What is neuromarketing? The best definition related to the group of methodologies and research tool can be provided with the words of Professor Ale Smidts, who coined the term more than 20 years ago. Prof. Smidts defines neuromarketing as:” the study of the cerebral mechanism to understand the consumer’s behavior in order to improve the marketing strategies.”
In simpler words, neuromarketing can help to understand why consumers behave in a certain manner when they are in the sight of a decision, whether online or in front of a store shelf, or they are exposed to advertising.
The reason behind the constant increase in the implementation of such tools has one fundamental reason: the inability of traditional marketing research techniques, such as focus groups, questionnaires and interviews, to dig deeper into the most unconscious customer needs and reasons why they make the decisions they make. Being able to draw from such insight can let companies know which messages really resonate into the customer mind, improve the efficiency of the prototyping phase and benefit from more and more fine and hidden intuitions.
The study was designed to investigate in a quantitative way how the mind would process the information given and the resulting answer once the respondents would have been presented with a choice. The study focused on the understanding of cognitive bias, that is the group of cognitive distortions that lead to decisions that appear as irrational.
The sample consists of 202 people, of which 95 are men and 107 are women, the mean age is 37 years old and the mode is 24 years old, and 55% has at least a bachelor degree.
One of the questions inside the study asked to the respondents was how much they would have been willing to pay the ticket to take part to two different lotteries. The first was the one less risky and with an easy to compute expected value, while the second was riskier and harder to estimate. Despite the different level of risk, both lotteries had expected value of around €8. The goal of this part of the study was to understand the willingness to pay of each lottery, how do they compare to one another and if certain groups would behave differently from others in each lottery.
Before jumping to the results, it is necessary to describe the model developed in 1979 by Kahneman e Tversky, the Prospect Theory, in which the authors outline the theoretical model involving the decision-making process that induces the individuals to make suboptimal decisions. The theory is based on two main functions:
The value function: how value is perceived when we incur into a potential gain or a loss. As shown in the image below, the curve is steeper on the bottom left side than in the top right corner. This means that the “pain” experienced by a loss is bigger that the “joy” from a symmetrical gain and are both marginally decreasing.
The probability function that shows how events that are very unlikely to happen are overestimated, while very likely events tend to be underestimated.
Coming to the results of the 1st lottery, the respondents are willing to pay on average €4,31 to take part, with a mode of €5 (around 21% of the sample). The standard deviation is quite high due to an uneven distribution in the answers. Furthermore, the large parts of respondents (92%) would be willing to take part to the lottery only if the price of the ticket is below its expected value.
As for the second lottery, the average price that participants are willing to pay is €3.87 and the mode is €1. The standard deviation is also high and the shape of the distribution is more skewed towards the right compared to the first one. As can be easily deduced from the graph, also in this case the large majority, equal to 90.6% of the sample, is not willing to pay more for the ticket than its expected value.
What Kahneman and Tversky theorized finds confirmation in the research results, as the vast majority of participants declare that they would buy the ticket only if the price is well below the expected value, especially in the first lottery, which is in line with what was mentioned above according to the value function. However, the probability function previously shown could justify the phenomenon such that in the second lottery, the percentage of people willing to pay more than €8 is slightly higher than in the first lottery, as some individuals in the sample, even when faced with a greater risk, are willing to spend more because, perceptually speaking, they overestimate their chances of winning.
Moving on to the bivariate analyses, in which the results of the lotteries were cross-referenced with the descriptive characteristics of the sample, there is not enough evidence of a relationship between the price at which one is willing to pay the ticket and the level of education, while there appears to be a significant difference with the variable "generation" and "gender". In particular for gender, if we evaluate the compare means test to determine if it is possible to reject the null hypothesis, we manage to define as statistically significant only the gender difference in lottery 1, while in lottery 2, although there seems to be an apparent difference, there is not enough evidence to make such claim. This contrasts with the hypothesis that the cause of the difference is the higher average risk appetite of men since, as the risk increases in the second lottery, the gender gap would be expected to increase and the test to be more significant.
Finally, the ANOVA was carried out, with the aim of evaluating the impact of the independent variables. In particular, the case in which education level and gender are independent variables is particularly interesting:
As can be seen from the graph, regardless of education level, men have a very similar willingness to pay for the ticket (€5,33 men without higher education vs €4,73 men with higher education), while the same statement cannot be extended to the female counterparts. In fact, women with a university degree have an ability to pay that is very similar to that of their male counterpart, while there is a very marked difference with the female counterparts who, have not been to university (€4,50 vs €2,89). In the end, among those without university education, the gender variable seem to be quite relevant in the willingness to pay as men without university education would pay 85% more than women without a university education (€5,33 vs €2,89). This gender gap, as mentioned before, does not occur in individuals with higher education.
The managerial implications that can be drawn from the lottery results are varied and can be applied to different marketing fields:
for example, since that, on average, individuals attribute more value to events in which the reward is smaller, but more certain, the types of promotions that respect such criterion should be encouraged. A classic example is company loyalty programs, such as the one presented by Vodafone, called Vodafone Happy, in which, in exchange for a certain number of points accumulated over time by being a customer, it’s possible to redeem a discount or participate in lotteries to win cars, high-tech gadgets and more. As discussed with people involved in the design of the program, overall, the favorite products of the telecom company consumers were the €5 discounts that could be used on companies affiliated with the program for the reason just discussed.
However, in the study it was also noted that not all groups attribute value in the same way. For example, men belonging to generation Z, who were found to be those with the highest willingness to pay and risk tolerance, perceive the value of an offer in a completely different way compared to other groups of consumers.
Assuming, for example, that I work for an online brokerage platform, I could encourage this segment to subscribe to the platform by communicating that, once they sign up, they have the chance to win shares/cryptocurrency worth up to a certain amount as shown in the ad below.
However, this type of communication would not have the same results for in a female or older audience, who could however be drawn by messages linked to savings on commissions for financial transactions or convey content that emphasizes the low volatility and security of certain financial instruments.
Comments