OVER THE TOP AND THROUGH AI TO BIG DATA’S HOUSE WE GO Qligent COO Ted Korte on how AI and machine learning can be used to prevent subscriber churn
he media delivery business has become a game of seconds. The lines have blurred between broadcast and other IP-related services for delivering media, while content creation has grown from original TV series and movies to how-to videos and social media posts. Access to content for consumers seems limitless, with digital audio and video now the preferred media for nearly all of our daily activities. With so much content being consumed for a wider variety of purposes, viewing time and audience attention spans have grown shorter, making every second count. The main contributor to the rapid expansion of content creation and consumption has been the emergence of over the top (OTT) delivery, made possible by broadband connectivity to a wide range of “connected” devices. This model gives consumers access, convenience and value that wasn’t available via traditional linear services. However, cable, satellite, IPTV and over the air (OTA) delivery will not completely disappear; each will find their place in this new media delivery ecosystem. For these providers, competing in this fragmented landscape will require a mix of traditional linear services alongside new OTT services, combined with a strong data-driven approach. Content owners maintain very little control upon turning their product over to CDNs and OTT service providers for delivery. To complicate matters, they lack insight into the viewer’s quality of experience (QoE), as more and more third-party services become part of the end-to-end solution. This vacuum of information begs for new methods that ensure a quality experience and proper measurement of viewer engagement. The aggregation of quality of service (QoS), QoE and viewer behaviour data produces extremely large but trusted data sets. By harnessing sophisticated machine learning (ML) and artificial intelligence (AI) technologies to process this data, media enterprises
can glean the valuable insights needed to improve the viewer experience. Significantly, these techniques can be used to predict – in turn allowing operators to prevent – customer-impacting problems before they occur, which is invaluable in minimising subscriber churn. THE OTT CHALLENGE OTT has tremendous growth potential for the media and entertainment sector, with growth projected to exceed $158 billion worldwide by 2025. OTT delivery can provide consumers with oneto-one, personalised experiences while offering providers the ability to collect immediate feedback. To maximise this opportunity, content creators will need to determine the right content, right duration, right time and right platform to reach their audience in real time. Regardless of the end goal, though, the first question in any decision tree should be “Is the quality great?” Studies consistently place poor quality in the top four reasons why viewers abandon OTT video. And with short-form content consumption on the rise, even relatively brief problems become very noticeable – for example, imagine a five-second
‘The use of AI and ML enables providers to predict problems before they actually occur, and thus correct them before they impact their viewers.’ 58 | TVBEUROPE MAY 2019
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