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The Adoption of Analytics in Handling Netflix’s Business Challenges Cahya, Amani Bunga; Pavitra, Orked; Fahim Jamal, Dharma
International Journal of Information Technology and Computer Science Applications Vol. 3 No. 3 (2025): September - December 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v3i3.222

Abstract

Text analytics is a combination of various kinds of text analysis that combines a set of linguistic, statistical and machine learning that extract the meaning out of the text. For example, the analyzing of customer reviews written by Netflix’s customers can be used to find out common patterns and trends that happen around the business for better action-taking, customer experience, and new business models to be built in the future. By doing text analytics, the text data can be grouped with the purposes of creating word frequency distribution (word cloud) and sentiment analysis. Whereas web analytics is referring to the process of collecting data from website through data crawling before processing it into useful info to improve the website experience by using social media analytics (Saini et al., 2022). To find out ways to aid in the formulation of marketing strategies, clustering techniques have been used. The clustering techniques will include behavioral segmentation that focus on human behavior, demographic segmentation that focuses on age, and occupation, and psychographic segmentation that focus on human’s psychological characteristics such as interest, personalities, and so on.