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You Are Watching Netflix—and Netflix Is Watching You
Netflix is one of the biggest names of the Digital Age. It went from being a new way to rent movies, to a streaming service aggregating everyone else’s movies and TV shows, to being a powerhouse creator of original content in its own right. Oh, and it killed a one-time giant Blockbuster along the way and helped spawn a whole new branch of the entertainment world. However, it’s fair to ask if Netflix is really about making movies and TV shows. Is that really their main concern? The answer of course is ‘no’. The company is primarily about making money and for that, they need subscribers and in order to get the largest number of subscribers possible, they make use of a lot of data.
Naturally, they start with what they hope you want to see and basically spam your feed with a bunch of generically popular content. Over time, they will try to narrow it down. How do they do that? They make use of algorithms to gather information on what you watch. They also pay attention not just to what you click on, that is both too simple and not terribly informative. How many times have you clicked on a movie only to get about ten minutes in and decide you don’t want to watch it? The algorithms pay attention to that as well. What you watch, how long you watch it for, when you watch it, and all of that goes into the algorithm. From there, Netflix’s hope is that they will be able to find similar movies and put them in your recommended feed. Sounds simple doesn’t it? Yes and no.
For one, there are holes in this system. Not just the occasional recommendation you would never plan on watching but major problems that can break the algorithm altogether. Say you have roommates and you all share an account but also have very different tastes in movies? Or you have kids. Chances are you watch different things when they are around. That of course is what the profiles on Netflix and every other streaming service are all about. If they can break out each person individually, the algorithm has a chance to work. However, how many people really bother with the different profiles? I’m guessing it’s not as many as Netflix would like. Also, what if you have a busy schedule and rarely have time to watch a full two hour movie? You only have fifteen minutes here, twenty minutes there and typically work on something while the movie is on. So it might take a whole week to watch one movie. That kind of person likely wrecks the algorithm entirely.
Not to mention, how long does it take to build up a worthwhile profile of a given subscriber? One week? A month? A year? It will vary from person to person based on how much they watch, meaning how effective the recommendations are will vary a lot from one subscriber to the next. In short, Netflix’s algorithms are extremely inefficient in a variety of circumstances, and that means they are wasting time and money building user profiles that don’t work.
What should they do then? What would be a more efficient means of building those user profiles? Netflix could work with us at TARTLE. They could go directly to subscribers and ask what it is that they would like to watch. Who their favorite actors and directors are. When do they watch? Do they prefer movies or series? Do they like their series dumped all at once or would they prefer a weekly schedule? Netflix could talk directly to its subscribers and get feedback directly from them and so build a far more accurate profile than any other method. This would be faster and cheaper and in the end far more financially rewarding. Which means they could spend that extra time and money making better content to draw in more subscribers.
What’s your data worth? www.tartle.co
Tcast is brought to you by TARTLE. A global personal data marketplace that allows users to sell their personal information anonymously when they want to, while allowing buyers to access clean ready to analyze data sets on digital identities from all across the globe.
The show is hosted by Co-Founder and Source Data Pioneer Alexander McCaig and Head of Conscious Marketing Jason Rigby.
What's your data worth?
Find out at: https://tartle.co/
YouTube: https://www.youtube.com/c/TARTLE
Facebook: https://www.facebook.com/TARTLEofficial/
Instagram: https://www.instagram.com/tartle_official/
Twitter: https://twitter.com/TARTLEofficial
Spread the word!
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By TARTLE
5
88 ratings
Netflix is one of the biggest names of the Digital Age. It went from being a new way to rent movies, to a streaming service aggregating everyone else’s movies and TV shows, to being a powerhouse creator of original content in its own right. Oh, and it killed a one-time giant Blockbuster along the way and helped spawn a whole new branch of the entertainment world. However, it’s fair to ask if Netflix is really about making movies and TV shows. Is that really their main concern? The answer of course is ‘no’. The company is primarily about making money and for that, they need subscribers and in order to get the largest number of subscribers possible, they make use of a lot of data.
Naturally, they start with what they hope you want to see and basically spam your feed with a bunch of generically popular content. Over time, they will try to narrow it down. How do they do that? They make use of algorithms to gather information on what you watch. They also pay attention not just to what you click on, that is both too simple and not terribly informative. How many times have you clicked on a movie only to get about ten minutes in and decide you don’t want to watch it? The algorithms pay attention to that as well. What you watch, how long you watch it for, when you watch it, and all of that goes into the algorithm. From there, Netflix’s hope is that they will be able to find similar movies and put them in your recommended feed. Sounds simple doesn’t it? Yes and no.
For one, there are holes in this system. Not just the occasional recommendation you would never plan on watching but major problems that can break the algorithm altogether. Say you have roommates and you all share an account but also have very different tastes in movies? Or you have kids. Chances are you watch different things when they are around. That of course is what the profiles on Netflix and every other streaming service are all about. If they can break out each person individually, the algorithm has a chance to work. However, how many people really bother with the different profiles? I’m guessing it’s not as many as Netflix would like. Also, what if you have a busy schedule and rarely have time to watch a full two hour movie? You only have fifteen minutes here, twenty minutes there and typically work on something while the movie is on. So it might take a whole week to watch one movie. That kind of person likely wrecks the algorithm entirely.
Not to mention, how long does it take to build up a worthwhile profile of a given subscriber? One week? A month? A year? It will vary from person to person based on how much they watch, meaning how effective the recommendations are will vary a lot from one subscriber to the next. In short, Netflix’s algorithms are extremely inefficient in a variety of circumstances, and that means they are wasting time and money building user profiles that don’t work.
What should they do then? What would be a more efficient means of building those user profiles? Netflix could work with us at TARTLE. They could go directly to subscribers and ask what it is that they would like to watch. Who their favorite actors and directors are. When do they watch? Do they prefer movies or series? Do they like their series dumped all at once or would they prefer a weekly schedule? Netflix could talk directly to its subscribers and get feedback directly from them and so build a far more accurate profile than any other method. This would be faster and cheaper and in the end far more financially rewarding. Which means they could spend that extra time and money making better content to draw in more subscribers.
What’s your data worth? www.tartle.co
Tcast is brought to you by TARTLE. A global personal data marketplace that allows users to sell their personal information anonymously when they want to, while allowing buyers to access clean ready to analyze data sets on digital identities from all across the globe.
The show is hosted by Co-Founder and Source Data Pioneer Alexander McCaig and Head of Conscious Marketing Jason Rigby.
What's your data worth?
Find out at: https://tartle.co/
YouTube: https://www.youtube.com/c/TARTLE
Facebook: https://www.facebook.com/TARTLEofficial/
Instagram: https://www.instagram.com/tartle_official/
Twitter: https://twitter.com/TARTLEofficial
Spread the word!