Card House hot global Netflix how to rely on big data to achieve the counterattack

Source: Internet
Author: User
Keywords Big data behavioral data
Tags analysis behavioral data big data broadcast data how to kill netflix

Thirteen years, "Card House" is now a hot worldwide. This big data "count" out of the TV series, contains the choice of 30 million viewers, 4 million comments, 3 million thematic search. In the end, what to shoot, who to shoot, who to play, how to broadcast, are determined by the objective preferences of tens of millions of viewers. Netflix is ​​behind the "House of Cards," a successful case of using big data to kill a director.

Netflix analyzed the data and found that users liked Fincher (social network, director of seven sinners) and knew that Spacey starred in the film. They also learned that BBC's Solitaire House was very popular in 1990 and decided to spend 100 million U.S. dollars Put

However, Netflix was once a rat on the stock market. It plummeted from 298 U.S. dollars to 52.81 U.S. dollars about 18 months ago.

Take a look at Netflix how to counter the big data.

1, a product change a company.

"Solitaire House" has become the highest-rated episode, attracted investors Netflix first quarter earnings strongly curious, finally revealed the bottom of the puzzle, Netflix's profit from 1.02 billion US dollars last year also increased by 18 percentage points. Netflix also reaped 2 million paying subscribers in the United States and its share price soared back above $ 200, making it one of the best performers this year.

2, digging the user's behavior data.

Netflix has 27 million subscribers in the United States and 33 million worldwide. Generating more than 30 million actions per day, such as when you pause, play back, or fast forward, Netflix subscribers give you 4 million daily ratings and 3 million search requests.

3, geek-style CEO.

In December 2005, Hastings convinced Netflix scoring system to provide all the necessary information to the user preference forecasting system, while others in the company insisted that scoring systems alone were not sufficient and that other reference metrics were needed, such as when users clicked on video And the interval between the end of play, such as what stars the user is searching for. Hasting flirtatiously, Hasting spends two weeks on his Christmas holiday composing an Excel spreadsheet - he wants to write a recommendation algorithm that defeats other engineers 'approval based on a million users' ratings. He lost, but inspired him to set up the "Netflix Award," a $ 1 million bonus to encourage individuals or teams to refine the scoring system's algorithms.

4, harsh test.

Netflix always have endless testing. Testing is usually done - selecting groups of people from tens of thousands of users and testing them like doing a mouse experiment. Netflix lets a group of users create avatars for their own family members, giving them personalized rewards in return for reward. Another group of users who watch Netflix through Sony PS will receive a voice greeting and be asked what they want to see.

5, manage the user and television 10 inches.

Although Netflix has a very wide range of sources, many of them are obsolete and have limited appeal. The Netflix in order to make their services look more value, be regarded as under the full effort. For example, Netflix will look at the difference in viewing distance for each of the different devices, and how much resolution should be adjusted for best viewing. One Netflix mathematician is called a "10-inch designer," because the mathematician's responsibility is to control the resolution of the video so that it plays on the television (typically 10 inches from the television) Cinema comparable. Similarly, there are also employees who specialize in the best video resolution on notebooks and tablets.

6, predict the user's heartbeat.

"We use this predictive system to ensure that users see what they want before they say what they want." These daytime episodes all play part of the Netflix calculation late into the night. It needs to know which part of the hottest movie in a certain area was on that day and prepare it for the next day in advance. For example, if the Barttlestar Galactica is on fire Tuesday in Houston, Houston's Texas-based servers will pre-load more episodes for Wednesday night's preparation.

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