How Netflix Got Big with Big Data

Femi Akintoye our consultant managing the role
Posting date: 8/24/2018 7:51 AM
There’s little argument that Netflix have changed the game when it comes to how people consume entertainment. Whilst Amazon, Disney and Apple seek to replicate the success of Netflix’s model, they still lead the way with over 130 million subscribers worldwide and have just broken HBO’s 17-year streak as the most nominated ‘network’ at the Emmy’s with an astonishing 112 nominations. 

Having begun life as a subscription-based DVD rental-service created in response to founder Reed Hasting’s frustration with late rental fines, Netflix were one of the first to offer video-streaming as an option for viewing films and TV. Now filled with scores of original programming, the secret to their success lies not just in creativity and innovation, but in Big Data. 

Top Picks From Your Data


When the former CEO of the now-defunct Blockbuster claimed: “Netflix doesn’t really have or do anything that we can’t or don’t already do ourselves”, he made a vital oversight. Whilst Netflix may have offered fewer films and TV shows at the time, they were already busy collecting, and utilising, customer data in a way that hadn’t been done before. This included:

What do people search for?
When do they watch a program?
What device do they watch on?
Do genre preferences vary with device?
When do they stop watching?
What shows are the likely to ‘binge’?
Or even what are the horror films that people find too scary to watch until the end…

Netflix used, and still uses, this information to create recommendations for each user, curating an individual experience based upon personal preferences. This technique has been incredibly successful with over 75% of viewer activity based upon these recommendations.

And they continue to finesse how their collect their data, switching from a five-star rating system to a thumbs up/thumbs down model. Cameron Johnson, Netflix’s Director of Product Innovation had observed: “a difference between what [users] say, and what they do,”. For example, frequently-watched comedies were being awarded three stars, as opposed to occasionally-watched, but ‘more worthy’ documentaries being given five stars. By simplifying the system to a like/dislike set-up, Netflix can provide subscribers with recommendations “more aligned with what people actually play”. 

Stream if you want to go faster


Unlike traditional broadcast mediums, Netflix’s income doesn’t come from advertising, or a pay-per-view service, but subscribers. That means their main ambitions are to generate new subscribers and keep existing ones.

If Netflix has data that tells them users who stream over a specific number of hours of programming are more likely to stay, they can place their focus on ensuring they watch at least that many hours. It’s highly likely that the introduction of the ‘skip-credits’ feature was a result of Netflix realising that this was the time when people were most likely to turn off, when the was an opportunity to encourage them to watch more. 

Perhaps most interestingly of all, Netflix’s Big Data team are helping inform creativity. This ranges from supplying that data that helps personalise trailers for new content based on each subscriber’s preferences, to deciding which shows to commission. Netflix’s data told them that prison-based dramas, shows with strong-female ensembles, and programs with LGBT+ themes and characters were both popular, and shared a lot of audience overlap. With all this information at hand when they commissioned ‘Orange Is The New Black’ for a full series, Netflix could be sure that there was an audience for the show. 

As more and more companies add their own streaming services, including Disney’s expected behemoth, this targeted original content is going to become more and more valuable for Netflix. Fortunately, they’re long-used to changing not just how people watch, but also what they watch. 

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Where Tech Meets Tradition

Where Tech Meets Tradition

If you’re lamenting the decline of handmade traditional products, cast your cares aside. There’s a new Sheriff in town and its name is, Tech. Just a generation ago, children would leave the farm or the family business, go to school, and then move on to make their place in the world doing their own thing. Away from family.  Today, the landscape has changed and those who have left are coming home. But this time, they’re bringing technology with them to help make things more efficient and more productive. Is Tech-Assisted Still Handmade? In a word, yes. Artists still make things “from scratch”, except now technologies allow them to not only see their vision in real-time, but their customers, too. Have you ever wondered what the image in your head might look like on paper or in metal? What about the design of prosthetic arms and healthcare devices by 3D printers? You’re still designing, creating.  But just like any new technology, there’s still a learning curve. Even for cutting-edge craftspeople who find that sometimes, the line between craftsmanship and high-tech creativity may be a bit of a blur. Not to mention the expense for either the equipment required or being able to offer art using traditional tools at technology-assisted prices. Somewhere between the two, there is a trade-off. It’s up to the individual to determine where and what that trade-off is. Life in the Creative Economy One of Banksy’s paintings shredded itself upon purchase at an auction recently. AI is making music and writing books. Augmented Reality, Virtual Reality, and Blockchain all have their place in the creative economy from immersive entertainment to efficient manufacturing processes. Each of these touches the way we live now. In a joint study between McKinsey and the World Economic Forum, 'Creative Disruption: The impact of emerging technologies on the creative economy', the organisations broke down the various technologies used in the creative economy and how they’re driving change. For example: AI is being used to distill user preferences when it comes to curating movies and music. The Associated Press has used AI to free up reporters’ time and the Washington Post has created a tool to help it generate up to 70 articles a month, many stories of which they wouldn’t have otherwise dedicated staff.Machine Learning has begun to create original content. Virtual Reality and Augmented Reality have come together as a new medium to help move people to get up, get active, and go play whether it’s a stroll through a virtual art gallery or watching your children play at the playground.  Where else might immersive media play out? Content today could help tell humanitarian stories or offer work-place diversity training. But back to the artisan handicrafts.  Artistry with technology Whilst publishing firms may be looking to use AI to redefine the creative economy, they are not alone. Other artists utilising these technologies include:  SculptorsDigital artistsPaintersJewellery makersBourbon distillers America’s oldest distiller has gotten on the technology bandwagon and while there is no rushing good Bourbon, but you can manage the process more efficiently. They’ve even taken things a step further and have created an app for aficionados to follow along in the process. Talk about crafted and curated for individual tastes and transparency. It may seem almost self-explanatory to note how other artisans are using technology. But what about distilleries? What are they doing? They’re creating efficiency by: Adding IoT sensors for Data Analytics collection Adding RFID tags to their barrels Creating experimental ageing warehouses (AR, anyone?) to refine their craft. Don’t worry, though. These changes won’t affect the spirit itself. After all, according to Mr. Wheatley, Master Distiller, “There’s no way to cheat mother nature or father time.” Ultimately, the idea is to not only understand the history behind the process, but to make it more efficient and repeatable. A way to preserve the processes of the past while using the advances of the present with an eye to the future. If you’re interested in using Data & Analytics to drive creativity, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expect consultants to find out more. 

