The evolving field of neuromarketing¶
Isabel Dibble & Brandon Truong
As more and more portions of modern life are built to revolve around commerce, marketing, and communication, there is an increasing need to understand what is going on in the interactions thereof. When you see an advertisement, you’re interfacing with marketing stimuli that have been crafted to hopefully nudge you to buy a particular item. Although this pattern seems age-old, we are still at the forefront of understanding how we interact with and are affected by marketing. Neuromarketing has emerged and grown exponentially over the past couple decades as a core intersection of business, decision-making, and neuroscientific research, with large implications for both businesses and consumers. We might define neuromarketing as “the application of neuroscientific methods to analyse and understand human behavior in relation to markets and marketing exchanges” (Cherubino 2019). In this chapter, we discuss the emerging field of neuromarketing in-depth by describing the important methods used, its applications through various use cases, prefaced by a review of its origins. We close with an examination of the field’s ethical concerns and considerations, as well as incoming future directions.
In order to understand the concept and scope of neuromarketing, it’s helpful to first understand the fields of marketing and neuroscience from which it emerges. Marketing refers to the processes of attracting an audience to a product or service. Marketing as a business function is considered to have 4 key components: Product, Price, Place, and Promotion (The Marketing Book, 1987). Throughout all components, an essential goal is identifying and understanding a target consumer’s personality, desires, and needs. Therefore, market research is vital to studying and analyzing consumers’ behaviors to produce a product to sell at the right price and place. Lastly, understanding which platforms and how to message the product or service with promotions is important to capture consumers’ attention and convert their attention into sales of the product or service. To gain insights into consumer behavior, traditional marketing tools consist of conducting focus groups, surveys, and other behavioral studies looking at measures like recognition, recall, desirability/liking, persuasion, intent, attention, affect, (Venkatraman 2015). Although these approaches have resulted in a growth of understanding in the field of marketing, they primarily rely on qualitative behavioral and self-reports. The field of neuroscience offers itself as an appealing tool in uncovering components that affect humans’ cognitive processes, that can aid in understanding the “why” and “how” a consumer interacts or is attracted to a product.
In general, the goal of neuroscience is to understand the brain by identifying structures and the functions of those brain structures. Specifically through the advancement of neuroimaging technology, neuroscience has opened a more direct window into our brains by understanding the mechanisms underlying our interactions with our environment. The application of understanding our brain and its influence on human behavior has intrigued social and behavioral sciences. We examine specific technologies in this field as it pertains to neuromarketing in more depth in the Methods section.
Neuromarketing lies at the intersection of these seemingly separate fields of marketing and neuroscience. While there are nuanced versions of its definition, neuromarketing has emerged as a field to understand the neural structures and functions that influence how humans engage with marketing stimuli. Marketing stimuli can take the form of aspects such as product attributes, price, availability, sales promotion, and marketing communications (Lian 2016). In other words, neuromarketing uses the tools of neuroscience and applies them to the problems and questions in marketing. Although this chapter focuses on neuromarketing, it is worth mentioning that neuroeconomics is a closely related field that similarly looks at how neural mechanisms can inform and cause economic decision making (Sanfey 2003). Depending on how you view definitions of the fields, neuromarketing can be seen as a subfield of neuroeconomics. By providing an understanding of marketing-related decision-making at the neural level, the field enables another avenue in adding a holistic understanding through the brain with regards to behaviors we observe, that would otherwise be subject to subjectivity in self-reports and the like from traditional approaches. Take an example result like: a consumer exhibits likeness towards a product when packaged in a certain color. Traditional methods might conclude with this result, but a neuromarketing approach might in contrast take this result and see what happens in the brain when this behavior is exhibited, digging into the process by which this happens – the how and why, rather than just the behaviors themselves.
Methods of neuromarketing¶
As stated in the introduction, traditional tools in the marketing field have a limitation of relying on people’s self-reports to describe their feelings and preferences towards a product. The value of neuromarketing helps draw away from this reliance on subjective, self-reports to provide measurements of how an individual’s brain responds to a product. Some researchers in the neuromarketing field like to describe neuroscientific methods uncovering the “hidden” information our brain conveys in response to stimuli that an individual may not be consciously aware of. This phrase of “hidden” preferences is hotly debated among experts and while this chapter will note the claims researchers make in neuromarketing experiments, more understanding is needed to truly understand the brain mechanisms responding to stimuli – the correlative learnings we have do not necessarily teach us real causative properties of “hidden” preferences. For the goals of this paper, this section will instead broadly focus on the popular neuroscientific tools used in the neuromarketing field (Kottier, 2014).
The two main neuroscientific methods used in neuromarketing are functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). We will explain and compare each of these methods below.
