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How Netflix's AI Saves It 1 Billion Every Year Fox Business

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When you think of leaders in artificial intelligence, Netflix doesn't usually jump to the top of the list. But the streaming video service's VP of Product Innovation Carlos Uribe-Gomez and Chief Product Officer Neil Hunt published a paper that says some of its AI algorithms save Netflix 1 billion each year. In their paper, the two Netflix execs detail how the company's recommendation engine impacts its churn rate. Netflix no longer reports its churn rate, but the paper notes that Netflix's "retention rates are already high enough that it takes a very meaningful improvement to make a retention difference of even 0.1%." Let's dive into how the recommendation engine saves Netflix money -- and what the return on investment looks like.


How Netflix Saves 1 Billion A Year Using AI - ValueWalk

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Netflix does not usually jump to the top of the list when one thinks of leaders in artificial intelligence, but Netflix's VP of Product Innovation, Carlos Uribe-Gomez, and Chief Product Officer Neil Hunt published a paper informing investors that some of its algorithms help them save 1 billion each year. In the paper, the two executives detailed how the company's recommendation engine impacts its churn rate. The video streaming giant does not report its churn rate, but the paper mentions that the Netflix's retention rates "are already high enough that it takes a very meaningful improvement to make a retention difference of even 0.1%." This year, the streaming giant plans to spend 6 billion on content. With such a big investment, it could get all sorts of TV series and movies, but if it just presents the most popular selections to everyone, many titles would remain unseen.


Is Artificial Intelligence Controlling What You Stream on Netflix, Hulu? – ThomasNet News

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Sign up here to get the day's top stories delivered straight to your inbox. The routine is familiar now. Off from the day, lounging on a couch, ice cream at the ready, the remote or mouse clicks onto the preferred streaming site, perhaps to watch the show everyone is talking about or to be reacquainted with an old favorite. Streaming television and movie services are so deeply ingrained in the quotidian now, binge-watching is a common weekend activity and there are colloquial dating terms that invoke them -- "Netflix and chill." People log onto Netflix, Hulu, and other streaming services at all times of the day: during their commute; in the morning while getting ready; and when curling up at night.


The ROI of recommendation engines for marketing

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Netflix's long list of suggested movies and TV shows is a fantastic example of a personalized user experience. In fact, about 70 percent of everything users watch is a personalized recommendation, according to the company.


Recommendation Engines: How Amazon and Netflix Are Winning the Personalization Battle

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Customer experience personalization is all about data first. Get the data right and you can shape the overall customer experience by applying data science and machine learning. Recommendation engines are very powerful personalization tools because it's a great way to do "discovery" – showing people items they will like, but are unlikely to discover by themselves. They improve a visitor's experience by offering relevant items at the right time and on the right page. In the immortal words of Steve Jobs - "a lot of times, people don't know what they want until you show it to them."