Abstract
Neuromarketing is implementing itself slowly into market research without the academic acknowledgment. This phenomena seems to be paradox, since researchers are more and more aware of the significant effect emotions have on consumers and neuroscience has already been proven to be a complementary data source in certain research contexts. One recently published paper from Temple University in particular (Dimoka 2015) verified that neuroscience – within limitations – contains significant effectiveness in market research in regards to advertisement success and is providing new insight and data for further academic research. This paper urges academic marketing research to adapt the complex technique of neuroscience and cut back the criticism towards it. Most criticism is directed to marketing pioneers claiming neuromarketing can predict purchase sale or consumption, which is not the case. Neuromarketing is rather a very complex and difficult observational research method that analyzes emotional processing to determine the unconscious variability in behavioral research, thus a very significant and complementing tool to the more rational traditional market research.
Introduction
Marketing research has been developing rapidly over the last century. The developments in the 70s included hereby a usage of rather cognitive psychological research techniques as suppose to a more sociological and cultural perspective in the 80s and 90s. Researchers of the last decades found out that the conscious and rational buying-decision is seldom the trigger for an actual purchase. Emotions and dependencies towards certain feelings and relationships are the major reason why people make decision and act unpredictable sometimes. Researchers have been considering this and trying to monitor the subconscious reactions of consumers to understand certain phenomena of interest – this method is also known as neuromarketing. Interestingly, although the first studies has been conducted in the early 90s (Price 2012), the method seems to be hardly criticized and hasn’t been adopted into market research literature yet.
The Understanding of Decision-Making
Rational Thinking vs. Emotions and Feelings
The suggestions of academics and experts that rational thinking is the major decision-maker for consumer has been steering advertisement for the most part of the 20s century. But this suggestion has been reformed. A phenomenon discovered by Hoch & Loewenstein (1991) referred to as “time inconsistency” – spontaneously changing your first intention, resulting in being inconsistent over time – helps us to understand the division of the brain into two major regions. First, there is the rational prefrontal cortex, which makes the logical decision-maker to invest for a “future reward” and second, the more primitive limbic system, which stands for the “immediate gratification” (Coy 2005) and makes you spent all your savings on a spontaneous Vegas trip.
Nowadays, it is scientifically proven that emotions are the main decision-maker for most intentions. Emotional attachment in contrast to rational logic is the reason why people buy Coca Cola although they prefer the taste of Pepsi (Fugate 2008; Haig 2005), smoke although every smoker knows that it negatively effects ones health (Lindstrom 2008; Petersa et al. 2012) and believe that an expensive wine – even when demolished with acid – tastes better than a decent cheap one (Perrachione & Perrachione; Plassmann et al. 2008; Garcia & Saad, 2008; Hubert & Kenning, 2008). The list goes on. All these decisions seem to be made by the limbic system, which is the autonomic control terminal of the brain for emotions (Blessing 1997), behavior, long-term memory and epinephrine flow (McClue et al. 2004; Morgane et al. 2005).
This thesis has been supported and verified by Antonio Damasio (Bechara & Damasio 2005; Damasio 1996) in the elaboration of his somatic marker hypothesis. His hypothesis claims that rational decision-making always depends on emotional processing, due to the phenomenology of past decisions and individual tastes. The gradient of emotionality is, however, depending on the decision. For example, the higher the risk of a decision, the more logical and cognitive is the process of deciding (Gonzalez et al. 2005).
The Neurophysiological Reaction to Emotions
A negative example in market research shows the disastrous effect of ignoring emotions in marketing. Coca Cola conducted 1985 a study of 200.000 participants to change their original recipe in favor of making an objective better tasting soda product than competitor Pepsi (Haig 2005). Even though participants preferred the prototype recipe 8% more than Pepsi’s and 20% more than the original one, consumers rejected the “new” Coke on the market. The company president Donald Keogh concluded:
“The simple fact is that all the time and money and skill poured into consumer research on the new Coca-Cola could not measure or reveal the deep and abiding emotional attachment to the original Coca-Cola felt by so many people." (Haig 2005:p. 12)
A lot of research has been done on this aspect since the mid 80’s and researchers are aware that a buying-decision of a product cannot be broken down to only their characteristics, cost or product’s advertising message, but rather to the intuitional relation with the product’s brand and how consumers envision the added value of the product to their lives (Hammou et al. 2013). Furthermore, it supports Fugate’s statement (2007) to shift the focus from product development towards brand and image development.
