Analysis of skin conductance response during evaluation of preferences for cosmetic products

Neurophysiological approaches to exploring emotional responses to cosmetics: a systematic review of the literature

Introduction

This systematic review explores the use of neurophysiological measurements to study emotional responses to cosmetic products. The aim is to evaluate existing literature on these measurements in cosmetics, identify the main findings, highlight methodological challenges, and propose new guidelines for future research.

Method

A systematic search focusing on neurophysiological measures to determine emotions induced by different cosmetic products was carried out in accordance with PRISMA guidelines.

Results

A total of 33 articles identified with the EBSCO database met the inclusion criteria. In all, 10 different measurement tools were used in these articles to assess the emotional effects of cosmetic products.

Discussion

This review emphasizes the complexity of interactions between cosmetics and emotional responses. It underscores the importance of future research with a more holistic approach that couples several physiological measurements. Among them, electrophysiological brain activity shows potential for enhancing understanding of emotional responses related to cosmetic products. Frontal asymmetry, particularly in the alpha frequency band, was often use and frequently linked to positive emotional states, although conflicting evidence exists. Additionally, cardiac activity, specifically the LF/HF ratio, emerges as a promising marker for differentiating between different cosmetic products. However, methodological heterogeneity, present challenges for replicability, generalizability, and complicate data interpretation.

Evaluation of the hydrating benefits of a cationic hyaluronic acid: From biological evaluation to consumer home use trial

Active ingredients are often assessed based on physiological measurements, but innovative technologies to measure skin sensations can provide a holistic volunteer assessment of the use of an ingredient. In this paper, the hydrating benefits of a cationic hyaluronic acid (HA) were evaluated alongside clinical biometrics and innovative cognitive measurements to determine how biological benefits correlated with volunteers' feelings and perceptions of hydration. The results demonstrated that cationic HA provides hydrating benefits at the clinical level due to its film-forming properties. Through the use of innovative behavioural measurement tools, we were able to show that these outcomes are perceived by naïve consumers in real-life conditions. In addition, the benefits of cationic HA reported by users were in accordance with the mental representation they had related to the use of HA, thus the product achieved complete sensorial embodiment. We can conclude that the combination of clinical evaluations and home use trials consolidates product assessment when seeking to measure consumer satisfaction with proven biological benefits.

Autonomic Responses Associated with Olfactory Preferences of Fragrance Consumers: Skin Conductance, Respiration, and Heart Rate

Assessing the olfactory preferences of consumers is an important aspect of fragrance product development and marketing. With the advancement of wearable device technologies, physiological signals hold great potential for evaluating olfactory preferences. However, there is currently a lack of relevant studies and specific explanatory procedures for preference assessment methods that are based on physiological signals. In response to this gap, a synchronous data acquisition system was established using the ErgoLAB multi-channel physiology instrument and olfactory experience tester. Thirty-three participants were recruited for the olfactory preference experiments, and three types of autonomic response data (skin conductance, respiration, and heart rate) were collected. The results of both individual and overall analyses indicated that olfactory preferences can lead to changes in skin conductance (SC), respiration (RESP), and heart rate (HR). The trends of change in both RESP and HR showed significant differences (with the HR being more easily distinguishable), while the SC did not exhibit significant differences across different olfactory perception preferences. Additionally, gender differences did not result in significant variations. Therefore, HR is more suitable for evaluating olfactory perception preferences, followed by RESP, while SC shows the least effect. Moreover, a logistic regression model with a high accuracy (84.1%) in predicting olfactory perception preferences was developed using the changes in the RESP and HR features. This study has significant implications for advancing the assessment of consumer olfactory preferences.

Emotional design pictures: Pleasant but too weak to evoke arousal and attract attention?

A new field of research builds on the theoretical assumption that distinct design manipulations, such as human-like features with appealing colors (emotional design), foster multimedia learning by influencing the learners' affective state (i.e., valence and arousal) and attention. Empirical studies, however, provide inconsistent findings of the affective potential of emotional design, underlining the need for psychophysiological measurements to assess the affective state and attention more objectively. The effects of differently designed stimuli (picture-text combinations with anthropomorphic pictures in bright and saturated colors [emotional design], picture-text combinations with non-anthropomorphic pictures in grayscale [neutral design], and plain text [control design]) on junior high school students' valence (N = 15), arousal (N = 18), and attention (N = 27) were examined. Valence was determined by students' judgments on a rating scale; arousal and attention were assessed by psychophysiological parameters (electrodermal activity of students and their dwell time on stimuli, respectively). To allow the examination of valence and arousal as separate dimensions, two independent experiments were conducted. Results of experiment I show that students perceived emotional design stimuli as more pleasant than stimuli in neutral or control design. Besides, an interaction with the content of the stimuli was found. While the positive effect of the emotional design was found for concepts that could be interpreted as potentially positive (e.g., sunlight) or neutral (e.g., consumer), stimuli representing potentially negative concepts (e.g., dead consumer) were not perceived as more pleasant if presented in emotional design. Experiment II shows that emotional design did not induce higher arousal than neutral and control designs and did not attract more attention. Instead, the text within picture-text combinations (emotional and neutral designs) attracted more attention when pictures were presented in neutral than in emotional design. By investigating the emotional state more differentiated and by examining arousal and attention using psychophysiological parameters, the present study helps to understand the heterogeneous findings of previous studies.

