By Arash Pendari & Giles Wilson, VionLabs AB; Michael Eagles, Liberty Global
Live TV was, and still is, a brilliant discovery tool, but it needs a makeover. Sooner rather than later.
Live TV scheduling is all about audience flow. The ability to engage the viewer and retain them within that live broadcast channel is the primary function of good broadcast scheduling and how live TV has been able to maintain its dominance over viewing minutes for so many years.
When pay-tv was young, the linear channel was the only way of finding new content, with its limited possibilities it still served as a great tool in guiding viewers to content and providing a quick way of sampling a large amount diverse content. The TV channel logo and brand helped guide to the direction of channels and provided comfort in what to expect behind a certain logo. You would expect to find nothing but boats behind the “Sailing Channel” logo, and inspirational mood programs behind the “Travel Channel” logo. A channel without a clear enough content profile would often become less and less relevant and lose viewership.
In an SVOD and non-linear world the brands of the broadcasters play a less important role in guiding between content and the brand properties of the logos have been given less relevant. Instead, we can see playlists, recommendations and series emerging as the guiding stars for this. In this paper we will show how a strong playlist capability (“Next Player”), that uses Machine Learning and A.I. to compare similarities in types of content, can provide a good proxy for that scheduling art form.
Whilst the possibility of watching any content asset at any given time represents a superior customer value to the defined time slots of the linear channels, it also represents an expectation of an increasingly active customer and places a lot more of the burden of discovery on the consumer. This is a burden many customers are neither capable, nor willing, to shoulder. The lack of guidance in the user experience is now creating a problem for consumers in navigating and finding new content. We intend to show that this burden can be eased through content similarity analytics for matching, combined with user-created profiles; shifting the audience flow story and related value creation opportunity towards the platform.
The effect of the discovery problem we describe has been an increased amount of the consumers’ time being spent on the process of discovery instead of watching content - searching for content or becoming paralyzed by the many choices. This in turn creates the perception of a significantly smaller content catalog than most players actually have available. By introducing the Next Player concept, we aim to reduce customer frustration and increase satisfaction as well as re-invigorating the traditional TV business model by modernizing the Linear TV viewing experience and creating new advertising inventory.