Since its inception, Netflix has paved the way for streaming to become the new way to watch content and it’s no surprise either. If we look back upon the history of content distribution in the entertainment industry, technology has always been at the forefront. Look no further back than when radio helped bring entertainment across frequencies, or when television brought movies and sitcoms into the homes of suburban America. And now thanks to mobile technology, we have a radio, television, and computer all combined into a device that can fit into our pocket. Technology has always been the limit to what the entertainment industry can accomplish, but with the digital age increasing the interconnectedness of consumer to merchant, it appears that the limit may be no more thanks to data science.
Before discussing how streaming takes advantage of data science, we have to talk about how it got there. With almost everybody relying on mobile technology, especially their smartphones, it’s now far more easier to obtain information and data on people. The digital age has introduced corporations and business to the digital footprint: a collection of data that summarizes a consumer’s purchasing habits and, most importantly, their online activity. That online activity is what draws the attention of businesses and advertisers. By using data analytics, businesses and advertisers can create a profile of their target audience that gives them the best opportunity to sell their products and/or services. In the case of something like Netflix, data science can not only help sell its services, but develop products based on their users activity.
Netflix has always been a data science driven company. On their own website, they state:
“Partnering closely with business teams in product, content, studio, marketing, and business operations, we perform context-rich analysis to provide insight into every aspect of our business, our partners, and of course our members’ experience with Netflix.”
Netflix is one of the first online content platforms to take advantage of data science and algorithms. Their software engineers are able to detect the viewing habits of their users and create personalized recommendations for them in order to generate more web traffic on their site. Netflix’s reliance on data and algorithms is so strong that they even developed algorithms that change the thumbnail image of a movie or TV show. For example, they’ll change the thumbnail if the image contains the likeness of an actor or genre that you prevalently watched on Netflix. Their system is so efficient and effective that Netflix knows all of their users’ viewing habits 80% of the time. And with their content library being one of the largest, they can cover a large market of consumers with personalized algorithms for each of them.
Netflix doesn’t have to rely on a system like the Nielsen Ratings to determine what shows they need to produce. They have access to data that detects even the tiniest detail. Netflix’s data reaches so far that they can even detect a user’s browsing and scrolling behavior on their interface. The main point being is that Netflix deeply knows its user base and market. And the thing that makes Netflix such a smart company is that they utilize their data to not only manage licensed content, but to create their own.
In a New York Times article titled “Giving Viewers What They Want,” David Carr writes, “Netflix is commissioning original content because it knows what people want before they do.” The subject of Carr’s article was about how Netflix’s new show at the time, House of Cards, was unlike any other show. It has nothing to do with its content but rather with its inception. House of Cards was one of the first streamed shows, and according to Forbes, its first season was ordered in full. Netflix did not order a single pilot so that they can show test audiences. They already knew that their user base would want to watch House of Cards due to their data analysis supporting it.
Netflix churned out more hits like their collection of superhero shows set in the Marvel Cinematic Universe, Orange is the New Black, Stranger Things, and The Queen’s Gambit. Netflix’s success was what led to what’s been deemed the “Streaming Wars.” All of a sudden services like Hulu started rivaling Netflix, and then movie studios started introducing streaming services like WarnerMedia’s HBO Max and Disney+ that add content libraries to their respective properties. And with these streaming services, original content was made for streaming.
With streaming becoming so big and popular, the biggest question is how does this affect the entertainment industry, or more importantly, how it affects the type of content we’ll watch in the future?
Netflix’s data science driven production process somewhat clashes with how a movie or TV show is regularly produced for conventional platforms. For the traditional method, it relies on what worked in the past and gut instinct. Film studios rely on the success of past films in order to help them decide what to greenligiht. For Netflix, they only need to see what their data analysts report. For Netflix, a success of a show is already determined before it gets greenlit due to their data analytics. What this suggests is that Netflix isn’t looking for a creative filmmaker or writer that could pitch them a new show. Rather, it suggest that Netflix is only looking for a competent filmmaker that can make the type of show that they already know what they want. In other words, it seems like they’re looking for a simple role player rather than a creative artist.
It’s to no one’s surprise that movies and TV is equally as a business as it is an art form. Netflix commissioning artists and filmmakers to produce content for their platform isn’t something we haven’t seen before, but what is different is the lack of artistic risk that studio executives have a sixth sense for. A lot of the great films and TV shows we’ve cherished in our popular culture were deemed too risky or a guaranteed failure. Cultural icons like Star Wars or even Seinfeld wouldn’t have happened if not for studio executives taking that leap of faith and relying on their intuition.