Measurement of Stress Relief during Scented Cosmetic Product Application Using a Mood Questionnaire, Stress Hormone Levels and Brain Activation

Nowadays, consumers’ well-being plays a decisive role in the purchase of cosmetic products. Although factors influencing consumers' well-being are very subjective, companies strive to develop their products in such a way that a positive effect is likely. Therefore, methods are required to objectively explore and scientifically prove the product’s performance on humans. In this placebo-controlled study, a method was developed to evaluate relaxation or stress relief associated with one olfactory ingredient of a cosmetic product (face cream). Our experimental protocol included product testing in 25 healthy females, while an emotion questionnaire, analysis of saliva samples regarding the concentration of the hormones cortisol and α-amylase and mobile EEG measurement for quantification of the alpha brain waves before and after stress induction were conducted. It was shown that with this experimental design, the sample with the ingredient produced significant stress relief, as evidenced by significantly less negative emotion, significantly lowered cortisol levels and showed a trend towards a significant increase in alpha activity compared to placebo application. Our data provide evidence that this method is suitable for analyzing the differences between the two samples. In the future, this method can be utilized in the current or a further optimized form to evaluate the psychophysiological effects of cosmetic products on humans.

An intelligent neuromarketing system for predicting consumers' future choice from electroencephalography signals

Neuromarketing utilizes Brain-Computer Interface (BCI) technologies to provide insight into consumers responses on marketing stimuli. In order to achieve insight information, marketers spend about $400 billion annually on marketing, promotion, and advertisement using traditional marketing research tools. In addition, these tools like personal depth interviews, surveys, focus group discussions, etc. are expensive and frequently criticized for failing to extract actual consumer preferences. Neuromarketing, on the other hand, promises to overcome such constraints. In this work, an EEG-based neuromarketing framework is employed for predicting consumer future choice (affective attitude) while they view E-commerce products. After preprocessing, three types of features, namely, time, frequency, and time-frequency domain features are extracted. Then, wrapper-based Support Vector Machine-Recursive Feature Elimination (SVM-RFE) along with correlation bias reduction is used for feature selection. Lastly, we use SVM for categorizing positive affective attitude and negative affective attitude. Experiments show that the frontal cortex achieves the best accuracy of 98.67±2.98, 98±3.22, and 98.67±3.52 for 5-fold, 10-fold, and leave-one-subject-out (LOSO) respectively. In addition, among all the channels, F_z achieves best accuracy 90±7.81, 90.67±9.53, and 92.67±7.03 for 5-fold, 10-fold, and LOSO respectively. Subsequently, this work opens the door for implementing such a neuromarketing framework using consumer-grade devices in a real-life setting for marketers. As a result, it is evident that EEG-based neuromarketing technologies can assist brands and enterprises in forecasting future consumer preferences accurately. Hence, it will pave the way for the creation of an intelligent marketing assistive system for neuromarketing applications in future.

BCI-Based Consumers' Choice Prediction From EEG Signals: An Intelligent Neuromarketing Framework

Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how customers react to marketing stimuli. Marketers spend about $750 billion annually on traditional marketing camping. They use traditional marketing research procedures such as Personal Depth Interviews, Surveys, Focused Group Discussions, and so on, which are frequently criticized for failing to extract true consumer preferences. On the other hand, Neuromarketing promises to overcome such constraints. This work proposes a machine learning framework for predicting consumers' purchase intention (PI) and affective attitude (AA) from analyzing EEG signals. In this work, EEG signals are collected from 20 healthy participants while administering three advertising stimuli settings: product, endorsement, and promotion. After preprocessing, features are extracted in three domains (time, frequency, and time-frequency). Then, after selecting features using wrapper-based methods Recursive Feature Elimination, Support Vector Machine is used for categorizing positive and negative (AA and PI). The experimental results show that proposed framework achieves an accuracy of 84 and 87.00% for PI and AA ensuring the simulation of real-life results. In addition, AA and PI signals show N200 and N400 components when people tend to take decision after visualizing static advertisement. Moreover, negative AA signals shows more dispersion than positive AA signals. Furthermore, this work paves the way for implementing such a neuromarketing framework using consumer-grade EEG devices in a real-life setting. Therefore, it is evident that BCI-based neuromarketing technology can help brands and businesses effectively predict future consumer preferences. Hence, EEG-based neuromarketing technologies can assist brands and enterprizes in accurately forecasting future consumer preferences.

Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior

The current paper investigates the value and application of a range of physiological and neuroscientific techniques in applied marketing research and consumer science, highlighting new insights from research in social psychology and neuroscience. We review measures of sweat secretion, heart rate, facial muscle activity, eye movements, and electrical brain activity, using techniques including skin conductance, pupillometry, eyetracking, and magnetic brain imaging. For each measure, after a brief explanation of the underlying technique, we illustrate concepts and mechanisms that the measure allows researchers in marketing and consumer science to investigate, with a focus on consumer attitudes and behavior. By providing reviews on recent research that applied these methods in consumer science and relevant related fields, we also highlight methodological and theoretical strengths and limitations, with an emphasis on ecological validity. We argue that the inclusion of physiological and neuroscientific techniques can advance consumer research by providing insights into the often unconscious mechanisms underlying consumer behavior. Therefore, such technologies can help researchers and marketing practitioners understand the mechanisms of consumer behavior and improve predictions of consumer behavior.