Many scholar studies have acknowledged the connection of a dynamic relationship between changes in emotional states and changes in neurophysiology (DeYoung et al. 2010; Gazzaniga et al. 2009; Glimcher, 2009; Langleben et al. 2009; Tamietto & de Gelder 2010). People build up dependencies to the chemical changes in their brains’ created by emotions, which are similar to hormone floods, and want to sustain these reactions. Therefore, it is essential for marketers to investigate the emotional engagement of their consumers to avoid further “disastrous” effects.
The Neuromarketing Approach
Neuromarketing as Safety-Belt
The emotional effects of advertisements on consumers can be obtained and rehashed for analyzing purposes through neurological imaging of the brain. The most frequent and insightful method is the usage of a functional magnetic resonance imaging (fMRI). By dividing the brain into separate regions, whereas each region represents a distinctive impulse of emotional processing, the machine analyses the oxygen concentration in these regions while the analyzed object is preforming a cognitive task (Ogawa et al. 1990). A high oxygen concentration indicates a more active brain region. Hereby, neuroimaging can draw, for example, conclusions on consumers’ buying behavior by determine product preferences and price distinctions (Knutson et al. 2007; Hammou 2013; Lee at al. 2006), negotiating behavior (Sanfey et al. 2003; Lee at al. 2006), but moreover it can help companies to design, develop and prototype products and advertisements (Ariely & Berns 2010; Fugate 2007); further, prevent advertisement and branding failures.
The secret around the hype towards neuromarketing is the recognition that neuroimaging can reveal hidden information about the consumer. Such hidden information is usually controversial to existing marketing paradigm and thus extraordinary helpful in market research. Moreover, neuroscience is not only able to gain further insight to consumer behavior; it is also able to do this in real-time (Hubert & Kenning 2008; Lee et al. 2007; Fugate 2007; Ohme & Matukin 2012), providing research the ability to alter the determined elements of their stimuli to satisfy their study purpose. For example, Oxford University researchers found out – by using real-time neuroscience –, what people hear and smell has a bigger emotional impact than what they see (Lindstrom 2008). In addition, although visual advertisement seems to be the major-used channel to consumers, high visual appealing advertisement with positive face expressions in contrast to text-based advertisement with neutral face expression has been just slightly more memorable (Kenning et al. 2007). Concluding, that visual stimuli are not highly engaging the limbic system and emotional processing.
Taken into consideration that information in the brain is processed consistent and stereotypical (Hasson et al. 2004), an analysis of brain processes should determine consumers’ reactions and therefore behavior to an extent, that emotional processing in advertisements (Fugate 2007) and perceived product design (Lindstrom 2008; Berns & Moore 2012) is being assured or even improved.
Criteria and Limitations of Neuromarketing
Neuroimaging in science and practiced marketing does conceal decent applications but with application comes limitation. With increasing stimulus complexity, simple interpretations of brain activation will become more difficult (Ariely & Berns 2010) and limit the effectiveness of the analysis (Kenning et al. 2007). Although the complex interactions between brain areas are still being researched, the measurements are manageable by developing specific adjustments. In a Coke and Pepsi study the participants were laying inside an fMRI scanner embedded with cooled plastic tubes and plastic mouthpieces with a software-controlled pump to assure the effectiveness of the scan (McClure et al. 2004b). Nevertheless, the process of scanning through fMRI requires participants to remain immobile for 45 minutes to an hour and a half, which may alter the analysis due to discomfort or movement during the scan (Riedl et al. 2010; Maxwell 2008). Falk et al. (2011), for example, had to use foam paddings to fix the head position to ensure better scan results. The complexity points out that the usage of neuroscience requires experts in the field of neuropsychology or at least neuroscientific techniques (Kenning et al. 2007); hence, making the analysis more difficult than traditional questionnaires.
The cost of neuroimaging is another big limitation. Although hidden information about consumer behavior would outweigh the actual cost of a big marketing campaign (Ariely & Berns 2010), a typical fMRI scanner costs according to Kenning et al. (2007) about one to two million euros respectively 1.5 to three million US dollars (Ariely & Berns 2010). With annual cost of US$100.000-$300.000 and US$500 per hour (Ariely & Berns 2010), neuroimaging is made inaccessible for smaller marketing firms and explains the rise of neuromarketing consultancies.
Neuroscientific data needs to be conducted structuralized and obtained through a framework, furthermore it needs to go through necessary adjustments to prevent errors and misguidance of the analyzed data. Vechiatto et al. (2010) observed that more than a third of the published studies didn’t use essential methodology to correct the data. This is not really surprising, since this paper already stated difficulties in the data collection. Furthermore, not only the fixation, but also gender (Garcia & Saad 2008), mental health (Dimoka et al. 2015), current physical ability (Falk et al. 2011) and biases of participants (Ariely & Berns 2010; Fugate 2007) needs to be checked to ensure the significance of data. Collected data is even criticized further, by claiming that single-region correlations in the brain are not significant enough for predictions of consumptions (Ariely & Berns 2010; Fugate 2007) or don’t explain the origin of discrepancies between different measures (McConnon & Stead 2007).
