Understanding the impact of video quality on user engagement

  • Authors:

  • Florin Dobrian;Vyas Sekar;Asad Awan;Ion Stoica;Dilip Joseph;Aditya Ganjam;Jibin Zhan;Hui Zhang

  • Affiliations:

  • Conviva, San Mateo, CA, USA;Intel Labs, Berkeley, CA, USA;Conviva, San Mateo, CA, USA;University of California, Berkeley/Conviva, Berkeley, CA, USA;Conviva, San Mateo, CA, USA;Conviva, San Mateo, CA, USA;Conviva, San Mateo, CA, USA;Carnegie Mellon University/Conviva, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the ACM SIGCOMM 2011 conference
  • Year:
  • 2011

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Abstract

As the distribution of the video over the Internet becomes main- stream and its consumption moves from the computer to the TV screen, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand if and how video quality affects user engagement and how to best invest their resources to optimize video quality. This paper is a first step towards addressing these questions. We use a unique dataset that spans different content types, including short video on demand (VoD), long VoD, and live content from popular video con- tent providers. Using client-side instrumentation, we measure quality metrics such as the join time, buffering ratio, average bitrate, rendering quality, and rate of buffering events. We quantify user engagement both at a per-video (or view) level and a per-user (or viewer) level. In particular, we find that the percentage of time spent in buffering (buffering ratio) has the largest impact on the user engagement across all types of content. However, the magnitude of this impact depends on the content type, with live content being the most impacted. For example, a 1% increase in buffering ratio can reduce user engagement by more than three minutes for a 90-minute live video event. We also see that the average bitrate plays a significantly more important role in the case of live content than VoD content.