Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance

In today’s competitive digital landscape, banking firms must leverage qualitative and quantitative analysis to enhance their website interfaces, ensuring they meet user needs and expectations. By combining detailed user feedback with data-driven insights, banks can create more intuitive and engaging online experiences, ultimately driving customer satisfaction and loyalty. Thus, the need for website customer behavior analysis to evaluate its interface is critical. This study focused on the five biggest banking firms and collected big data from their websites. Statistical analysis was followed to validate findings and ensure the reliability of the results. At the same time, agent-based modeling (ABM) and System Dynamics (SD) were utilized to simulate user behavior, thereby allowing for the prediction of responses to interface changes and the optimization of their website, and to obtain a comprehensive understanding of user behavior, thereby enabling banking firms to create more intuitive and user-friendly website interfaces. This interdisciplinary approach found that various website analytical metrics, such as organic and paid traffic costs, referral domains, and email sources, tend to impact banking firms’ purchase conversion, display ads, organic traffic, and bounce rate. Moreover, these insights into banking firms’ website visibility, combined with the behavioral data of the neuromarketing study, indicate specific areas for their website interface and performance improvement.

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Publication Details

Journal
Electronics
Published
2024-08-16
DOI
https://doi.org/10.3390/electronics13163256
Citations
5
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
5.66
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article

Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance

Nikolaos T. Giannakopoulos, Δαμιανός Π. Σακάς, Stavros P. Migkos
5 citations
Electronics
Digital Marketing and Social Media
5.66
article

Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance

Nikolaos T. Giannakopoulos, Δαμιανός Π. Σακάς, Stavros P. Migkos
article en
5 citations

Abstract

In today’s competitive digital landscape, banking firms must leverage qualitative and quantitative analysis to enhance their website interfaces, ensuring they meet user needs and expectations. By combining detailed user feedback with data-driven insights, banks can create more intuitive and engaging online experiences, ultimately driving customer satisfaction and loyalty. Thus, the need for website customer behavior analysis to evaluate its interface is critical. This study focused on the five biggest banking firms and collected big data from their websites. Statistical analysis was followed to validate findings and ensure the reliability of the results. At the same time, agent-based modeling (ABM) and System Dynamics (SD) were utilized to simulate user behavior, thereby allowing for the prediction of responses to interface changes and the optimization of their website, and to obtain a comprehensive understanding of user behavior, thereby enabling banking firms to create more intuitive and user-friendly website interfaces. This interdisciplinary approach found that various website analytical metrics, such as organic and paid traffic costs, referral domains, and email sources, tend to impact banking firms’ purchase conversion, display ads, organic traffic, and bounce rate. Moreover, these insights into banking firms’ website visibility, combined with the behavioral data of the neuromarketing study, indicate specific areas for their website interface and performance improvement.

ElectronicsVol. 13(16)
Agricultural University of Athens (GR), University of Western Macedonia (GR)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Digital Marketing and Social Media
5.66
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Neuromarketing and Big Data Analysis of Banking Firms’ Website Interfaces and Performance — Nikolaos T. Giannakopoulos, Δαμιανός Π. Σακάς, et al. · Electronics (2024) | TGRS Research Map | TGRS