This seesaw of what’s successful and what’s not is what led to the popular William Goldman quote “Nobody knows nothing.” For a streaming service like Netflix, they’re trying to erase that need for a leap of faith. From a business perspective, it makes sense that Netflix is trying to erase that risk that could lose the company millions of dollars, but Netflix isn’t selling a product that can be bought off the shelf in a last minute Black Friday shopping deal. They’re providing movies and TV shows, products that don’t have an expiration date or a need to be replaced for the newest model. They live in the hearts and souls of people’s memories, and are ways for people to connect. Bringing that cold, calculative approach that Netflix is using to commission their original content can take away the artistic imprint that’s essential to what makes a good movie or TV show.
With other streaming services trying to replicate Netflix’s success, relying on data science rather than artistic risk could be the future of producing movies and television. If I were writing this before March 2020, my concerns would stop at the future of just streaming content, but since I’m assessing the future of producing content after experiencing the COVID-19 pandemic, the effects of data science may go beyond the internet.
During the COVID-19 pandemic, Warner Bros. decided to release their 2021 slate of films in both theaters and on HBO Max. What appears to be an attempt to gain as much profit as possible during the pandemic could be the future of theatrical releases. From a business perspective, the use of data science and analytics could help assess the success of theatrically-released films a lot better than box office earnings. That being said, though, moving to streaming can mean the further decline of movie theaters. Considering the situation that they were in, Warner Bros. made a smart business decision in testing out what releasing theatrical films on streaming could potentially look like. The first two flagship films that they released on HBO Max was Zack Snyder’s director’s cut of Justice League and Godzilla vs. Kong. Both films have reportedly increased the number of subscribers during their releases (myself included). While not a ground-breaking success that made Warner Bros. automatically think that streaming is the new movie theater, it still offers a glimpse of what’s possible to come.
The films that Warner Bros. released weren’t just any ordinary films; they’re tentpole films that can help sustain a franchise and thus produce more films. If this move by Warner Bros. further encourages studios to rely on streaming services, some movie theaters could end up closing their buildings. Some smaller theater chains like Arclight are shutting down operations due to the pandemic. It’s not a question of whether the theatrical experience is essential to the viewing of cinema, but evaluating the artistic value of how we consume our content is often replaced with the goal of convenience, especially with movie ticket prices preventing people from willing to come to the theater. For theaters, a lot of contributions are affecting its sustainability, and the repercussions of the COVID-19 pandemic just made the the situation a whole lot worse.
With all the potential foreshadowing and warning that industry analysts have said about how streaming can affect the entertainment industry, they’re all still predictions. Analysts have said the same about television, so it’s no surprise that history is repeating itself with streaming. If we were to look through a lens of how streaming can make the entertainment industry different rather than in trouble, there are some potential upsides.
With streaming taking advantage of the mobile technology that is essential in everybody’s lives, it’s especially essential to the younger audiences. The profile of the current younger audiences is that they’re more diverse and accepting of new ideas, and they’re the most reliant on technology. The data science of streaming is eliminating that risk of producing content that may seem too risky, which is also a practice that prevents different stories from being told. In other words, movies and TV with diverse points of view are limited in the traditional form of producing content, which leads to accusations of prejudice and discrimination of the studio heads. With that said, we know that these studio heads only care about money, and the data science of streaming giving them a more secure way to obtain that money. With the young, diverse audiences showing that they’re into diverse storytelling in that content, it’ll be reflected in the data, which is where the money is.
To sum it all up, the power and influence of data science on executives can lead to more diverse storytelling and possibly better representation. An example can be seen in the handling of Zack Snyder’s Justice League. In the theatrical release, the character of Cyborg, a Black superhero, has a very limited role. In the director’s cut released on HBO Max, his role was so essential to the story that it drew massive praise from fans and HBO Max’s users.
Movie theaters can also change in a positive way depending on how you look at it. The economic incentive of data science in streaming could push studios to put their blockbuster content onto streaming. Since the masses rely on convenience, and streaming offers that convenience, studios can have a better understanding of how to somewhat beat the market. With movie theaters losing all big ticket items, they would have to adapt. They could do that by bringing in smaller, independent films onto their screens and target their audiences through there. Independent films were losing theater space due to the popularity of blockbuster films, but if studios were to move those blockbuster films to streaming, there would be room left for the indie films. Now the question is if this switch were to happen, would everything feel the same with the exception of streaming taking the blockbusters? Probably not. Movie theater chains might have to limit the number of theaters so that they can invest in markets that are into indie films while studios may need to put a cap limit on blockbuster budgets. But it would be a situation where everyone comes out on top.
The main point of all this isn’t to point out that streaming is good or bad for the entertainment industry. If I were to use the history of the entertainment industry as my evidence, then it’ll prove that streaming is just a different platform for watching content. And with that different platform, everybody will adapt despite Hollywood being plagued with chaos, it thrives on the chaos. I predict that in the next ten years, industry analysts will look back on this moment and just say that streaming is another hump that Hollywood had to get over like they did with television.
