The influence of neuromarketing: machine learning based empirical analysis

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Bibliographic Details
Main Authors:	Muktadir, MD. Abdullah Al, Malek, Shamsul, Hossain, Zakia
Other Authors:	Reza,Md Tanzim
Format:	Thesis
Language:	English
Published:	Brac University 2024
Subjects:	Neuromarketing Long Short-Term Memory model Machine learning Machine learning.
Online Access:	http://hdl.handle.net/10361/24048

id	10361-24048
record_format	dspace
spelling	10361-240482024-09-10T21:04:49Z The influence of neuromarketing: machine learning based empirical analysis Muktadir, MD. Abdullah Al Malek, Shamsul Hossain, Zakia Reza,Md Tanzim Department of Computer Science and Engineering, Brac University Neuromarketing Long Short-Term Memory model Machine learning Machine learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 36-38). This study attempts to investigate the topic of neuromarketing and how it has be come an emerging topic that might be used as a tool for market research. Both academic writing and real-world marketing are embracing neuromarketing. Addi tionally, it applies brain science to a management setting. It looks after the theoret ical contribution of neuromarketing which comprehends modern consumer response to marketing stimuli. Again, the research in the field of neuromarketing looks at how people’s brains respond to marketing strategies. Researchers use methods like FMRI, EEG and eye tracking to study why consumers may claim to desire one thing but ultimately make choices depending on their feelings. In order to under stand how customers’ bodies, thoughts, emotions and inner selves are engaged in decision making, the research will use neuromarketing strategies. Additionally, it covers the expanding use of neuromarketing across sectors and lists the top neu romarketing firms in each. Also, it analyzes the expanding use of neuromarketing across a range of sectors and lists the top neuromarketing firms currently operating. The study examines the equipment and methods used in neuromarketing, such as eye tracking, galvanic skin reaction, EEG analysis and cognitive analysis. These approaches can be combined to create a comprehensive understanding. That can allow the customers to respond to marketing stimuli. Overall, this study adds to the expanding body of information on neuromarketing that leads to creating interest in this particular area. Besides, it’s potential for use in brand management, advertis ing, and marketing. Explores the potential of EEG technology in neuromarketing which is emphasizing the ethical considerations. It highlights the role of machine learning algorithms. In terms of analyzing consumer responses to marketing stim uli through EEG signals.Through, suggesting the field is on the verge of significant breakthroughs. It focuses on the empirical approaches in neuromarketing applied to food choices. Therefore, it presents a comprehensive approach to predict consumer emotions. Through EEG signal analysis, it can achieve a remarkable accuracy of approximately 96.89% in predicting consumer preferences. MD. Abdullah Al Muktadir Shamsul Malek Zakia Hossain B.Sc in Computer Science 2024-09-10T10:14:00Z 2024-09-10T10:14:00Z ©2023 2023-09 Thesis ID 18301235 ID 20201141 ID 20201141 http://hdl.handle.net/10361/24048 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 38 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Neuromarketing Long Short-Term Memory model Machine learning Machine learning.
spellingShingle	Neuromarketing Long Short-Term Memory model Machine learning Machine learning. Muktadir, MD. Abdullah Al Malek, Shamsul Hossain, Zakia The influence of neuromarketing: machine learning based empirical analysis
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
author2	Reza,Md Tanzim
author_facet	Reza,Md Tanzim Muktadir, MD. Abdullah Al Malek, Shamsul Hossain, Zakia
format	Thesis
author	Muktadir, MD. Abdullah Al Malek, Shamsul Hossain, Zakia
author_sort	Muktadir, MD. Abdullah Al
title	The influence of neuromarketing: machine learning based empirical analysis
title_short	The influence of neuromarketing: machine learning based empirical analysis
title_full	The influence of neuromarketing: machine learning based empirical analysis
title_fullStr	The influence of neuromarketing: machine learning based empirical analysis
title_full_unstemmed	The influence of neuromarketing: machine learning based empirical analysis
title_sort	influence of neuromarketing: machine learning based empirical analysis
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/24048
work_keys_str_mv	AT muktadirmdabdullahal theinfluenceofneuromarketingmachinelearningbasedempiricalanalysis AT malekshamsul theinfluenceofneuromarketingmachinelearningbasedempiricalanalysis AT hossainzakia theinfluenceofneuromarketingmachinelearningbasedempiricalanalysis AT muktadirmdabdullahal influenceofneuromarketingmachinelearningbasedempiricalanalysis AT malekshamsul influenceofneuromarketingmachinelearningbasedempiricalanalysis AT hossainzakia influenceofneuromarketingmachinelearningbasedempiricalanalysis
_version_	1814309317793284096

The influence of neuromarketing: machine learning based empirical analysis

Similar Items