Published: 2024-04-10
Purchasing Patterns Analysis in E-commerce: A Big Data-driven Approach and Methodological
DOI: 10.35870/ijsecs.v4i1.2384
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Abstract
This research aims to analyze purchasing patterns in e-commerce using a Big Data-based approach and data analysis methods. Leveraging advanced technology and analytical methodology, this research explores consumer behavior, market trends, and factors influencing purchasing decisions in e-commerce. Through collecting transaction data from leading e-commerce platforms and applying rigorous data analysis techniques, this research identifies significant patterns and provides valuable insights for e-commerce companies. This research shows that big data has great potential in understanding consumer behavior and market trends in e-commerce. In contrast, sophisticated data analysis methods are essential in interpreting the large and complex data generated by e-commerce. The findings of this research significantly contribute to the development of the e-commerce industry by helping companies improve their marketing strategies and business decision-making. However, this research also needs help, as it requires data analysis skills and privacy issues. To overcome these challenges, collaboration between researchers, e-commerce companies, and governments is needed to develop the necessary data analysis expertise and ensure that consumer data is managed securely and ethically. Thus, this research provides a more holistic view of consumer behavior and market dynamics in e-commerce, assisting companies and policymakers in addressing challenges and opportunities in an ever-evolving landscape.
Keywords
Purchase Pattern Analysis ; E-commerce ; Big Data ; Data Analysis Method ; Customer Preferences
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 4 No. 1 (2024)
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Section: Articles
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Published: %750 %e, %2024
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License: CC BY 4.0
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Copyright: © 2024 Authors
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DOI: 10.35870/ijsecs.v4i1.2384
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Andik Adi Putra Riwayat
Digital Business Study Program, Faculty of Science and Technology, Institut Teknologi Sains dan Kesehatan ICME Jombang, Jombang Regency, East Java Province, Indonesia
Agnes Dwita Susilawati
Management, Economics and Business Study Program, Universitas Pancasakti Tegal, Tegal City, Central Java Province, Indonesia
Zakiyyatun Naqiah
Digital Business Study Program, Politeknik Hasnur, Barito Kuala Regency, South Kalimantan, Indonesia
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