How Netflix Implements Big Data Is All about You | Big Think

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  • čas přidán 31. 03. 2016
  • How Netflix Implements Big Data Is All about You
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    According to Netflix's VP of Product Development, there's a misconception about big data. It's not a treasure trove of information, as many people and their companies assume, but more like "a big mountain of garbage." The problem, as Todd Yellin sees it, is sifting through the data to find the information that will actually benefit users, and that data is few and far between.
    Yellin appreciates the simplicity of the subscription model on which Netflix depends. While making the on-demand entertainment company entirely beholden to their customers for success, unlike Google and Facebook which draw substantial revenue from advertisers, it simplifies their understanding of big data. Ultimately it means serving one master, the customer, instead of two.
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    TODD YELLIN:
    Todd Yellin started working at Netflix over ten years ago and his current role as VP of Product Innovation revolves around changing the way people find great streaming content to watch over the Internet on their TVs, computers, and mobile devices. He is responsible for leveraging vast amounts of data, sophisticated algorithms, and best-in-class user interfaces across numerous viewing devices to create an easy, compelling way for Netflix members to find something great to watch. He also oversees member acquisition and how to best leverage social and messaging.
    Before Netflix, as a documentarian, Todd became the only person ever to film Tibetan children escaping over the Himalayas; the footage was shown worldwide by Reuters. His written account was published in The Progressive and syndicated by the NYT. He also wrote/directed a short documentary for British TV on political oppression in Myanmar, which was broadcast throughout Europe.
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    TRANSCRIPT:
    Todd Yellin: So it's funny, big data has been kind of a cliché in Silicon Valley for the last few years: big data this, big data that. Big data is really one big mountain of garbage with little gems buried it in this tremendous trash heap, and you want to find those gems - you really want to find out what's going to make the experience better. So there are a lot of sophisticated machine learning algorithms that Netflix and other companies deploy to really figure out what are the gems that are going to make a better experience, and what's the rubbish that you want to separate out and push to the side? Once you find those gems, it doesn't make it a more alienated, machine experience - it actually makes it a more personal experience. It becomes much more about the individual member.
    When I first got to Netflix we were looking at other companies that were doing personalization and leveraging the kinds of data they couldn't learn from. And one company that obviously wasn't competitive with Netflix was also doing some interesting things was Pandora, the music company. And Netflix is in Silicon Valley and they're up in Oakland, not too far away, and we're down in the South Bay. So we went up to - we had a meeting, a little powwow, this was many years ago, with Pandora. And they were really small then and Netflix was much smaller and we were just comparing notes. What was interesting about Pandora is Pandora had the Music Genome Project where they were tearing apart and deconstructing lots of music on all these different dimensions and trying to really understand the music. And I remember back in these days, and this was like ten years ago, they had their walls lined with CDs all over and they had a whole line of people in this cramped office with headphones on and they were listening to music with this big spreadsheet open and tagging everything about it. ......
    To read the transcript, please go to. bigthink.com/videos/todd-yell...

Komentáře • 49

  • @neonshoji
    @neonshoji Před 8 lety +38

    A five minute Netflix commercial. Great.

    • @gib803
      @gib803 Před 8 lety

      +Neon Oni It was good though :)

    • @frank5520
      @frank5520 Před 8 lety +1

      +Neon Oni The "big" question is: Does Netflix have good intentions with these algorithms? They are very advanced and 99.98% of us will never know how much these algos know about us.

  • @keshavbx
    @keshavbx Před 8 lety +2

    Interesting comments about this video. Found it cool hearing about the inside story of how much work & research/collaboration went into creating such a widely used product.

  • @MrMurraypants
    @MrMurraypants Před 8 lety +14

    Here's an idea: let me, the customer, decide what I want to watch. Let me get rid of the rubbish that I don't. Brilliant, I know.

    • @Anonymous-x1x
      @Anonymous-x1x Před 8 lety +1

      +MrMurraypants How do you know if its rubbish if you don't watch it? Sure there's a lot of trash in there. But I found a lot of interesting shows and movies I never thought I'd watch.

    • @MrMurraypants
      @MrMurraypants Před 8 lety +3

      I'm also talking about the shows you've already seen but don't necessarily want to watch again. I'd be nice if there was a nice small x at the top right of the thumbnail. That's all I'm saying.

    • @frank5520
      @frank5520 Před 8 lety +1

      +MrMurraypants The "big" question is: Does Netflix have good intentions with these algorithms? They are very advanced and 99.98% of us will never know how much these algos know about us.

    • @Anonymous-x1x
      @Anonymous-x1x Před 8 lety

      Frank As far as I know Netflix only uses the algorithms pertaining to the things you watch. And I'd rather them know that information because with that they can put more money into producing shows like Daredevil, The Seven Deadly Sins etc. If you're worried about information gathering, companies pay for your information everyday online from the things you look at, to the things you purchase. They already have entire profile about YOU ever since you got online.

  • @rohanpandey2037
    @rohanpandey2037 Před 8 lety +6

    Don't know what's up with all the haters in the comments. It was really cool hearing about how big data works and what things media companies do to serve customers relevant information.

    • @kassim6154
      @kassim6154 Před 6 lety

      and honestly if they want sieve through 100's of shows without any recommendation to tell them what might be good for them, the putlockers are just next door

  • @MarkShaneHansen
    @MarkShaneHansen Před 8 lety +1

    Some people argue that it's unethical to use data on individuals to present them more precise ads... but why? If you see an advertisement, and think "Hey, I would enjoy owning and using that item", what's the problem? I feel like Google just did both the advertiser and the customer a favor.
    If someone buys anything they don't need or want just because an ad was shown to them... well, maybe they should work on that, because there are ads almost everywhere.

