Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas
Do podcasts and music compete with one another? Understanding music and podcast listening habits
Over the past decade, podcasts have been one of the fastest growing online streaming media. Many online audio streaming platforms such as Pandora, Spotify, etc. that traditionally focused on music content have started to incorporate services related to podcasts. Although incorporating new media types such as podcasts has created tremendous opportunities for these streaming platforms to expand their content offering, it also introduces new challenges. Since the functional use of podcasts and music may largely over- lap for many people, the two types of content may compete with one another for the finite amount of time that users may allocate for audio streaming. As a result, incorporating podcast listening may influence and change the way users have originally consumed music. Adopting quasi-experimental techniques, the current study assesses the causal influence of adding a new class of content on user listening behavior by using large scale observational data collected from a widely used audio streaming platform. Our results demonstrate that podcast and music consumption compete slightly but do not replace one another – users open another time window to listen to podcasts. In addition, users who have added podcasts to their music listening demonstrate significantly different consumption habits for podcasts vs. music in terms of the streaming time, duration and frequency. Taking all the differences as input features to a machine learning model, we demonstrate that a pod- cast listening session is predictable at the start of a new listening session. Our study provides a novel contribution for online audio streaming and consumption services to understand their potential consumers and to best support their current users with an improved recommendation system.
Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions
Rishabh Mehrotra, Prasanta Bhattacharya, Mounia Lalmas
Rishabh Mehrotra, Chirag Shah, Benjamin Carterette