TY - GEN
T1 - Analysis of Attraction Response on Product Packaging Based on EEG Signal
T2 - 25th International Electronics Symposium, IES 2023
AU - Suhendro, Jauzaa Maylia
AU - Wibawa, Adhi Dharma
AU - Mas, Arbintoro
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Product packaging is a key component of the marketing strategy. Packaging is a powerful visual marketing tool that grabs consumers' attention and shapes their perception of brands and products. Neuromarketing tries to show how product packaging affects customer behavior, emotional responses, memory, and cognitive processes in the brain. In addition, it can provide deeper insight into consumers' unconscious brain responses to product packaging compared to traditional methods such as surveys or interviews. Recently, electroencephalogram (EEG) technology has been used widely by researchers to record and analyze brain activities, but very few on analyzing consumers' brain activity when interacting with product packaging. This study involves 30 volunteers to investigate the brain signals of attractive and unattractive packaging. Four EEG channels were used to record the signals, namely T3, T4, O1, and O2. EEG-preprocessing was done to do the feature extraction, and classification stage. The cleaned EEG signals were decomposed into Alpha, Beta, and Gamma sub-bands. To classify attractive and unattractive packaging, features Power Spectral Density (PSD) was taken from EEG data and computed. Based on the result, we found that the PSD value on attractive packaging is relatively higher than on unattractive packaging from each subband (alpha, beta, and gamma). It can be concluded that the high PSD value also indicates high enthusiasm for attractive packaging. We also found that the activity in the gamma subband indicates a higher cognitive process on attractive packaging. The three classification algorithms used in this study are Random Forest, KNN, and SVM. The best results were obtained from the random forest algorithm (73%), followed by KNN (60%), and SVM (52%).
AB - Product packaging is a key component of the marketing strategy. Packaging is a powerful visual marketing tool that grabs consumers' attention and shapes their perception of brands and products. Neuromarketing tries to show how product packaging affects customer behavior, emotional responses, memory, and cognitive processes in the brain. In addition, it can provide deeper insight into consumers' unconscious brain responses to product packaging compared to traditional methods such as surveys or interviews. Recently, electroencephalogram (EEG) technology has been used widely by researchers to record and analyze brain activities, but very few on analyzing consumers' brain activity when interacting with product packaging. This study involves 30 volunteers to investigate the brain signals of attractive and unattractive packaging. Four EEG channels were used to record the signals, namely T3, T4, O1, and O2. EEG-preprocessing was done to do the feature extraction, and classification stage. The cleaned EEG signals were decomposed into Alpha, Beta, and Gamma sub-bands. To classify attractive and unattractive packaging, features Power Spectral Density (PSD) was taken from EEG data and computed. Based on the result, we found that the PSD value on attractive packaging is relatively higher than on unattractive packaging from each subband (alpha, beta, and gamma). It can be concluded that the high PSD value also indicates high enthusiasm for attractive packaging. We also found that the activity in the gamma subband indicates a higher cognitive process on attractive packaging. The three classification algorithms used in this study are Random Forest, KNN, and SVM. The best results were obtained from the random forest algorithm (73%), followed by KNN (60%), and SVM (52%).
KW - Brain Signal
KW - Electroencephalography (EEG)
KW - Neuromarketing
KW - Packaging
KW - Power Spectral Density (PSD)
UR - http://www.scopus.com/inward/record.url?scp=85173603160&partnerID=8YFLogxK
U2 - 10.1109/IES59143.2023.10242535
DO - 10.1109/IES59143.2023.10242535
M3 - Conference contribution
AN - SCOPUS:85173603160
T3 - IES 2023 - International Electronics Symposium: Unlocking the Potential of Immersive Technology to Live a Better Life, Proceeding
SP - 479
EP - 485
BT - IES 2023 - International Electronics Symposium
A2 - Yunanto, Andhik Ampuh
A2 - Ramadhani, Afifah Dwi
A2 - Prayogi, Yanuar Risah
A2 - Putra, Putu Agus Mahadi
A2 - Ruswiansari, Maretha
A2 - Ridwan, Mohamad
A2 - Gamar, Farida
A2 - Rahmawati, Weny Mistarika
A2 - Rusli, Rusli Muhammad
A2 - Humaira, Fitrah Maharani
A2 - Adila, Ahmad Firyal
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 August 2023 through 10 August 2023
ER -