Rohit Kumar is responsible for Researchwire European & North American business. He is an HEC, Paris 2008 MBA and Indian Institute of Technology (IIT) Kharagpur 2002 engineering graduate with close to 17 years of experience in business innovation and strategy, business development and client relationship roles. He is working with ResearchWire since 2016 and as a partner, is responsible for the growth of ResearchWire in Europe and North America.
Prior to ResearchWire, Rohit was handling sales strategy and pricing for Syniverse Technologies, a telecom services provider, where he was instrumental for growth in EMEA and India through product innovations, creative pricing and discounting models and executing strategic sales plans.
Rohit is based out of Luxembourg and has been living in Europe for last 12 years. He understands European & North American customers and their needs and ensures that our customers always have a local person to reach out whenever needed.
When Disney launched its streaming service in 2020, it attracted 10 million subscribers in the first 24 hours from just the US, Netherlands, and Canada. We are in the midst of a streaming revolution. Media analysts predict that there will be nearly two billion active subscriptions to on-demand video streaming services in 2025, indicating a 65% increase over the end of 2020.
Cutting-edge technologies like artificial intelligence (AI) and machine learning (ML) allow OTT players to generate insights from the tonnes of user data that is available to them. From helping them recommend the right content to each user to enabling them to produce original content in line with the expectations of different demographics, AI and ML are all set to revolutionize how we consume entertainment.
The OTT market is expected to reach $194.20 by 2025. The primary engine for this growth will be traditional broadcasters who aim to compete with online video streaming giants such as Netflix, Hulu, Amazon Prime Video, etc.
Let’s see how AI/ML is transforming content production and delivery:
1. Content Production:
The 20th Century Fox collaborated with IBM to make the world’s first “cognitive movie trailer” for Morgan, a horror movie. It entailed training an AI that uses fantastic scenes from other horror movies and trailers to create a trailer that will pique the interest of horror aficionados.
From IBM: “There are patterns and types of emotions in horror movies that resonate differently with each viewer, and the intricacies and interrelation of these are what an AI system would have to identify and understand in order to create a compelling movie trailer. Our team was faced with the challenge of not only teaching a system to understand, “what is scary”, but then creating a trailer that would be considered “frightening and suspenseful” by a majority of viewers.”
The AI (coupled with the help of human editors) managed to do this in 24 hours. Creating a movie trailer without the assistance of AI takes anywhere from ten to thirty days. AI keeps getting better with time as it learns and adapts. AI can create new videos from content repositories, in real-time. They can even perfectly optimize it for release on different OTT platforms.
2. Provides a hyper-personal approach:
One of the biggest advantages of AI/ML technology in the industry is its capacity to push content specific to the interests of the consumer. If you display content to people based on their interests, they are more likely to watch it. It will drive content consumption. AI can be leveraged to determine the preferences of customers. The content they enjoy, the ones they skip, the genres that they spend more time on, movie durations that they prefer, etc. When OTT platforms use this information to drive content recommendations, it will result in hyper-personalized content and increase their happiness.
3. Acts as a retention tool:
There are hundreds of OTT platforms. Gaining the attention of consumers and keeping it that way takes a lot of effort. OTT subscriber churn rate in the US is as high as 44%. You need to be constantly pushing the right buttons to keep them interested in what you offer. If only platforms could seamlessly understand the requirements of a customer and recommend content based on each individual’s unique interests, isn’t it? Thankfully, AI has the capability to do just that.
What do you think an AI system is powered by? Data. The AI system learns from previous customer data and trains itself to understand patterns and predict customer behavior. It suggests content that is relevant to the users and their specific requirements.
You cannot send recommendations based on a single attribute alone. A 30-something female OTT customer from South Korea with a master’s degree who lives in Paris, France, might have a completely different movie taste from someone who shares the same attributes.
AI studies the specific customer’s behavioral and real-time data to create highly personalized recommendations. The insights that an AI engine provides help OTT platforms offer a terrific experience.
