Netflix eliminated the 5-star rating system because most subscribers didn't understand it8
Netflix has announced today that it is no longer using its 5-star rating system that was supposed to show viewers how much they would enjoy watching a particular movie or television shows. The stars are being replaced by a percentage that is supposed to show the same thing. Netflix was forced to make this change because the 5-star system was misunderstood by most Netflix subscribers. It was never intended to be a rating that all potential viewers would use to determine whether or not to watch certain content.
To put it another way, the star ratings on Netflix were not designed to show you how popular a movie or show was to the Netflix audience. It was actually a prediction of how much you would enjoy content based on programs you've previously viewed on the site. For example, House of Cards might have a one-star rating when you looked it up, but for someone obsessed with politics, the show might have had 5-stars on its Netflix listing.
To make the concept easier to understand, Netflix is now using a thumbs up/thumbs down system. If you like a particular title that has been suggested to you and want to see similar suggestions, click on the thumbs up. A thumbs down means that you are not interested in this particular title and do not want Netflix to recommend to you any similar content ever again. Netflix is also adding a new personalized % Match score to each title. Based on algorithms that measure your viewing history on the app, the % Match score is a prediction that attempts to guess whether or not you will enjoy a movie or television show on Netflix. The higher the % Match score, the more you are apt to enjoy a particular title.
To show you how ingrained people's responses are to certain stimuli, consider that when Netflix tested the thumb up/down system, ratings activity soared by 200% Having said that, Netflix simply wants you to know that the more information you give the company about your individual tastes and likes, the more precise it can be when it comes to recommending video content for you to enjoy.