Big Data outcome Part 2

Week 9 (19/05)

 

This is the final Week of my big Data Blog Where it will go over the Last Topic which is Topic 21: Applications of BIG Data techniques to a problem. This last topic will cover the sub topics of Designing profitable creative content and designing targeted advertising.

 

Topic 21

Applications of Big Data  techniques to a problem

 

As  My search about netflix in the previous topic 18 Big Data and Netflix go hand in hand, This topic will go indepth about how netflix truely uses the big data. How they started, their own original series and how they've used their big data to help them prosper.

 

 

 

History of netflix

Netflix started as a similar business to BlockBuster which being a dvd rental company But what seperated Netflix from BlockBuster is their methods, while blockbuster was a in person video rental store where people could look at their stock rent a dvd and had to return it by a specific date, Netflix on the other hand had decided to go with a subscription based model where customers would subscribe pick a DVD and have it mailed to them.Before 2007 Nexflix had offered to block buster 50 million dollars to buy them to get a jump start in the online video streaming platform as they were hemorrhaging more money than they had but blockbuster had declined the offer. One of many blunders which pushed block buster futher into their quick spiral into bankruptcy.

 

 

 

 

Netflix Originals 

Netflix uses its big data analytics when creating their own original shows or series. The biggest case of Netflix using big data for its shows its the american remake of house of cards. House of cards originally a british TV series hosted on BBC 1 which was a political drama. Netflix had seen the success of the UK version and had decided to risk it an make an american version of it. Which had costed over 100 million dollars which was a big risk for netflix. Using big data netflix had used their analytics to know that alot of their subscribers had watched the orginal version and that had also liked watching movie with kevin spacey as the protagonist so netflix using this data had put kevin spacey as the lead role in the series  which lead to the series getting 6 seasons.

 

 

 

 

 

 

 How netflix uses  Big data to push futher

 As shown Topic 18 Netflix uses Big data analytics They use their analytical data to determine what their subscribers do, this can include pausing and unpausing,skipping parts of a show,stop watching a showm skip an episode of a show, ratings, search, scrolling and even what device your watching the show from. all this analytical data helps netflix determin what works for them and what doesn't. by using this data netflix can focus into a specific area which can get them money 

designing target advertising

 Designed targeted advertising is a method of targeted advertising which uses big data analytics and sources to target specific individuals with advertisments which shows things which they might like, might of bought or searched for but didn't buy all in a veign to get users to click on the ads. Many companys use Targeted advertising But for this Blog I will be focusing on how facebook uses designed targeted advertising, facebook has multiple methods of analyzing user data these methods include

 

 

 

Tracking Cookies

 Tracking Cookies allows for Facebook to Track its Users across the web, Once a user logs in they can track what they are doing, so if a user is also browsing on other sites facebook can use these cookies to figure out what sites their on and start to gather a data base on what the user likes to then use that data to do targeted advertising

 

 Facial recognition

 A more recent investment facebook has made is in the facial recognition and image processing fields, this allows facebook to track users across the internet and on other facebook profiles with its image recognition system which is provided via user sharing,

 

 

Tag suggestions

 Facebook allows users to tag in photos aswell as suggests people to tag which uses its facial recognition software along with its image processing

 

Like analyzing 

FaceBook uses Posts Likes to catagories information from its users as a study from cambridge university found out that the pattern of facebook likes can accurately predict users sexual orientation, statisfaction with life, intelligence, emotional stability, religion, alochol and drug use, relationship status, age, gender, race and even politcal views.

 

https://www.cam.ac.uk/research/news/digital-records-could-expose-intimate-details-and-personality-traits-of-millions

 

 

 

 

 Downsides

 

With facebook harvesting so much data from its user is its privacy converns. As users don't know how or what truely facebook is doing with their data. As facebook has had many mishaps with users datas