Big Data Analysis for Effective Monetization of over the Top TV Content

Consumption of digital-media is shifting to Over-the-Top (OTT) delivery model and no longer requires involvement of multiple system operator in content distribution. These benefits are balanced by lack of standards for delivery platforms, audio-levels and advertising delivery. Inadequate industry standards, ad-block use, limited bandwidth and differing viewer-experience challenges content monetizing and delivery. With availability of inexpensive processing power and efficacy of real-time analysis technologies for big metadata, industry focus has shifted to content-recommendation and hyper-targeted advertising resulting in enhanced customer experience and efficient content distribution. The metadata managed by OTT platform can create partial-differential-equations containing unknown multivariable functions and partial-derivatives that can be analyzed in real-time. This paper presents the challenges and opportunities for a telco-grade OTT management-and-delivery-platforms as an ecosystem for collection of big-data from content-owner and client. This metadata could be fed to robust real-time analytic systems for augmenting end-user experience while generating revenue for content-owners and service-providers.

Published

2015-10

Content type

Original Research

Keywords

Over the top TV, advertising and media, electronic commerce, big data analytics

DOI

10.5594/M001648

ISBN

978-1-61482-956-0