To improve users' experience and decrease their likelihood of quitting watching videos, this paper addresses the question of how to encode the videos used in adaptive bitrate (ABR) video streaming. When addressing ABR video streaming, a lot of effort has been put into developing ABR control schemes. However, ways to appropriately encode videos also need to be defined. Unlike previous approaches that focus on coding quality, this paper considers the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">user quitting ratio</i> . The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">user quitting ratio</i> is the percentage of users still watching videos at a given time and enables us to address the consequences of quality and stimulus duration on the decision of a user to quit. Considering the value of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">user quitting ratio</i> , this paper describes a method that uses content analysis, as well as a network's historical throughput data, to define how video should be encoded to decrease the likelihood of users quitting watching. Unlike previous approaches, the method is independent of the ABR control scheme used by the video player, and the selected ladders perform equivalently across different players with different behaviors. Results of experiments based on real-world network traces demonstrate the usefulness of the proposed method.