Functional magnetic resonance imaging (fMRI)¶
When there is neural activity in a specific area of the brain, there is an increase in the level of oxygenation in the blood in that area of the brain. Thus, identifying regions of increased blood oxygen indicates activity in the brain in response to a stimulus. fMRI is able to illustrate, with high spatial resolution, an accurate depiction of an activated brain region. This is helpful in terms of neuromarketing to identify brain areas that are being activated in response to a product (Kottier, 2014), as researchers can examine and correlate the areas of the brain to a stimulus.
Electroencephalography (EEG)¶
While the fMRI is advantageous because of its ability to clearly display activated brain regions, EEG is special in regards to its precise timing in capturing electrical signals in the brain. Thus, EEG has a high temporal resolution, but low spatial resolution. In the field of neuromarketing, EEG can be used to discern when a person is responding to a product due to the electrical signals firing and the EEG capturing those signals immediately (Kottier, 2014)
What areas of the brain are important to understand for neuromarketing?**¶
An exciting advantage with the emergence of neuromarketing is using neuroimaging data such as fMRI and EEG to more accurately pinpoint preferences of consumers. But where in the brain do researchers study?
Neuromarketing relies heavily on the neuroscientific research understanding the basic brain mechanisms that illustrate humans’ preferences, which is part of a larger research around value-based decision making. Research has highlighted the ventromedial prefrontal cortex (vmPFC) and ventral striatum as areas that consistently seem to predict people’s preferences (Glimcher, 2013, p. 373). In the next section of this chapter, a few experiments within the neuromarketing field will be described that illustrate how measuring activity in these two brain regions leads to predictions about people’s values on goods.
Use cases¶
As stated in the methods section, neuromarketing gleans neuroscientific insights to learn how consumers react and feel towards products based on neuroimaging reflecting activity in certain brain areas. In this section of the chapter, various experiments will be discussed to provide a better glimpse at the types of research conducted in the field of neuromarketing.
To begin, a seminal paper that sparked more research in neuromarketing is a study that examines the neural responses underlying behavioral preferences for drinks. In this study, McClure et al. examined the preferences for Coca Cola versus Pepsi in a blind test, while also probing the influence of brands on behavioral preference for a product. Using Coca Cola and Pepsi in this study is an interesting, unique choice because these two brands actually have similar chemicals incorporated to make their products, however, people have strong, explicit preferences for one of the brands over the other. Therefore, the researchers were curious to examine how exactly people neurally respond to these products when they are not aware of what brand they are drinking versus when they are aware. In the study, participants were lying in a fMRI scanner, drinking Coca Cola or Pepsi (McClure et al., 2004).
The results from these two experiments suggest two, independent brain areas involved in producing preferences. From the blind test, the ventromedial prefrontal cortex (vmPFC) activity indicated participants’ preferences for either Coca Cola or Pepsi. This finding reaffirms the method of tracking activity in the vmPFC to determine people’s preference for specific products. However, examining only sensory information may not be enough to determine a person’s preference. Cultural information has been found to be an influence on one’s preference. Thus, the second experiment tested the influence of Coca Cola’s brand in determining people’s behavior. In result, McClure et al. found that brand knowledge, in this case the Coca Cola brand, biased preference decisions, which was reflected in brain activity in the hippocampus, dorsolateral prefrontal cortex (dlPFC), and midrain. These three brain areas seem to be separate from the vmPFC activity, since vmPFC activity was found to be unaffected by the brand knowledge (McClure et al., 2004). In summary, this paper identified distinct neural responses to sensory and culture information when examining behavioral preferences for Coca Cola versus Pepsi soda.
Another study worth describing sought to identify what kinds of neurophysiological measures predict the success of advertisements. While Venkatraman et al. review physiological measures such as eye tracking, this chapter will focus on the comparisons Venkatraman et al. made between fMRI and traditional measures used in advertising studies. The authors specifically assessed certain measures that have been known to relate to high-level constructs commonly studied in advertising research. These main constructs are attention, affect, memory and desirability. The study consisted of assessing participants’ reactions to 30-second television advertisements. One goal of the study was to identify regions in the brain that reflect key traditional advertising measures of liking, purchase intent, and recognition (Venkatraman et al., 2014).
A main result from the study found activity in the dlPFC and vmPFC reflecting the liking measure. This finding is consistent with other studies that argue liking represents both cognitive and affective processes, which respectively is associated with activity in the dlPFC and vmPFC brain regions. A broader takeaway from this finding is that liking, in this case an advertisement, produced activations in the dlPFC, and in result, the researchers are making claims that liking is associated with brain areas that involve cognitive processes. When identifying brain regions that tracked recognition, the hippocampus had higher activitations. Because the hippocampus is strongly associated with memory, the researchers in this experiment infer that the signals from the hippocampus may relate to a higher chance of remembering the stimulus, the advertisement, at a later test. While this is the claim made in the paper, a caveat is that inferring brain signals from a stimulus requires further investigations before making strong conclusions.
