Paper Contents
Abstract
In the era of digital streaming, personalization has become a crucial component of user engagement and platform success. This research explores the impact of personalized content recommendation systems on customer engagement at Netflix, a global leader in streaming services. The study investigates how Netflixs advanced recommendation algorithmspowered by collaborative filtering, content-based filtering, and machine learningaffect user satisfaction, viewing behavior, and subscription retention. By analyzing user interaction patterns and reviewing secondary data, the research examines the effectiveness of these systems in enhancing user experiences and maintaining loyalty. Additionally, the paper considers how demographic factors such as age, education, and regional distribution influence the success of personalized recommendations. The findings aim to offer insights into the strategic role of data-driven personalization in digital content delivery and its implications for user engagement in the streaming industry.
Copyright
Copyright © 2025 Ayusikha Dutta. This is an open access article distributed under the Creative Commons Attribution License.
