TV Data Revolution: The perfect Cloud TV Platform
As consumers have embraced the anywhere, anytime viewing capabilities of video streaming — first on their computers and then on their smartphones, tablets and connected TVs — they’ve applied a similar standard to over-the-top (OTT) services. They expect to get the same quality of experience as when they turn on the television in their living room. The future of OTT will not only meet this expectation but exceed it, offering a seamless, personalized streaming experience for each user. Content offering and quality of service will be tailored to the habits and preferences of each individual viewer. Innovation is the cornerstone of video streaming, and as technology evolves, OTT services of the future will provide an engaging viewing experience unlike anything we know today. All of this thanks to consumer engagement data.
What does it take to build the perfect Cloud TV Platform?
TV has long set the standard for quality in-home video experience. We are coming out from a phase in video and entertainment media when experiences were living room-centric and scheduled. In the present circumstances generated by the COVID-19 pandemic, we are seeing an acceleration of trends that had begun to appear just before it, with consumers demanding new experiences that are easy-to-use and multi-screen, on demand anytime and anywhere. Of course, this raises many challenges on how to maintain the same level of quality and improve user experience that viewers had become accustomed to, sitting on the couch in their living room, and watching paid TV.
Customers are now demanding the same quality to scale to integrate all these new features to blend the agility of OTT streaming, openness, creativity in the business models device, reach personalization, etc. So, the question here is, what does it take to meet customer expectations of the perfect Cloud TV platform?
Everyone is pursuing the same old goal: to build a powerful Cloud TV service that offers reliable connectivity, multi-screen experience, cost extensive library of content and scalability to grow their service as their audience grows, typically across borders and to multiple countries. They also will want to aggregate other content providers’ main technology variables to be successful in building out a Cloud TV service.
When we look at end users, basically what do they want? As with paid TV, they want to go into the living room, sit on the sofa, turn on the TV and receive the content. They do care about all the features that we provide them, they care about personalization, but at its essence they want to stream and to watch the content they want, when they want it. So your system has to be reliable, it should be scalable and adaptable to all kinds of things that can happen during the streaming of content.
So for example, in the event of a major news break or sports event, you can suddenly have a burst of users. Let’s say it’s 9 p.m, the game is starting and viewers turn on the TV to watch it. For us, as the people who provide the technology, we need to expect a sudden burst of users that could be like 10 times more than what we would have at a regular time, and go into the millions of people if it’s a huge event; this is when you need the system that can scale very fast in all kinds of ways and use data in order to understand when and how much to scale. There are different kinds of techniques that can be used to build Cloud TV, such as containers and kubernetes and capacity planning for parts, and again, this relies on a lot a lot of data that that needs to be constantly monitored to understand what happened before, what kind of user flows are going to happen and how can you better react in order to handle those bursts. Your system needs to be robust.
When you fully understand your customer’s expectations, you know that there are things that they will tolerate, like a glitch in adding content to a favorites list, but missing the game because there’s a problem…. this is the kind of issue viewers don’t accept and may even cause them to ask for their money back or cancel their subscription, or even churn from the service, which you definitely don’t want to happen. So when we say robust, we’re talking about the ability to detect problems super-fast, and also how we handle them. Sometimes the answer is not to fix, but to mitigate, to find a way to allow that 99.999 percent to continue viewing the content through all kinds of caching mechanisms by again, using data to understand what you want to cache and how to keep the service going even when there’s a hitch in your system.
Another crucial aspect is the ability to update the service. Within the whole architecture of micro services, you want to be able to roll each one out separately, if you have an issue there or you want to change something. You want to build a real Cloud TV that can scale very rapidly and fix itself if there’s an issue. And then of course, there’s the level of the user experience, and the speed of personalization and ability to discover content: which content you promote to your customers using all kinds of techniques, pushing the right content for each segment of users. And this is again based on a lot of data research to understand what each customer wants to do, and then knowing what content to promote.
So basically, scalability, reliability and automation of the different operations, using data to achieve these three goals are in summary some of the key elements that drive today’s state-of-the-art cloud TV.
To know which are the obstacles to growth and which variables have an impact on UX and ott streaming and digital media services growth, what impact would 5G have on this and what will the future evolve on the super aggregation strategy take a look to our Whitepaper: The Perfect Cloud TV Platform
