Netflix, which has around 33 million subscribers, said that many of its members found the five-star rating system confusing. It's not a measure of overall popularity, but rather based exclusively on your individual viewing habits, behavior and ratings you've provided. They've always reflected what Netflix predicts a particular viewer will enjoy - and they've never represented an average user rating, the company said.
Not only are thumbs easier to understand, but ratings activity increased by 200% when Netflix replaced stars with thumbs in testing.
Stars were not meant to be a reflection of popularity so that's why Netflix had to come up with a new system that could provide better matches to suit the style of shows and movies that you enjoy watching. Choose thumbs-down and Netflix will stop suggesting it. However, Netflix explains that this isn't how its star ratings worked, and that rather than showing the overall quality of the show, they were created to show users to what degree the content was relevant to them.
The new system gets at the heart of the way the streaming-video giant approaches ratings and reviews.
"This is the promise of internet TV", said Cameron Johnson, director of product innovation at Netflix, "that you can choose what you want to watch". Give a show or movie a thumbs down, and Netflix knows not to recommend it to you again. The higher the percentage score next to a title - say, 95% - indicates how likely you'll like the title, in Netflix's calculations.
This allows Netflix's algorithms to tailor its suggestions to your tastes, using your personal ratings to find better matches.
Netflix first introduced the new rating system to hundreds of thousands of new Netflix users across the world past year. The Thumbs are the key to refining those predictions: They're created to let users give direct, immediate and uncomplicated feedback about the recommendations Netflix is making.
This is all created to provide a better experience for Netflix subscribers because the new system will allow for better and more personalized recommendations. This means as you continue to rate more content, you'll see even better recommendations over time.
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