4. High-quality viewing across multiple media formats:
Interactive video-based digital content has a lot of takers because of the immersive experience that it offers. OTT platforms have already managed to offer seamless digital entertainment across multiple media formats. Some of the bigger OTT players leverage the seamless interconnectivity that allows them to watch content on screens that offer 4k and 8k resolution. With a boom in the sales of smart TVs, features such as ultra-high resolution, better picture quality, and an immersive experience will become a must-have.
Technologies such as augmented reality and virtual reality will create more opportunities for providing an immersive and experiential experience.
5. Content protection by blockchain:
Blockchain can help content creators and distributors in storing, classifying, copyrighting, and distributing digital content. The immutable public ledger will allow OTT platforms to create effective policies to restrict content from unauthorized users. It will reduce instances of piracy and protect against copyright infringements.
6. Short-form videos:
Bite-sized video content improves engagement by a huge factor. AI/ML engines can create highlights, teasers, recaps, key moments, and trailers to show the viewers what they can expect when they decide to watch a movie or show. This saves a lot of time for the consumers as they don’t have to sit through the content to understand if it will be of interest to them.
7. Video playback:
Data and speed requirements have significantly increased recently, especially with 4K video resolution coming into play. If the bandwidth is restricted, it can result in throttling, which creates a video buffering problem. AI technology can adjust the video quality based on the available network quality, without affecting the experience of the user.
It can even gauge the user’s favorite video quality and use that resolution whenever they are watching a video. By adapting content and services based on the data range available, AI and ML can provide richer and more engaging experiences for their audience.
8. Blending OTT platforms:
AI is disrupting the OTT ecosystem by blending the platforms. We will see platforms merging applications and functionalities. For example, YouTube is not just a video-watching platform, it can also be used as a messaging board, social network, video editor, and so on. In the immediate future, OTT platforms can also be used to engage fans. You will see video platforms that come with eCommerce integrations that allow you to make direct purchases. Live commerce combines entertainment with the ability to purchase items. It provides businesses, marketers, and OTT platforms an opportunity to generate revenue.
Combining the user base of social media platforms, content development, and streaming capabilities of OTT platforms can completely change the game.
How does Netflix use Machine Learning to its advantage?
Netflix is one of the most popular OTT platforms in the world. Let’s see how they use machine learning to provide their end-to-end video streaming solutions. ML helps Netflix design advanced prototypes, evaluate algorithms, improvise models, and experiment incessantly to come up with new ways to provide better service.
-
Netflix thumbnails:
The video streaming platform creates attractive graphics that are automatically generated by the ML process. It is created based on viewer choices. Based on the vast data of the shows or videos that you have watched on the platform, the ML system unifies the images.
-
Their homepage:
One of the brilliant use cases of ML on OTT platforms is Netflix’s homepage. As soon as you enter, you will find it filled with shows or movies that you are watching currently and recommendations that match closest to your viewing patterns.
-
Its recommendation system:
Users get personalized suggestions on the platform, through the ML engine. Reports say that its recommendation system saves them more than $1 billion a year.
-
Content delivery:
Netflix does pioneering work in content delivery. It has patents for technology that improves how content is delivered to viewers, decreasing data loss while improving stream quality, and reducing buffering.
- Choosing the location:
More than being just a streaming platform, Netflix is a production company. They produced 2,769 hours of original content in 2019, 80% more than that of 2018. The location at which the movies or shows are shot is important because it directly affects the bottom line too. Netflix uses machine-learning algorithms to determine the perfect shooting location for a particular show or movie.
The machine learning algorithms check the cost, schedule of the cast and crew, location shooting requirements, probability of getting shooting permits, weather, and other relevant factors. Their ML systems quickly find shooting locations that are the most optimal and feasible.
Wrapping up:
Consumption of entertainment through traditional media has reduced drastically, and there has been a huge shift to consuming content on OTT platforms. They provide an eclectic set of shows and movies and the accessibility to watch them from anywhere. It has also made entertainment consumption an immersive and engaging experience.
OTT platforms are fighting to improve their technological capabilities as much as for content. If one platform offers a better experience than the other, consumers wouldn’t hesitate to switch. The future holds exciting prospects for AI and ML in the OTT landscape.
If you are in the OTT space and are looking to take care of your inventions, Researchwire will be able to help you in the right direction. Get in touch with us and see the kind of difference we can make for your intellectual property.