  • @daphnelun112
    @daphnelun112 Před 3 lety +4

    It always comes to 'if you are not paying for the product, you're the product'.

  • @timhorton7799
    @timhorton7799 Před 8 lety +1

    That was a big think. He is a big thinker

  • @voiceofaliens
    @voiceofaliens Před 8 lety

    Uhh.. wrong... google/facebook having to serve two masters is same as netflix. google/facebook have no product to sell customer, which is why they sell advertiser's product. Netflix _is_ the product for sale, so they serve not only customers but also themselves. Both models serve both product and customer.

  • @slugfly
    @slugfly Před 8 lety +1

    when I get ads, if not skippable, I skip the vids.

  • @Seftr
    @Seftr Před 8 lety +2

    You can tell every Big Think Netflix clip is filmed elsewhere, not on principle location. Bit fishy.

    • @littlesometin
      @littlesometin Před 8 lety

      +SeftR how can you tell?

    • @Seftr
      @Seftr Před 8 lety

      The format. The color correction. The visible grain in comparison to the others.

  • @Hogis__
    @Hogis__ Před 8 lety

    Well it works like shit in Finland. It always suggests mostly irrelevant titles for you, but the library here isn't quite as large as the one in the US, so it might not be right to only fault the data research . But I subscribe mainly for the exclusives and for occasional movie nights anyways, I'll find what I want regardless of the suggestions.

  • @PlasteredDragon
    @PlasteredDragon Před 8 lety +2

    Netflix's streaming selection is utter shit. Their "recommended for you" titles seem to be a list of whatever is newly available for streaming this month.

    • @Pleaseunderstand
      @Pleaseunderstand Před 8 lety

      +PlasteredDragon Not to mention it seems to be particularily biased towards Netflix originals.

    • @RantingRamsay
      @RantingRamsay Před 8 lety +2

      +PlasteredDragon It improves the more you rate things. If stuff pops up in "recommended for you" that you know you will not enjoy, rate it 1-star (or "hated it"). Make sure to rate things you really enjoy as 5-stars. The more you do this, the more your "recommended for you" section will present you with things you're likely to enjoy.
      I've had streaming Netflix for a few years now, and because of taking the time to rate things, very rarely does it suggest something I don't want to watch. Sure, it still happens occasionally, but when it does I just rate it 1-star and move on.

    • @PlasteredDragon
      @PlasteredDragon Před 8 lety

      RantingRamsay I've rated thousands of titles. It doesn't help. The selection is too poor to make a difference.

    • @RantingRamsay
      @RantingRamsay Před 8 lety +1

      PlasteredDragon Well, then all I can say is that our experiences have varied greatly.

  • @edsmelly
    @edsmelly Před 8 lety +1

    I just want to know who wrote the title to this vid? "How Netflix Implements Big Data Is All about You" ? Really? How about "Netflix's implementation of big data is all about you"? Or, "Netflix implements big data with you in mind"?

  • @What2expectinthehospital

    Netflix hardly gets new material. I routinely look for their new content especially under science fiction. Their content is either outdated or stinks with low stars.

  • @TheZeGamerNoob
    @TheZeGamerNoob Před 8 lety

    WTF, legit Uni teacher had a rant today all about this.

  • @michaelwinter742
    @michaelwinter742 Před 8 lety +1

    Netflix needs more growth. Too many boring movies.

  • @connorhughe636323dd
    @connorhughe636323dd Před 8 lety +1

    big think i hope this is an April fools

  • @visamap
    @visamap Před rokem

    Thank you all very much

  • @NyNNyXXX
    @NyNNyXXX Před 8 lety

    Great to... is not working!

  • @frank5520
    @frank5520 Před 8 lety

    Their CEO might....

  • @NoReezN
    @NoReezN Před 8 lety

    3 Masters don't forget the government.

  • @GreaterDeity
    @GreaterDeity Před 8 lety

    Just before I clicked on this, it said, '666 views'. You know what, I'm not even watching it now.

  • @ericsnell3040
    @ericsnell3040 Před 7 lety +1

    Someone accidentally uploaded a commercial

  • @rozras
    @rozras Před 8 lety

    this video in a nutshell : Why we are better then them.

  • @kinpatu
    @kinpatu Před 8 lety +1

    Pandora must have found some rabbit pellets and thought they were gems.

  • @frank5520
    @frank5520 Před 8 lety

    envy

  • @bitesizehistory3529
    @bitesizehistory3529 Před 8 lety

    1. What's with all the Netflix ads on this channel?
    2. What he described is not a pow wow. I think the word he was looking for was a business meeting :)

  • @filippolombardo7578
    @filippolombardo7578 Před 8 lety +1

    this is why i love netflix

    • @vaibhavgupta20
      @vaibhavgupta20 Před 8 lety

      You love Netflix because they use big data differently?

    • @timhorton7799
      @timhorton7799 Před 8 lety +2

      +Vaibhav Gupta is that not a good enough reason ?

    • @vaibhavgupta20
      @vaibhavgupta20 Před 8 lety

      Tim Horton nope thats not good enough.

  • @ednaloren
    @ednaloren Před 8 lety

    Netflix is awful. Most of what they have is trash. Just a waist of money.

  • @rayannasr6931
    @rayannasr6931 Před 5 lety

    change the presenter, so annoying to hear and watch