The success of AR in television will stem from augmenting main-screen video with additional metadata and video information, which can be displayed in AR either in a headset or through a second screen experience. One exciting use-case is sports, since fans love data and that data is readily available. Some sports are especially well suited for AR, if they are dispersed over a large area, like in a motor race. It is impossible to view the entire action at once, so being able to choose additional information or viewpoints is a real consumer value-add.
Consumers have unlimited content choice but may reach a point when they have had enough of fragmentation across multiple streaming services. There must be some re-bundling. Key responsibilities for a Pay TV super-aggregator include low-touch onboarding of new content and providing a bridge between content silos. They must provide an elegant, data-driven approach to personalised content discovery.
The TV industry is once again seeking new codecs to boost video compression efficiency. A successor to HEVC is under active development: VVC (Versatile Video Coding). This standard is due for completion in October 2020 and is likely be approved as H.266 (VVC), but the licensing model is currently unclear. Meanwhile, AV1 is regarded as the natural successor to VP9, though questions remain over adoption beyond the largest SVOD providers.
Companies such as Google see their smart speakers more as computing devices that live in a shared environment than as personal devices. A happy home will need a multi-modal approach that includes remote control button-based voice interaction, as well as standard remote control input. Today’s popular smart speakers focus on what the user is saying rather than how the user is talking to the device: recognising emotion could be the next step in personalising experiences. Button-based voice control is a less obtrusive approach to emotion recognition and customisation.
Imagine asking your TV, tablet or smartphone for the latest on Brexit and being offered a series of broadcast-quality video clips in response. The TV operator environment would be like a search engine – and it can find your favourite celebrity, catch-phrase or pop culture topic, too. This is possible where an AI ‘reads’ faces, speech, objects, logos, on-screen text and subtitles. The engine understands what video is about and what is relevant to you. It can find, cut and present the content it finds as a series of short clips. A voice assistant becomes a natural way to find content.
While significant efficiencies are enabled in software-based video compression, machine learning and artificial intelligence are being used to further optimise video delivery. AI systems can fine-tune algorithms to particular needs - like face detection or dark scene processing - faster. ML and AI improve encoder density. Codec evolutions can be tested more quickly, allowing operators to experiment with new business models. There is much more scope for customisation. This article explores the implementation scenarios for AI/ML in video compression.
With advertising revenues under pressure, TV channels see targeted advertising as an exciting new opportunity. According to eMarketer, by 2019, personalized advertising spending will...
Younger demographics are now far more likely to be influenced by social media and act on the recommendations of friends when deciding what TV to watch. In order for OTT platforms to grow, their content must be highly visible, accessible and sharable. Social content reach will be the most important factor in winning market share. The key challenge is positioning your social channels as the ‘go-to’ place for your target audience and delivering complementary content in ‘real-time’. This article summarises what you need to think about.
By providing hyper-personalisation, AI can help increase user engagement and ultimately revenues for video publishers. It can be used to create and display content in engaging ways, like transforming once-static homepages into dynamic, interactive portals. By deriving actionable insights from big data, AI provides an understanding of what viewers want and helps video providers develop content that resonates. AI can also analyse what is happening inside video – like when a goal has been scored or someone is injured in sports. The true test of AI will be making judgements about what game highlights will impress us the most.
Figures show that the U.S. connected TV marketplace grew 748% year-on-year in Q2/18 and there are forecasts that the connected TV market in the UK will double between 2016 and 2020. This shows that programmatic TV is a force to be reckoned with. Brands and their agencies should work collaboratively with tech, strategic and creative experts in order to develop successful campaigns that make full use of the opportunities programmatic provides. And in order to achieve truly advanced TV buying, advertisers need to layer their first-party data on top of the automated buying to improve their targeting.