During-the-top (OTT) media, which uses artificial intelligence and machine learning at the forefront, has changed the game in the media sector over the last several years.

It allowed viewers to access streaming data anywhere, anytime.

It bypassed cable, broadcast, and satellite TV platforms, allowing more cost-effective marketing directed toward hyper-targeted audiences.

Another interesting fact here is that OTT platforms helped us survive the pandemic when we only had limited outdoor entertainment options and mandated social distancing. 

To date, OTT platforms like Netflix, Hotstar, and Amazon Prime consistently keep their viewers engaged by providing what their viewers want to see.

AI-Powered Personalization as a Retention Tool For Your OTT Services

Today OTT platforms can easily understand what their viewers are looking for. With this valuable knowledge, they create content based on their preferences. 

We are now witnessing an OTT revolution. It has already taken off. 

Have you ever wondered how it all works? The answer lies in AI-powered personalization.

• Here the customer data & insights are utilized with the power of artificial intelligence. 
• The AI ​​engine learns from past customer data and trains itself to predict behavior. It delivers relevant content to users based on their needs and interests. 
• Companies use real-time behavioral and customer data to create highly contextual and relevant content.

The extensive list of recommended movies and TV series from leading OTT platforms is a great example of AI-powered personalised user experience. Its recommendations are based on an algorithm that accumulates data. 

OTT platforms may recommend content based on your viewing history and preferences.

The data-driven insights about your audience and their interests can give you an edge over competitors and deliver a seamless customer experience.

AI also helps prevent issues like video buffering and data loss.

Moreover, by continuously learning from customer experiences, AI can help create better and more engaging experiences for audiences. 

The five R’s of OTT Personalization

• Recognize: Identify users, including demographics, geography, and expressed interests.
• Remember: For future analysis, remember user preferences, viewing patterns, and habits.
• Recommend: Recommend what users want to see based on their behaviour, preferences, and interests.
• Relevance: Suggested content should be relevant to the user’s location, preferred language, and time of year.
• Reinforcement: Record user reactions to recommendations and use additional analytics to recommend better.

How the OTT King Netflix Uses Machine Learning?

Netflix, the king of the OTT, has come a long way since its humble beginnings as a movie distribution company in 1997.

Today, the company maintains its dominance with a massive 200 million dollar market share—Users (worldwide). 

However, only some of you know that the online video streaming giant owes much of its success to machine learning, big data, and analytics long before others realise its importance in global business scenarios.

Among the many OTT platforms and video content providers, Netflix stands out.

According to sources, nearly fifty million viewers worldwide watch sports, games, shows, and movies through this OTT video streaming service platform.

Like its other video streaming rivals, Netflix chooses to amp up its style of play by focusing on AI and machine learning.

Whether it’s content creation, curation, or user experience, machine learning is at the forefront of this platform.

Netflix Thumbnails

The video streaming platform showcases compelling images related to popular shows and actors to increase click-through rates.

With the proper implementation of ML, Netflix has acquired a huge database or catalog of shows or videos you wish to watch on the platform.

This schedule is automatically created by an ML process powered by Netflix based on viewer preferences.

Netflix also consistently chooses a consistent image based on user preferences.

Homepage

The Netflix website exemplifies the effective and efficient application of machine learning. In addition, it uses machine learning to recommend movies and games.

Netflix Recommendation System

The recommendation algorithm used by Netflix is powerful. Users can receive personalised advice from the platform.

Also, Netflix collects data based on preferences and later uses that data to find content that interests you. 

Streaming Quality Of Ott Platforms

Netflix continues simplifying its streaming video service based on user preferences and viewer information derived through artificial intelligence and machine learning.

In addition to video quality aspects, the platform also uses data to improve load times for shows, games, and movies. Moreover, it uses user data to measure and simplify the architecture of well-known OTT platforms.

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