Netflix Bigdata Analytics - The Emergence of Data Driven Recommendation
Srivatsa Maddodi, & Krishna Prasad, K. (2019). Netflix Bigdata Analytics- The Emergence of Data Driven Recommendation. International Journal of Case Studies in Business, IT, and Education (IJCSBE), 3(2), 41-51. DOI: org/10.5281/zenodo.3510316
10 Pages Posted: 21 Feb 2020
Date Written: October 21, 2019
Netflix is one of the largest online streaming media providers. It began its operations in 1997. Founded by two tech entrepreneur Reed Hastings and Marc Randolph. The Company’s head office is in Los Gatos, California. Netflix’s initially started selling DVDs or provide them on a rental basis. Over the period with growth of internet users and the decline of DVD sales and rental services, it changed its business model to video on demand. From 2012 onwards, it started producing its original TV-series and movies. Netflix uses bigdata analytics to understand its customers base better. By using these data, they provide better service or product to the customer. Netflix collects huge amounts of data from a vast variety of subscriber base. It collects data such as the location of a user; content watched by the user, user interests, the data searched by the user, and the time at which user watched. Based on these parameters its algorithm gives a personalized recommendation based on the user interest. Netflix has constantly focused on changing business needs they have moved their business model from DVD rental to video on demand and currently producing original shows. In this paper we analyze various business strategies of Netflix. This paper also analyzes how Netflix with the help of bigdata analytics focused on improving the subscriber’s experience and how it helped to be more customer-centric and increased its user base. Based on the SWOT and PESTLE analysis we have provided some suggestion that can be incorporated by Netflix as business strategy.
Keywords: Netflix, Bigdata, Data analytics, Customer experience, Video on demand
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