When I first sat down to write this post, I planned to focus on Netflix\u2019s success in utilizing user data to provide recommendations for users on what to watch. But the more research I did, the more I found out that this is just one of many examples of how Netflix uses data analysis in creative ways. From improving subtitles to choosing which movies to license, to even creating personalized trailers for their proprietary shows, Netflix is all over it.<\/p>\n
Did you know that Netflix collects all of this data about you every time you log on? (source: Kissmetrics)<\/em><\/p>\n Netflix recommendation system<\/strong><\/p>\n It\u2019s like that best friend who knows you love comedies and that last week you watched Zoolander and Groundhog Day. They don\u2019t think you\u2019ve seen School of Rock, so how about checking it out?<\/p>\n Netflix\u2019s proprietary recommendation system utilizes user data to provide personalized recommendations on other movies and shows to watch. When Netflix users first sign up, they are asked to fill out a short survey with their preferences and rankings on movies. Netflix then uses this, along with data collected about past viewings, to recommend movies and shows to users. This is a huge value add to the user \u2013 not only do they get recommendations on movies based on their preferences, but they also get exposure to films (sometimes older) that they otherwise wouldn\u2019t have even heard about. And hey, it works. Over 75% of viewing activity is driven by these recommendations.<\/p>\n Licensing movies<\/strong><\/p>\n How, you may ask, does data help Netflix decide which movies to license for their collection? Netflix\u2019s goal when deciding is to figure out what users will enjoy the most. For example, say a huge box office hit was just released, and would come at a very hefty price tag to Netflix. For the same price, Netflix could license 5 or 6 other movies by the same actors and\/or genres, and get a total user enjoyment of even more than what it would be with the box office hit. Jenny McCabe, Director of Global Media Relations, says that to do this,<\/p>\n \u201cWe look for those titles that deliver the biggest viewership relative to the licensing cost. This also means that we\u2019ll forgo or choose not to renew some titles that aren\u2019t watched enough relative to their cost.\u00a0<\/em>We always use our in depth knowledge (aka analytics and data) about what our members love to watch to decide what\u2019s available on Netflix\u2026.If you keep watching, we\u2019ll keep adding more of what you love.\u201d<\/em><\/p>\n Personalized trailers on proprietary shows<\/strong><\/p>\n Netflix has some incredible shows of their own \u2013 House of Cards, Orange is the New Black, and the list keeps growing. What you maybe didn\u2019t realize is how deep Netflix gets in using data to make these shows appeal to you, specifically you. For the launch of House of Cards, Netflix made ten difference trailers, and your viewing behavior dictated which of these trailers that you saw. You love watching Kevin Spacey films? You without a doubt say the trailer that featured him prevalently throughout. Well then of course you will want to binge watch this new series featuring your favorite actor, Kevin.<\/p>\n Conclusion<\/strong><\/p>\n Netflix\u2019s creative use of data goes hand in hand with their success thus far, and ultimately drives their user satisfaction and retention that will drive this growth going forward. Netflix will soon (if they are not there already) be able to compete with \u2013 and defeat \u2013 the HBOs of the world because they are able to capture and creatively utilize so many data points from their user.<\/p>\n","protected":false},"excerpt":{"rendered":" From improving subtitles to choosing which movies to license, to even creating personalized trailers for their proprietary shows, Netflix creatively uses data capture and analysis to satisfy, retain, and attract customers. <\/p>\n","protected":false},"author":27,"featured_media":0,"comment_status":"open","ping_status":"closed","template":"","categories":[655,776,1020,90,1021,55,497],"class_list":["post-2803","hck-submission","type-hck-submission","status-publish","hentry","category-data","category-data-analytics","category-movie","category-netflix","category-show","category-tv","category-watch"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/data-driven-value-creation-value-capture-and-operating-models\/","yoast_head":"\n\n