Johnson, Nuraeni
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Enhancing E-Commerce with Big Data: From Browsing to Buying Through Recommendation Systems Johnson, Nuraeni; Purwanegara, Mustika Sufiati; Mulyono, Nur Budi
International Journal of Entrepreneurship, Business and Creative Economy Vol. 4 No. 1 (2024): January
Publisher : Research Synergy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/ijebce.v4i1.1930

Abstract

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.