How movie studios use data

Lights, Camera, Data

Whilst Data continues to play a huge role in all aspects of life; developing businesses, schools, health care etc., one industry has already seen a massive impact from the Big Data revolution. The film industry, and its television counterpart, were among the first see to the potential of how Data can transform the way they work.  Beyond profit, access to new types of Data is allowing companies to consider what audiences will be most interested in at specific times, utilising current viewing habits, what topics are the most popular on social media, and even the news so they can create something that tailors to everyone’s different interests. The Streaming Revolution Netflix’s popularity is down to more than the variety of movies and series it has to offer. Its pioneering use of recommendation systems, originating when it was purely a DVD rental service, means that it always knows what its subscribers want to watch, when they want to watch it, and on what device. Their ability to tailor bespoke recommendations, down to which poster people see, has created an entirely different approach to how viewers chose and engagement with entertainment.  Netflix’s Data collection means that it knows its audiences very well, something they can utilise as part of their marketing. By contrast, even a behemoth like Disney can struggle to compete. Following the success of 2015’s Star Wars: The Force Awakens, Disney Chairman, Bob Iger admitted ‘we don’t have any idea who went to see Star Wars in the cinemas’. Whist this may have not been too much of a problem at the time, given the film’s $2 Billion box office, the diminishing returns of the films that have followed suggests that better insight as to why the film was a success may have been beneficial. It’s no wonder, therefore, that Disney are launching their own streaming service later this year.  Beyond Box Office In the majority of businesses these days, Data is used to decipher consumer buying habits, web traffic and social media interactions, as well as to monitor supply chains, costs and sales. This is no different for the movie industry, particularly when examining what makes a move work. By using Data Science, producers can determine which actors, directors, release dates and even running times are likely to make a movie profitable. For example, history may dictate that the summer is likely to be the most profitable time of year. Whilst this may be true for June, where average profit is $100m, ten times that of January, November and December are the second and third most profitable months.   Beyond assessing profitability, however, Hollywood is using technology to try and re-establish a relationship between creators and audiences. Newly emerging tools are empowering studios to convert massive quantities of movie-goer reactions into meaningful actionable insights. With Big Data analytics, movie executives have gained an insight into audience’s perspectives and this is dramatically altering the way in which movies are made, marketed and distributed. Companies like IBM are looking at new ways of tracking sentiment analysis that will have a massive impact on the creative process. However, whether or not the industry’s leading writers and directors will want to work within these parameters is yet to be seen.  #DataDrivenAds Data’s impact on the movie industry goes beyond the insights it offers on audience perceptions. When it comes to marketing a movie, the Data & Analytics space offers a number of opportunities. Studios are beginning to realise that, in order to drive the small-screen generation to the big screen, they need to come to their territory. To promote ‘The Dark Tower’ in Singapore, Sony ran a series of targeted mobile adverts that allowed users to choose a character to engage with. A follow up campaign then targeted users who had engaged with relevant messaging and details of showtimes at their nearest cinemas, using the mobility of their devices to their advantage. Furthermore, for the release of ‘Ready Player One’, Facebook offered an augmented reality experience for those who engaged with the film’s poster in public.  However, sometimes, the most effective marketing technique remains word-of-mouth. Netflix’s ‘Bird Box’ received little critical praise and minimal attention initially upon release. However, once users started posting memes about the movie onto their social media feeds, viewing figures picked up exponentially. This allowed Netflix to reassess their marketing efforts and respond to public sentiment, creating a strategy that fed off the zeitgeist and was significantly more effective.  Data has transformed the movie industry. If you’d like to work with Data & Analytics to transform another, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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