How Netflix Measures Customer Preferences by Using Big Data? | BazingoInc

How Netflix Measures Customer Preferences by Using Big Data?

In the fourth quarter of 2017, Netflix reached to 117.58 million streaming subscribers worldwide. Out of these subscribers, 54.75 million subscribers are from US alone. The figure is huge as it shows the increasing popularity of Netflix medium.

Getting such wealthy data also gives Netflix an opportunity to utilize data insights for better customer experience.

People complain about spending so much time online but how come Netflix manages to keep its audiences hooked? And, how it handles millions of users’ data to drive success?

Visualization and assessment of data value is where Netflix is very strong.

With more than 130 million hours of watching every day, no doubt Netflix has changed the way we used to watch our favorite movies and shows. Although, churn rate of Netflix was 9% in 2016 but it may raise because of increase in prices as the company is expected to have more of original content.

However, let’s focus on how Netflix is clever enough to know all our preferences and never let us get out of its influence.

Netflix Stats

  • Netflix saves $1 billion through its algorithms from retaining customers.
  • On average of 60-90 seconds of choosing something to watch, a member loses interest.
  • 80% of the Netflix streaming is affected by the recommendation it offers.

How Netflix Collects Massive Amount of Behavioral Data?

Some of the typical events Netflix evaluates data are:

  • Ratings
  • Searches
  • Date movie/show watched
  • Device on which movie/show was watched
  • Nature of shows variations depending upon device
  • When the show/movie paused
  • Which movies/shows are being re-watched
  • Do people watch credits

How Netflix Evaluates Big Data?

1- Takes deeper insights into preferences

Original shows of Netflix are what makes it one of the obvious choice when it comes to movies/shows streaming. Fan favorites like Stranger Things, House of Cards, Orange is the New Black etc. Netflix keeps its tabs open on its user base.

Following data is being considered:

1-Number of users who watched the show
2-Number of users who watched the entire episode
3-Gap between 2 episodes being watches by a user
4-Pause, rewind and fast forward data collection
5-At which day of the week user watches the show
6-Date and time user watches the show
7-Searching habits of a user

Take an example of House of Cards. Netflix worked on a hypothesis. First, David Fincher’s ‘The Social Network’ was watched by large number of users. He is also the director of House of Cards. Second, Kevin Spacey movies do good business. Third, there were different trailers of House of Cards, one for Spacey fans, one for Fincher fans and one for female protagonists of the season.

2- Sends emails of the Newly Added Shows

Netflix has a vast content library and it would be stupid enough to not use such big data for user recommendations based on their choice.

Netflix doesn’t just collect data it actually uses it wisely. Based on existing customer viewing habits, it recommends newly added shows through emails.

Email format is simple yet functioning. User if likes the recommendations he can directly play it on the device or user can save it to his watch list.

3- Push Notifications, Opened Most of the Times

Most of us find it irritating to get push notifications but it totally depends on the interests of the user. Apart from suggesting new movies or seasons, Netflix also covers what new season of the old season is available.

Example, users when finished House of Cards, Netflix sent season 2 notifications to the users who were following season 1.

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