Netflix Bigdata Analytics- The Emergence of Data Driven Recommendation

Abstract

Netflix is one of the largest online streaming media providers. It began its operations in1997.Founded by two tech entrepreneur Reed Hastings and Marc Randolph. The Company’shead office is in Los Gatos, California. Netflix’s initially started selling DVDs or providethem on a rental basis. Over the period with growth of internet users and the decline of DVDsales and rental services, it changed its business model to video on demand. From 2012onwards, it started producing its original TV-series and movies. Netflix uses bigdata analyticsto understand its customers base better. By using these data, they provide better service orproduct to the customer. Netflix collects huge amounts of data from a vast variety ofsubscriber 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 onthese parameters its algorithm gives a personalized recommendation based on the userinterest. Netflix has constantly focused on changing business needs they have moved theirbusiness model from DVD rental to video on demand and currently producing originalshows. In this paper we analyze various business strategies of Netflix. This paper alsoanalyzes how Netflix with the help of bigdata analytics focused on improving thesubscriber’s experience and how it helped to be more customer-centric and increased its userbase. Based on the SWOT and PESTLE analysis we have provided some suggestion that canbe incorporated by Netflix as business strategy