Post by account_disabled on Dec 9, 2023 0:39:16 GMT -5
After all, from the scripts, characters, trailers and even every image that appears on your screen, they are facts based on data analysis and recommendation algorithms. Some people, like me, believe machine learning algorithm that writes a script with everything that certain audience wants to see, making it possible for directors to be much more more creative, through a good Big Data update. According to what I learned in the presentation by Michelle Ufford, Engineering Manager at Netflix, in October 2016 the company had 86.7 million members, supporting more than 1000 types of input devices (smartphones, tablets) and more than 125 million hours watched per day.
It currently has more than 125 million users. Today that number is probably Phone Number List much higher, and you can clearly notice that the content is increasingly segmented, bad movie recommendations are becoming less and less, and the user experience and usability improves every day. Netflix co-founder Reed Hasting often says that when you are going to guide someone on the use of data, you need to use Analytics, directing you towards focus, analysis and money. By studying the use of predictive analytics in the company we can conclude some of its applications. Therefore, your data sources consist of: Your experience when watching the content: You probably return to a scene, advance in an episode to see the end or pause the series at a certain moment.
The exact moment in which you see content: knowing the exact date and time in which its clients use its services allows the company to know much more about its users; The device on which you use Netflix is also very important to understand user habits; Yes, the company also uses machine learning and data analysis applications for its UX and UI. Knowing the browsing behavior of users along with the launch brings many insights; Perhaps one of the most important variables on Netflix is the rating that users give to movies. The company at one point discovered that two buttons, one for like and one for dislike, provide much better information than the 1 to 5 rating.
It currently has more than 125 million users. Today that number is probably Phone Number List much higher, and you can clearly notice that the content is increasingly segmented, bad movie recommendations are becoming less and less, and the user experience and usability improves every day. Netflix co-founder Reed Hasting often says that when you are going to guide someone on the use of data, you need to use Analytics, directing you towards focus, analysis and money. By studying the use of predictive analytics in the company we can conclude some of its applications. Therefore, your data sources consist of: Your experience when watching the content: You probably return to a scene, advance in an episode to see the end or pause the series at a certain moment.
The exact moment in which you see content: knowing the exact date and time in which its clients use its services allows the company to know much more about its users; The device on which you use Netflix is also very important to understand user habits; Yes, the company also uses machine learning and data analysis applications for its UX and UI. Knowing the browsing behavior of users along with the launch brings many insights; Perhaps one of the most important variables on Netflix is the rating that users give to movies. The company at one point discovered that two buttons, one for like and one for dislike, provide much better information than the 1 to 5 rating.