to films, TV shows, and multimedia content. These insights help fine-tune productions to enhance emotional engagement and viewer retention.

The field is also finding applications in learning and education, where neuromarketing is used to develop more effective teaching methods. By optimising educational materials based on students’ cognitive and emotional responses, it becomes possible to improve memory retention, comprehension, and knowledge assimilation.

Looking ahead, the most fascinating implications of neuromarketing lie in its potential to reshape the relationship between brands and consumers. Among the most promising developments, the emergence of digital twins stands out as a breakthrough innovation. These virtual simulations, capable of replicating the behaviour and emotional responses of specific user groups, could revolutionise qualitative research, making it more cost-effective and accessible, thus eliminating the need for large-scale laboratory testing.

At the same time, we are witnessing a shift from the attention economy to the intention economy, a new paradigm where the goal is no longer just to capture consumer attention but to predict and influence their purchasing intentions.

From attention economy to intention economy

The attention economy and the intention economy represent two distinct models of consumer interaction with digital content.

The attention economy, first theorised in the 1970s by political scientist Herbert Alexander Simon, and later reinforced by the rise of the internet and social media, is based on capturing and retaining users’ attention. In this model, content is produced in ever-increasing volumes, often prioritising immediate impact over quality. The goal is to maximise the time users spend on digital platforms, translating engagement into advertising revenue or commercial conversions. However, this approach has led to information overload, where users are constantly exposed to an overwhelming stream of content—often irrelevant, fragmented, or low-quality—making it harder to distinguish valuable insights from background noise.

In contrast, the emerging intention economy shifts the focus towards understanding and fulfilling consumers’ real needs. In this model, technologies such as artificial intelligence play a pivotal role in predicting and proactively responding to consumer intentions. The objective is no longer to passively attract users with generic content but to provide tailored information and solutions based on their explicit and implicit needs.

Thanks to a deeper understanding of users’ emotional and perceptual experiences, future marketing strategies could become increasingly personalised and proactive, anticipating consumer needs with greater accuracy. This shift represents a fundamental change, from competing for fleeting attention to building meaningful, predictive, and responsive interactions with consumers.

Finally, neuromarketing and artificial intelligence could play a crucial role in enhancing the ethics of communication. By integrating these technologies, brands can craft more meaningful messages, helping to reduce anxiety and alleviate media pressure on users—counteracting the overwhelming volume of stimuli they encounter daily.

Laura Luongo, project manager at the International Neuromartech Observatory, highlights this shift:

Laura Luongo, project manager dell’International Neuromartech Observatory

«Neuromarketing offers a unique value: it allows us to bring meaning to communication in an environment oversaturated with content, creating messages that genuinely resonate with people

Why an International Observatory?

Despite the opportunities offered by neuromarketing, the sector remains young and lacks clear regulation. For this reason, the Italian Neuromarketing Association (AINEM), in collaboration with the GreatPixel agency, founded the International Neuromartech Observatory (INO). Its goal is to map the neuromartech landscape and establish clear standards to ensure transparency, scientific integrity, and ethical use of these technologies.

Giovanni Pola explains:

«The Observatory is not just a research project but a platform for ensuring transparency and accountability in a rapidly evolving sector. We want to create a clear roadmap that allows all stakeholders to operate with scientific rigour and ethical responsibility.»

The Observatory aims to provide a detailed mapping of the neuromartech sector, identifying active companies, employed technologies, datasets used, and data collection methods. A key aspect of its work is ensuring transparency, making sure that information is gathered and managed ethically, respecting user privacy and minimising biases in datasets.

Beyond regulating data collection, the Observatory focuses on establishing industry standards, developing technical protocols, ethical guidelines, and quality criteria to ensure the reliability and validity of neuromarketing measurements. Collaboration between businesses and universities is another central pillar, with the creation of a dedicated platform for sharing knowledge, experiences, and best practices, fostering constructive dialogue between academic research and practical applications.

Finally, knowledge dissemination is a strategic objective pursued through conferences, seminars, and educational events. The Observatory is committed to informing both the public and industry professionals, offering insights into the potential and challenges of neuromarketing and AI-driven marketing.

The Observatory’s methodologies

To ensure a comprehensive and in-depth mapping of the sector, the International Neuromartech Observatory (INO) has developed a methodological plan that integrates qualitative and quantitative tools.