To complement traditional research properly neuroscience needs to be classified as qualitative or quantitative. Unfortunately, this is not possible because the criteria for neuroscience are being found in both approaches. The data provided by neuroscience are qualitative pictures measured without defined purpose, but analyzed with numbers and statistically quantitative methods in a structured laboratory environment. Therefore, it uses mostly a quantitative approach to determine explorative and qualitative data about feelings, perceptions, decision-making processes (Seller 1998), attitudes and motivations (McDaniel & Gates 2013).
For neuromarketing to have an actual application and to be a “legitimized academic field”, it needs to have a working framework consistent of behavior models, which will give guidance on how to interpret the statistical neuroimaging data (Fugate 2007). Since neuroscience is generally being defined as complementary to traditional research methods, the working framework can only be fully established if neuroscience is being accepted as a limited market research method.
Neuromarketing in Comparison to Traditional Research Methods
Currently, there are six major categories of data collection methods. These are tests, questionnaires, interviews, focus groups, observation and constructed and secondary or existing data created by research participants (Johnson & Christensen 2014:225). Since neuroimaging seems to make an observation of the brain regions and doesn’t necessarily engage the researcher in the data collection- process or even require the participants to act, neuroscience could be defined as an observational research method. Johnson & Christensen (2014:236) described observational as: “[...] watching [of] behavioral patterns of people in certain situations to obtain information about the phenomenon of interest”. Further research defined observations as more cost and time consuming, but moreover as supplement to improve data from questionnaires or other common research methods (Chisnall 1997; Aaker et al. 2007; Churchill & Iacobucci 2012). Only one element of neuroscience does not fit in observational research definitions, which is the limitation of observation methods to provide information about motives, attitudes, intentions (Aaker et al. 2007) or feelings (McDaniel & Gates 2013).
Using Churchill & Iacobuccis’ (2010) Degree-Model for observations, neuroscience is conducted contrived in a laboratory setting with a mechanical instrument but is being further defined strongly dependent on the used methodology – although it is mostly an unstructured and exploratory analysis, where the research is mostly disguised. As mentioned earlier, on the one hand neuroscience is usually a quantitative observation with qualitative aspects and might be difficult to include in a pure qualitative or quantitative analysis, but on the other hand Koller (2008) and Johnson & Christensen (2014) suggested a combination of qualitative and quantitative approaches in market research to optimize the insight on the more and more complex and connected consumer.
The “New” Market Research
Although neuroscience is commonly considered – with certain limitations – to be more valuable than focus groups and in-depth interviews (Lee et al. 2007; Murphy et al. 2008; Butler 2008; Hubert & Kenning 2008; Eser et al. 2011; Fugate 2007; Fugate 2008 and Page 2012), it has not been adopted as a state-of-the-art technique in market research as a way to predict consumer behavior. This has been verified by the research conducted to this paper. All marketing books with “market research” in the title in the whole offline library of the SDU combined mentioned neuromarketing or the use of neuroscience only on two pages; by just giving a “snippet” of the development and, furthermore, only one book added neuroscience to its index for quick access (Churchill & Iacobucci 2010; Fahy & Jobber 2012; McDaniel & Gates 2013; Bradley 2013; Aaker et al. 2007; Chisnall 1997). To be absolute sure, books that had been outdated had been updated to their latest available edition through SDU’s library summon without any improvement of the content implicating no progress.
Even though neuroscience might have limitations, predicting behavior is seldom without any limitations. Self reports and focus groups – the most frequently used research method – suffer from limitations to reveal actual reasons for behavioral change due to social desirability effects (Booth- Kewley et al. 2007; Edwards 1953; Hubert & Kenning 2008), the fact that people do not consciously know about the influencing factors (Nisbert & Wilson 1977), or subjective opinions, which aren’t altering the actual behavior (Wilson & Schooler 1991). Armitage & Conner (2001) claim that three quarters of the statistical variability in people’s behavior is unexplained, while some researchers might think the unexplained variability is even higher (Webb & Sheeran 2006). By looking at the active brain regions in real-time, neuroimaging is already providing a complementary data source, simply to the fact that the observer is in charge and the participants have no influence over the collected data (Butler 2008; Hubert & Kenning 2008; Fugate 2007). As explained earlier, this conception of revealing hidden data is commonly shared with other researchers. Micu and Plummer (2010) summarize this statement by defining self-reported measures as rather subjective and incomplete because they only capture conscious decision and declared opinions. Neuroscience as a complementary observation method can overcome these limitation.
