Catch-up TV analytics: statistical characterization and consumption patterns identification on a production service

Abstract

Multimedia IP Television services, such as on-demand Catch-up TV, are in an active migration process towards Over-The-Top (OTT) delivery using state-of-the-art Content Delivery Networks (CDNs). Maintaining the same Quality-of-Experience (QoE) of managed IPTV networks is challenging and requires a thorough understanding of users’ behaviors and content demand characteristics. This article leverages Catch-up TV usage logs obtained from a Pay-TV operator’s live production IPTV service containing over 1 million subscribers to characterize and extract insights from service utilization at a scale and scope not yet addressed in the literature. A detailed analysis on the characteristics of users’ viewings is performed, with a study of when, where, and how often users access the service, along with how they behave during each viewing session. The results show that Catch-up TV consumption exhibits very high levels of utilization throughout the day, and is heavily polarized towards specific genres, recently aired programs, and content broadcasted during prime-time. The superstar effect is notorious. This analysis is complemented by a service optimization perspective, which shows that large gains are achievable by caching popular programs, and by loading content in advance to users’ Set-Top-Boxes (STBs). This comprehensive research study is supplemented by detailed statistical information tables, which highlight the feasibility of efficiently migrating Catch-up TV services to OTT-scenarios, and provide the foundations for future works able to explore these results.