How Netflix Uses Big Data to Drive Success
Netflix has over 100 million subscribers in the past nine years since its founding; the online streaming platform Netflix has turned the film and television industry on its head. With that comes a huge amount of data they can analyze to improve the user experience.
Big Data has helped Netflix to become the king in online streams.
If you have a Netflix subscription understands the process of finding a movie or TV show to watch. For Netflix user it has unique sets of options with Netflix, putting a lot of effort into ensuring you find something to watch quickly. This differentiates Netflix from other online streams.
Let’s see how Big Data helps Netflix
Big data helps Netflix to decide which programs will be of interest to the user and the endorsement of the system actually influences 80% of the content that user watches on Netflix.
The Netflix even gave away a $1 million prize since it has been founded to the group who came up with the best algorithm for anticipating how customers would like a movie based on previous ratings.
Algorithms help Netflix to save $1 billion a year in value from customer retention it is an eye-opening figure in the entertainment industry.
Finding the next smash-hit series with Big Data
Netflix has arranged itself as a content designer, not just a distributor for movie studios and other networks.
Big Data enabled Netflix to spend $100 million on 26 episodes of the House of Cards, as they were confident the show could be marketed successfully to their audience.
They know it would appeal to the fans of the originals British “House of cards” and the built-in fan bases for director David Fincher and actor Kevin Spacey.
The ultimate strategy which Netflix hopes to improve in the number of hours those customers spends using its service.
Big Data in Personalized video ranker
Netflix collects information for each member profile in a personalized way.
The same genre now for each member has an entirely different selection of videos.
These rows are based on genre, with headers like “Suspenseful Movies”.
Big Data algorithm orders Netflix’s catalog according to the user tastes and the resulting order is used to select the order of videos in a particular genre and in the other rows as well.
Big Data algorithm in Top-N video ranker
This algorithm of Big Data analyzes the best few personalized recommendations in the entire catalog for each member.
It focuses on the top of the rankings, unlike PVR which looks at the ranking for the entire catalog.
Big data in Trending Now
In “Trending Now” Big Data hones in on short-term trends, spanning anywhere from a few minutes to a few days.
It takes into account unique personalized metrics and teases out two types of trends – those that repeat at regular intervals, such as an uptick of romantic films around Valentine’s Day, and one-off events, like a hurricane, that drive sudden interest in documentaries about natural disasters.
Big Data in Continue Watching
“Continue Watching” is the list of shows the user has not completed watching.
Big Data sorts the recently viewed titles based on Netflix’s best estimate of whether you intend to resume watching, or if you’re just going to abandon the title.
Big Data considers factors such as time elapsed since viewing, whether you stopped watching in the middle, beginning, or end, or whether different titles have been viewed since.
Big Data algorithm in Video-video similarity
Finally, the “Because You Watched” row anchors its recommendations to a single video. This video-video similarity Big Data algorithm, as it is called, helps drive this list.
Big Data algorithm that generates a ranked list of videos for every video in Netflix’s entire catalog.
But even though the ranking itself is not personalized, the anchor video which makes it to the homepage is, as is the subset of BYW videos recommended.
Netflix is just one example of how Big Data helps us make simple viewing choices and how Big Data
has influenced the entertainment industry in a big way. The applications of Big Data
are many fold.
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and Data Analytics
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