When comparing the effects of traditional and neurophysiological methods, the researchers used a dependent variable of advertisement elasticity, which roughly measures the effectiveness of an advertisement on influencing a percent change in sales. An important note the researchers found is that traditional measures explain most of the variation in advertisement elasticity as these methods produced 72% of the adjusted R-squared variable in the regressions (Venkatraman et al., 2014, p. 447). Therefore, this finding reinforces the argument in this chapter of neurophysiological methods not replacing traditional methods, but instead complimenting them. When controlling for the traditional measures, researchers found fMRI a significant predictor of advertisement elasticity as roughly 85% of the variation is explained by this method (p. 448). Additionally, researchers suggest that measures such as EEG and eye tracking could still be useful in explaining the variance of advertisement elasticity. In general, this paper and others support the future of neuromarketing consisting of neurophysiological measures complementing traditional measures in order to glean the best predictors to attract consumers and convert them into buying a product (Venkatraman et al., 2014).
Ethical and cultural implications¶
The onset of neuromarketing both as a research tool and a tool employed in industry often brings up strong ethical concerns and cultural implications.
One of the primary fears of neuromarketing is that of manipulation and free will. Billions of dollars are spent on marketing every year: dedicated efforts to figure out how to get consumers to purchase goods. There is increasing awareness of the surveillance and potentially manipulative processes that go behind commercial marketing. We can see clear emotional feelings of consumers such as a targeted ad feeling too intimate or “potentially dangerous”, and the opposite where one feels not seen (e. g. being sent an ad that applies to a demographic unlike yourself) (Ruckenstein, 2019). These sorts of feelings are likely the root of the gut-reaction aversion to the idea of neuromarketing; if one can understand what’s going on in my brain and how to affect it, perhaps to the effect of buying something, that feels scary or unethical. However, it is important to note that marketing research and practices have understood ways to manipulate and coerce consumers to buy products long before neuromarketing. These harmful possible effects, manipulation, or collateral damages are from marketing and commercial practices in general, not because of the onset of adding neuroscience to the mix. Neuromarketing provides a more acute and holistic lens into how these marketing practices function in relation to parts of the brain.
In the concerns of manipulation with regards to marketing and neuromarketing, the idea of “Dark Patterns” (DP) is often mentioned. One might define DP as “user interfaces that trick the users into doing something they did not mean to do” (Di Geronimo 2020). Although this concept is more heavily used in the context of design, user experience, and human-computer interaction, neuromarketing findings can influence practices in the fields thereof. For example, e-commerce websites will use countdowns and limited offers to coerce users into buying products (Di Geronimo 2020). The end-applications of DP are not limited to commerce, but also games, social media, news, and more.
Murphy et. al. (2008) suggests that the concerns of neuromarketing lie in two categories: “(1) protection of various parties who may be harmed or exploited by neuromarketing and (2) protection of consumer autonomy.” Marketing and neuromarketing may be employed for manipulative, exploitative, or invasive purposes. Although forms of neuromarketing are perhaps being employed by bad-actors, research in the area allows us to develop better understandings of people’s interactions with marketing stimuli, and thus provides ways of knowing what is possible, what the effects are, and how to combat dark patterns and manipulative practices better. Understanding a potentially manipulative practice, like a countdown timer on an e-commerce website (Di Geronimo, 2020), allows us to combat or regulate the employment of it in practice. This is especially helpful in that the public does not have a solid lens into the inner-workings of private companies’ marketing and neuromarketing efforts – we as consumers are almost always only at the receiving/consuming (not creating) end of marketing stimuli.
There is also the notion that marketing applies to more than just large companies marketing products to the public. With the new paradigm of social media and influencer culture, where it is increasingly understood that virtually anyone is or can have an influence on how you think, purchase, or operate, even this consumer-focused lens of marketing is nearly universal. Although something like an fMRI is expensive for a solopreneur to use to market their online course or social media presence, the better understanding we have in general across neuromarketing can aid in informing, regulating, and ensuring neurological safety across all forms of marketing.
Conclusions and future directions¶
Although many important findings have been discovered, the field of neuromarketing is still in early days. Measurements like fMRI and EEG take precedence in many neuromarketing research endeavors. Many modern approaches to developing our understanding of neurological behavior with respect to marketing stimuli additionally tend towards a multi-faceted tracking approach. It is likely we will see more studies where understanding of consumer behavior is interpreted through a combination of neurophysiological metrics (brain response, heart rate variability, and eye tracking) (Guixeres 2017). Although neuromarketing has been defined as being scoped to neuroscientific measures like brain response, it might be the case that behaviors may best be understood through a multi-faceted approach. Just as Duque-Hurtado et al. (2020) wrote, it is apparent that “the objective of neuroscience applied to marketing is not to replace traditional methods but rather to complement them.”
