In this article, we will try to give a detailed overview of the main and most commonly used technologies and methods in Neuromarketing, in both corporate and academic circles. To achieve this, we analyzed the most cited papers in the literature and explored the most proposed tools by marketing professionals and firms.
Powerful functional neuroimaging technologies have been introduced in the current period as a result of decades of work by scientists and engineers knowledgeable in and interested in neurotechnology. Other sources mention physiological signal and biometric tools like eye tracking, skin conductance response/EDA, heart rate, respiratory rate, pupil dilation, and electromyography facial. (see list on the NMSBA website).
Despite the fact that fMRI has been employed in the majority of relevant, peer-reviewed academic studies, it is less likely to be used in industry due to its practical constraints. Neuroscientists test marketing messages with a variety of instruments, and factors like price, ease of use, speed, etc. can be considered when selecting the most relevant technology for the scientific and methodological requirements of a certain study project. In general, neuroscientists classify methods by temporal and geographical data acquisition resolutions. Given the quick activity of the brain (milliseconds), higher temporal resolution provides a more precise interpretation of the brain signal but generates voluminous, difficult-to-analyze data. Techniques with a low resolution, such as fMRI or PET, can overlook rapid events. On the other hand, they can record the action of a structure in the brain that is responsible for a certain function or residue if it is made up of many mechanisms and neural pathways that are responsible for different things. ( for further reading see Cerf & Garcia-Garcia, 2017, Plassmann et al., 2012).
In the sections that follow, we will provide a comprehensive review of the tools and techniques utilized by neuromarketers and then compare these tools and techniques based on their respective prices, spatial and temporal resolutions, fields of application, advantages, and limitations.
The functional magnetic resonance imaging (fMRI) technology analyzes the degree of deoxygenated hemoglobin in the brain during neuronal activity. By comparing scans taken when the brain is actively completing a task to scans taken while the brain is resting, functional magnetic resonance imaging (fMRI) can detect the presence of active systems, and It can be used to observe and analyze individual emotional responses, level of engagement, and memory recall when a consumer is exposed to various marketing stimuli (advertising, packaging, etc). As a fascinating example of the technique’s enormous potential, it was recently used to measure the brain activity of adolescents while they listened to music by relatively unknown musicians. Over the next three years, sales of the same songs were linked to how the participants’ brains reacted to the music during the first listening session. This shows that brain responses to music could be used to predict future sales. (explore the study here).
- fMRI advantages
Despite being in its infancy, fMRI appears to be a valuable and promising instrument for marketing researchers thanks to a number of advantages:
- Non invasive. This technique does not entail the administration of radioactive substances, allowing for repeated observations of the same individual.
- It has the highest spatial resolution compared to all other technologies.
- Convenient for assessing emotional responses
- fMRI drawbacks
A survey of the scientific literature reveals that an fMRI scanner has very high fixed costs in addition to being physically limiting and inconvenient, which severely restricts the generalizability and commercial implications of fMRI research.
- An MRI machine is very expensive (The costs might vary between $200,000 and $1,000,000)
- uncomfortable for the research subjects
- It is a lab-based procedure only
- Low temporal resolution
A functional MRI involves not only the skills of a qualified individual but also the utilization of a clinical or laboratory environment. Due to the technology’s low temporal precision, it is not possible to pinpoint precisely when a specific emotion was triggered; nonetheless, it is possible to assess whether an emotional response occurred. The high cost of performing an fMRI and the fact that it cannot be utilized on a large number of people are ultimately the greatest hurdles to overcome in order to employ the technique successfully.
EEG is an electrophysiological technique for monitoring and recording the electrical activity of the brain through the attachment of several electrodes to the scalp. It is the most widely utilized brain monitoring tool in the marketing sector. Generally, EEG recordings are divided into two categories for analysis: ERP (event-related potential) refers to the voltage time series recorded in reaction to a particular event, such as the beginning of a stimulus or the depressing of a button. Multiple cortical responses to the same event are averaged to provide a cleaner voltage time series that may contain components important to an issue of study, such as positive or negative voltage peaks. The second way of analysis is known as “spectral analysis” and entails evaluating the spectrum of frequencies that comprise the electrical signal.
The EEG has been employed in numerous studies examining consumer behavior, analyzing the efficacy of advertising and gauging consumers’ emotional responses to marketing stimuli.
Dmochowski et al. carried out one of the most significant EEG investigations in neuromarketing in 2014. Initially, they obtained EEG data from a small sample of individuals while they watched an episode of The Walking Dead. Then, using regression logic, they established a considerable relationship between the recorded metrics and the number of associated tweets in the general population during the episode, on the one hand, and actual viewing of the episode, on the other (as estimated by Nielsen). Subsequently, they revealed a significant association between the measurements acquired from a new, small group of participants viewing Super Bowl advertisements and the assigned within-sample ratings and population ratings of the same Super Bowl advertisements. Their research demonstrates conclusively that a measurement based on EEG data can serve as a surrogate for overall involvement with a continuous stimulation. In addition, their research indicates that scalp measures may be able to anticipate the natural behavior of vast populations.
