Abstract
Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken response of consumers to the marketing stimuli. This article presents the very first systematic review of the technological advancements in Neuromarketing field over the last 5 years. For this purpose, authors have selected and reviewed a total of 57 relevant literatures from valid databases which directly contribute to the Neuromarketing field with basic or empirical research findings. This review finds consumer goods as the prevalent marketing stimuli used in both product and promotion forms in these selected literatures. A trend of analyzing frontal and prefrontal alpha band signals is observed among the consumer emotion recognition-based experiments, which corresponds to frontal alpha asymmetry theory. The use of electroencephalogram (EEG) is found favorable by many researchers over functional magnetic resonance imaging (fMRI) in video advertisement-based Neuromarketing experiments, apparently due to its low cost and high time resolution advantages. Physiological response measuring techniques such as eye tracking, skin conductance recording, heart rate monitoring, and facial mapping have also been found in these empirical studies exclusively or in parallel with brain recordings. Alongside traditional filtering methods, independent component analysis (ICA) was found most commonly in artifact removal from neural signal. In consumer response prediction and classification, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) have performed with the highest average accuracy among other machine learning algorithms used in these literatures. The authors hope, this review will assist the future researchers with vital information in the field of Neuromarketing for making novel contributions.
Highlights
Neuromarketing, an application of the non-invasive brain–computer interface (BCI) technology, has emerged as an interdisciplinary bridge between neuroscience and marketing that has changed the perception of marketing research
3.1 Marketing stimuli used in Neuromarketing As Neuromarketing is a focus of marketers and consumer behavior researchers, different strategies from marketing have been applied in Neuromarketing and they are being investigated for quantitative assessment from neurological data
The most used classification algorithms used in Neuromarketing over the last 5 years are Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN), Naïve Bayes, k-Nearest Neighbor (KNN) and Hidden Markov Model (HMM)
Summary
Neuromarketing, an application of the non-invasive brain–computer interface (BCI) technology, has emerged as an interdisciplinary bridge between neuroscience and marketing that has changed the perception of marketing research. With the help of brain–computer interface, the mental states of a customer, i.e., excitement, engagement, withdrawal, stress, etc., while experiencing a marketing stimuli can be captured [5] Besides these brain signal recording techniques, Neuromarketing utilizes physiological signals, i.e., eye tracking, heart rate and skin conductance measurements to gather the insight of audience’s physiological responses due to encountering stimuli. Systematic literature review from the engineering perspective with a focus on neural recording tools and interpretational methodologies used in this field is absent In this regard, our article sets its premises to answer the following questions:. We would like to explore the marketing stimuli used in Neuromarketing research articles over the last 5 years with their triggered brain regions. Interpreting the neural data with only statistical analysis has been out of scope of this paper
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