Netflix: A Comparative Analysis of User Consumption Habits Before and During the Pandemic

Digital platforms streaming audiovisual content have become a consumption phenomenon that has disrupted not only the production industry but also consumption habits and how decisions are made regarding what users finally see on screen. This study proposes a theoretical and empirical approach to analyze the method employed by Netflix to make use of users’ information in order to predict their future consumption. It revisits the concepts of algorithm, database, and artificial intelligence, followed by a description of the results of a previous study that monitored Netflix consumption habits. Our work presents a case study that involves the participation of 12 users from different countries with different sociodemographic conditions, who filled in data collection templates about their consumption every 2 weeks, for 6 months, undergoing different experiences in terms of content supply and COVID -19 restrictions. This study shows that the longer the consumption and the higher the number of productions streamed, the greater the power of Netflix to create more accurate and widely accepted suggestions. The platform’s predictive power in terms of future consumption, fueled by the pandemic effect, provides a scenario in which the control over human decision-making spreads, through other Internet platforms, to every aspect and life experience.