Numerous more recent studies have begun to employ machine learning applications to both the recognition and prediction of patterns (Guixeres 2017) (Hossain 2019). The use of AI/ML approaches to understand and mobilize findings has emerged over the past few years as an important subset of neuromarketing research, likely due to increased access to and creation of applicable data and computational resources.
Although we have not yet seen much neuromarketing research directly in upcoming technologies like audio-based media platforms (podcasts, Clubhouse, etc.), augmented reality, virtual reality, and gaming, we are aware that marketing – and thereby, neuromarketing – can apply to all of the above. We are already seeing some research being done in the design of things like passive brain-computer interface applications (Park, 2020). In the coming years, as these other technologies reach higher popularity, that may not have had as much historical research done, there will be an increasing need to understand how the plethora of new marketing stimuli and formats function with people. Even though observing new platforms is needed, just as said in the ethical considerations above, there is still an enormous amount of research needed to understand how existing and historical marketing practices/behaviors/stimuli function or functioned. These motivations go hand-in-hand with the development of new technologies, approaches, and analyses.
In summary, the future of neuromarketing looks increasingly multi-faceted and multi-disciplinary. As technologies improve, more granular, accurate, and informed readings of brain measurements to the effects of fMRI or EEG seem likely to be a core component of the field, but the integration with AI/ML, physiological response measurement, human-computer interaction – and more – provide an exciting frontier for expansive investigation and learnings.
References¶
Di Geronimo, Linda, et al. “UI Dark Patterns and Where to Find Them: A Study on Mobile Applications and User Perception.” Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, ACM, 2020, pp. 1–14. DOI.org (Crossref), doi:10.1145/3313831.3376600.
Duque-Hurtado, P., Samboni-Rodriguez, V., Castro-Garcia, M., Montoya-Restrepo, L. A., & Montoya-Restrepo, I. A. (2020). Neuromarketing: Its current status and research perspectives. Estudios Gerenciales, 525–539. https://doi.org/10.18046/j.estger.2020.157.3890
Kottier, W. G. (2014). The added value of neuromarketing tools in the area of marketing research. 4 IBA Bachelor Thesis Conference. Published. https://essay.utwente.nl/66222/1/Kottier_BA_MB.pdf
Glimcher, P. W. (2013). Value-Based Decision Making. In Neuroeconomics: Decision Making and the Brain: Second Edition (pp. 373-391). Elsevier Inc.. https://doi.org/10.1016/B978-0-12-416008-8.00020-6
Guixeres, J., Bigné, E., Ausín Azofra, J. M., Alcañiz Raya, M., Colomer Granero, A., Fuentes Hurtado, F., & Naranjo Ornedo, V. (2017a). Consumer neuroscience-based metrics predict recall, liking and viewing rates in online advertising. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.01808
Hossain, M. S., & Muhammad, G. (2019). Emotion recognition using deep learning approach from audio–visual emotional big data. Information Fusion, 49, 69–78. https://doi.org/10.1016/j.inffus.2018.09.008
McClure, S. M., Li, J., Tomlin, D., Cypert, K. S., Montague, L. M., & Montague, P. (2004). Neural Correlates of Behavioral Preference for Culturally Familiar Drinks. Neuron, 44(2), 379–387. https://doi.org/10.1016/j.neuron.2004.09.019
Murphy, E. R., Illes, J., & Reiner, P. B. (2008). Neuroethics of neuromarketing. Journal of Consumer Behaviour, 7(4–5), 293–302. https://doi.org/10.1002/cb.252
Ruckenstein, M., & Granroth, J. (2020). Algorithms, advertising and the intimacy of surveillance. Journal of Cultural Economy, 13(1), 12–24. https://doi.org/10.1080/17530350.2019.1574866
Park, S., Han, C.-H., & Im, C.-H. (2020). Design of wearable eeg devices specialized for passive brain–computer interface applications. Sensors, 20(16), 4572. https://doi.org/10.3390/s20164572
Venkatraman, V., Dimoka, A., Pavlou, P. A., Vo, K., Hampton, W., Bollinger, B. K., Hershfield, H., Ishihara, M., & Winer, R. S. (2014). Predicting Advertising Success Beyond Traditional Measures: New Insights from Neurophysiological Methods and Market Response Modeling. SSRN Electronic Journal. Published. https://doi.org/10.2139/ssrn.2498095