Another study by Baldo, Parikh, Piu, and Müller from Neuromarketing Labs showed that successful and unsuccessful sales of faschion products can be predicted using EEG signals. Indeed, and compared to their questionnaire-based prediction, which was only 60% accurate, their testing method, EEG-based, was 80% accurate.
- EEG advantages
The literature generally agrees that the EEG approach offers a variety of benefits that marketers and market researchers can leverage. It is a way to run experiments with low marginal costs and few needs for support and maintenance:
- Less costly than fMRI (prices can range from 99$ to +25000$)
- Can be employed outside of laboratory settings (the new EEG devices are mobile)
- high temporal resolution (around 1 to 2 milliseconds)
- EEG drawbacks
While EEG has many useful business applications, it also has a number of serious drawbacks. Most notably, poor spatial resolution. Because the skull has a high impedance, any change in voltage caused by the brain is spread out over a large area of the scalp, making it hard to figure out how decisions are made:
- Low spatial resolution
- When it comes to measuring emotions, it is not as accurate as fMRI
Having said that, the EEG can be applied to branding by examining brainwave patterns to spot trends in the retention of particular texts or visuals associated with a given brand. Due to the high temporal resolution of the method, changes in brain activity can also be used to track attention and level of engagement in advertising.
Researchers can collect data on where people are looking by attaching an eye-tracker to the subject’s head or to a computer. Because it can be used in many different ways, eye tracking is becoming more popular in fields like neuromarketing and behavioral neuroscience. Marketers can use eye tracking to predict what will catch consumers’ attention right away. They can also use the number of blinks as a measure of how emotional the stimulus is and the size of the pupils as a measure of interest. Eye-tracking data makes it simple for marketers to evaluate projects involving product design, customer attention, shelf layout, ad formats, and more. Compared to other neuromarketing technologies, eye tracking has become popular in business because it is inexpensive, can be used in a variety of settings, and has a strong link to advertising because it can quickly and accurately figure out where customers are looking.
- Eye-tracking advantages
The attention of consumers can be monitored in different ways using this methods which has various advantages:
- Relatively inexpensive (prices can range from 100$ to 10000$)
- Simple to install
- Mobile and allowing the experiment to be conducted in the real market situation
- Eye-tracking drawbacks
- Doesn’t measure emotions
- most often requires a combination with other tools
This technology can be used in different marketing situations: it can help check the consumer’s visual attention when viewing a product through its design and packaging, it can track the number of fixations per second (fps) while a person views an advertisement; and it can track the amount of time shoppers spend looking at shelves and researching specific items.
The FACS (Facial Action Coding System) is a reference handbook for the coding of face expressions. It was created by Paul Ekmann, the best authority on the scientific study of facial emotions. The software takes pictures and/or records the user’s face and assigns codes to each of their expressions based on Ekman’s 44 Action Units (AU). One or more muscles can tighten or loosen to make an AU, and the wide range of AUs makes it possible to “detect” many different emotions.
In the modern age of digital and machine learning, marketers can base different parts of their strategy on how customers feel. This is because emotions are the result of thousands of years of evolution by the human species, which learned how to use emotions to survive, communicate, and set itself apart from other species.
- Facial coding advantages
This technique is becoming increasingly credible for analyzing diverse emotive reactions to visual stimuli thanks to various advantages:
- Inexpensive compared to other tools
- Can be used in combination with other biometric data
- Non invasive
- Simple to implement (only requires a computer, webcam, and TV to display ads)
- Facial coding drawbacks
Despite the widespread usage of this technique by market research firms, it requires ongoing advances in machine learning to overcome cultural variances in facial expressions.
Facial coding can be used in different areas of marketing research: in product testing by analyzing the consumer’s reaction to the product’s proposed features, in testing and pre-testing ads to see which ones perform best and which ones don’t, and in measuring emotional responses to brands.
Galvanic skin conductance
Galvanic skin conductance is a commonly used and approved approach in neuromarketing. This method measures the physiological response to an emotionally stimulating stimulus. It can identify neural responses that precede many emotions, including joy, sadness, fear, anger, disgust, and indifference, because of the direct relationship between the central nervous system and reactions recorded on the palms of people. Neuroeconomics and neuromarketing have recently started to use this method to study how emotions affect buying and making decisions, according to research by Walla, Brenner and Koller, for example, skin conductance can be used to reveal brand preferences.
- GSC advantages
- Inexpensive and easy to set up
- Recommended for use in combination with other techniques (eye-tracking, facial coding, EEG)
- GSC drawbacks
This technique can not determine whether the emotion in question is negative or positive. In other words, if a GSC record for a positive and negative reaction appears identical, it cannot be utilized to differentiate between the two. This technique can be used to determine the level of engagement with a brand, product, or advertisement.
Marketing departments in academic and corporate settings now have access to a wealth of tools that enable them to do brain research without personally interviewing customers. Instruments can measure brain activity in a variety of ways. Others directly analyze brain tissue, investigate residual neural activity in a large population, investigate the quantity of oxygen required to run neural circuits, or investigate residual nervous system activity. Each instrument has advantages and disadvantages. The precision of time and space can vary greatly. There are speedier and less expensive alternatives. A variety of factors influence methodology selection, including the nature of the problem to be solved, the nature of the function to be tested, the available money, and the required execution time.