Enhancing E-Commerce with Big Data: From Browsing to Buying Through Recommendation Systems





recommendation system, customer behavior, e-commerce, big data-driven


This research focuses on analyzing the impact of a recommendation system on customer behavior in the e-commerce industry. This study examines the use of big data-driven product recommendations and tailored promotions to enhance customer engagement, conversion rates, and revenue generation. The importance of prioritizing customer engagement in the early stages of the purchasing process is emphasized, and key statistics related to customer behavior in e-commerce are presented. The objective of this research is to investigate the effectiveness of a recommendation system in influencing customer behavior and driving conversions in the e-commerce industry. The research design incorporates a case study analysis of a prominent marketplace in Indonesia. Data were collected from three automation trigger campaigns: browsing abandonment and purchase reminders. The findings of this research indicate that a recommendation system based on big data has a significant impact on customer behavior in the e-commerce industry. This research highlights the importance of prioritizing customer engagement and implementing effective recommendation systems to drive conversion rates and revenue in the e-commerce industry.


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Author Biographies

Mustika Sufiati Purwanegara, Bandung Institute of Technology

With extensive experience in various roles including researcher, consultant, and faculty member at SBM ITB, Mustika has focused her expertise on consumer behavior research, strategic marketing, and inclusive business ecosystems. She actively participates in international conferences and is a member of esteemed marketing science associations. Mustika's passion lies in exploring topics such as international trading, neuromarketing, digital marketing, consumer culture, and public policy, while also providing training, consultation, and market research services to businesses and communities.

Nur Budi Mulyono, Bandung Institute of Technology

Nur Budi Mulyono is an academic staff at the School of Business and Management, Institut Teknologi Bandung (SBM ITB), holding a bachelor's and master's degree in Industrial Engineering from Institut Teknologi Bandung in 2001 and 2005, respectively. He further obtained his doctoral degree in the field of disaster operation management from Toyohashi University of Technology.

Throughout his studies, Nur Budi actively participated in a local government project in Japan, focusing on developing a robust system for disaster prevention. He also contributed to the development of technical solutions for small and medium manufacturing industries in Toyohashi city, aiming to enhance their productivity and resilience against disruptions. His research interests encompass Operation Management, Productivity Management, Relief Supply Chain, Artificial Intelligence, and Resilient Systems in the manufacturing and energy sectors.


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January 30, 2024

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How to Cite

Johnson, N., Purwanegara, M. S., & Mulyono, N. B. (2024). Enhancing E-Commerce with Big Data: From Browsing to Buying Through Recommendation Systems. International Journal of Entrepreneurship, Business and Creative Economy, 4(1), 130–145. https://doi.org/10.31098/ijebce.v4i1.1930




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