Laura Luongo, project manager of the initiative, explains:

«Mapping the sector was our first step. We gathered data on around fifty companies operating nationally and internationally, analysing metrics, technologies, and data collection methods. This initial work allowed us to address a latent market need, providing a structured and systematic perspective.»

The Observatory employs various methodologies to analyse the neuromartech sector and define quality standards.

Structured questionnaires are a primary tool, sent to mapped companies to investigate crucial aspects such as data transparency, dataset quality, and employed technologies. The responses help establish inclusion criteria and assess compliance with ethical and scientific standards.

Direct interviews with industry representatives are conducted to gain deeper insights into adopted methodologies and verify adherence to principles of scientific rigor and operational integrity.

Comparative analysis plays a key role in evaluating different technologies and approaches, determining their effectiveness and level of innovation.

Scientific collaborations with academic committees and industry experts ensure that the findings are validated and supported by a robust methodological framework.

Exclusion criteria are established to define the minimum requirements for inclusion in the neuromartech landscape.

As Luongo highlights:

«We have already identified two fundamental and non-negotiable criteria: data transparency and scientific integrity of the platforms. These are essential to ensure that neuromartech operates ethically and rigorously.»

Ethics and transparency remain central concerns. Giovanni Pola emphasises:

«In our sector, there are no particularly severe risks linked to technology adoption, but transparency is crucial. We need to know who provides the data, how it is collected, and whether it is truly representative. This is essential not only to ensure the effectiveness of analyses but also to build a reliable and sustainable ecosystem.»

Glimpses of futures

We now seek to understand the implications and impact of this new approach to neuromarketing, not only on players in the advertising and commercial sectors but, above all, on consumers. To do so, we will use the STEPS  (Social, Technological, Economic, Political, Sustainability) framework, which analyses future prospects from multiple perspectives.

S – SOCIAL

The evolution of neuromarketing will redefine the relationship between brands and consumers, making the experience increasingly personalised. Through the integration of neuroscience and artificial intelligence, brands will be able to tailor content, advertisements, and offers in real time based on individuals’ cognitive and emotional responses. This will lead to more engaging and relevant interactions but will also raise ethical concerns regarding the potential for manipulation and the erosion of consumers’ decision-making autonomy. Ensuring greater transparency and regulation will be crucial to prevent personalisation from becoming intrusive or excessively influencing purchasing choices.

T – TECHNOLOGICAL

Technology will drive the next phase of neuromarketing’s development. The fusion of artificial intelligence, biometric monitoring, and neuroimaging will allow for increasingly detailed insights into consumer behaviour. Advances in machine learning and predictive analytics will eliminate much of the uncertainty in marketing strategies, enabling brands to anticipate consumer needs with extreme precision. However, the widespread adoption of these technologies will necessitate stricter regulations to safeguard privacy and ensure ethical data usage. Additionally, the emergence of digital twins—virtual models that simulate consumer behaviour—could revolutionise how advertising campaigns and engagement strategies are designed.

E – ECONOMIC

The shift from an attention economy to an intention economy will significantly impact business models. Rather than merely capturing consumer attention, marketing will focus on predicting and stimulating purchasing intentions, leveraging AI to interpret and anticipate consumer needs. This will enhance sales strategies, reducing advertising waste and improving customer satisfaction. However, this transformation could challenge traditional advertising-driven economic models, compelling businesses to rethink their monetisation and customer retention strategies.

P – POLITICAL

As neuromarketing technologies advance, governments and institutions will need to address regulatory challenges to prevent abuse and ensure consumer protection. The use of biometric data and neuroscience in marketing raises ethical issues related to transparency, privacy protection, and the manipulation of purchasing decisions. Stricter regulations are likely to be introduced, imposing clear limitations on the collection and analysis of neurological and behavioural data. Moreover, discrepancies in national regulations could create misalignments in the global market, impacting digital commerce and companies’ international strategies.

S – SUSTAINABILITY

Neuromarketing could play a role in promoting more sustainable and ethical consumption choices. The integration of AI will enable the design of marketing strategies that encourage responsible behaviours, promoting eco-friendly products and reducing waste. Additionally, more precise targeting will help minimise redundant advertising campaigns, contributing to a more efficient use of resources. However, the real challenge will be ensuring that these technologies are employed not solely to maximise sales but also to guide consumers towards more conscious choices, striking a balance between economic growth and social responsibility.

Written by:

Maria Teresa Della Mura

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