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 ondemand 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.

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 bestinclass 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.

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. ......

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