Analysis of Attraction Response on Product Packaging Based on EEG Signal: (A preliminary study of Neuromarketing on Packaging)

Jauzaa Maylia Suhendro*, Adhi Dharma Wibawa, Arbintoro Mas

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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%).

Original languageEnglish
Title of host publicationIES 2023 - International Electronics Symposium
Subtitle of host publicationUnlocking the Potential of Immersive Technology to Live a Better Life, Proceeding
EditorsAndhik Ampuh Yunanto, Afifah Dwi Ramadhani, Yanuar Risah Prayogi, Putu Agus Mahadi Putra, Maretha Ruswiansari, Mohamad Ridwan, Farida Gamar, Weny Mistarika Rahmawati, Rusli Muhammad Rusli, Fitrah Maharani Humaira, Ahmad Firyal Adila
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages479-485
Number of pages7
ISBN (Electronic)9798350314731
DOIs
Publication statusPublished - 2023
Event25th International Electronics Symposium, IES 2023 - Denpasar, Indonesia
Duration: 8 Aug 202310 Aug 2023

Publication series

NameIES 2023 - International Electronics Symposium: Unlocking the Potential of Immersive Technology to Live a Better Life, Proceeding

Conference

Conference25th International Electronics Symposium, IES 2023
Country/TerritoryIndonesia
CityDenpasar
Period8/08/2310/08/23

Keywords

  • Brain Signal
  • Electroencephalography (EEG)
  • Neuromarketing
  • Packaging
  • Power Spectral Density (PSD)

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