A few studies regarding substance usage (Brewer et al. 2008; Kosten et al. 2007; Paulus et al. 2005; Falk et al. 2011) already established the connection between measurable neuronal activity and behavioral change in regards to substance usage. These studies – beside many others with similar findings – help companies to conclude hidden information by analyzing consumers’ attention, emotion, memory and personal implication (Hammou et al. 2013). Thus, defining neuroscience not only effective in health, economy and entertainment sectors, but every observant study.
In despite of all the studies this paper investigated, the most interesting study has been the long- term effect of neuroscience on advertisement elasticity (Dimoka et al. 2015) – also referred to as advertisement success. Dimoka et al. (2015:444) described it with “[...] the percentage change in sales due to a 1% change in advertising measure being utilized [...] and has been used expensively in the literature”. Five companies were asked to provide market data from the past three to six years (sales figures and gross rating points6), which has been compared to the data collected from different market research and neuroscience methods. The study suggests that especially fMRI gives access to additional 5% of the variation. Although this variation is significantly lower than other studies claim, the used methodology has been more complex and further calculations for error-prevention have been made. Moreover, Dimoka et al. (2015) tried to investigate the full potential of self-reports in advertisement by analyzing ad execution (liking, excitability, recall) and the product featured the ad (e.g. attitudes, purchase intend). Furthermore, they used a slightly altered AIDA (attention, interest, desire and action) model7, which is the general procedure of an advertising process (Strong 1925) and has been used with complementary methods (Barry & Howard 1990) to investigate or develop advertisement success (Haley & Baldinger 2000; Morwitz et al. 2007; Walker & Dubitsky 1994) for decades, to compare self-reports result to neuroscience. This, so the researchers, provides a broad classification of common traditional measurements and can define advertisement success. Dimoka and her team (2015) claim that neuroscience holds significant advantages over self-reports by being able to separate between endogenous (“which aspect of the advertisement is selected and processed”) and exogenous attention (“which features of the stimulus attract attention and processing”)(2015:438) and collect higher quality data about valance and arousal, due to the real time measurements. Furthermore, the real time measurements also provide a distinction between the consumers’ encoding and retrieval of advertisements while the dopamine and reward-related brain activities can determine a more emotional and therefore accurate prediction of desirability. This verifies that consumer neuroscience holds further insights into all attributes of advertisement success.
Conclusion
This paper explained the position of emotions in today’s advertisement by highlighting the significant effect emotional stimuli have on people. Not only is emotional processing more memorable than rational decisions, it is also the reason for unpredictable behavior. Since society nowadays seems to be very versatile, companies (and researchers) need to find new data-collecting methods to manage and understand phenomenon in markets and reduce their dependency on traditional market research like focus groups and self-reports. It seems that research is drifting towards a neurological approach in market research, due to the fact that measurements with fMRI scanners can allocate emotions in the brain. But fMRI has been criticized as a time and money consuming and rather complex method, since the procedure is depended on aligned scan settings and data conditioning. Nevertheless, criticism and limitations of neuroscience are not stronger than with any other traditional research method and many studies proved neuroscience to be an efficient market research technique – especially as complementary method to traditional approaches. Thus, this paper concludes that the question “why neuroscience hasn’t been adopted into the literature of market research” can only be answered in two ways.
First, results of neuroscience studies seem to differ. Despite its efficacy and due to its complexity, neuroscience does not always have the same output and significance on the collected data. For example, motivational focused studies about substance abuse, taste and entertainment with a less rational and functional framework seem to have a higher significance in comparison to self-reports. Second, neuroscience is hard to define with conventional research methods since its criteria are dependent on the method neuroscience researchers are using. It is a mechanical quantitative observational method with qualitative aspects, that can be structured or unstructured and disguised or undisguised; thus, making it difficult for many researchers to use in their existing research framework.
This paper urges market research literature to close the gap between marketing practioneers and researchers by accepting neuromarketing as what it is: an observational method, which can improve data-collection and advertisement success significantly. It is far away from being a tool to ensure product sales or manipulate consumers’ minds, but rather – like any other observational method – is best used as a complementary method with other more “traditional” methods, and moreover is strongly depended on the research context. Market research has become more complex and needs a more complex research method. Given that conscious and subconscious methods explain independent limitations and variability’s in behavior change, researchers should be more flexible in their approaches and step out of conventional paradigms for the greater good of a better insight to behavioral research.
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