The struggle between artistic impulses and commercial imperatives is a question as old as art itself. In the film world, big data is changing all that. The joy and greatness of independent film is that the artist’s vision supersedes the fiduciary interests associated to the project. It doesn’t ignore them -nor should it- but it gambles on the fact that there is an audience for an idiosyncratic piece of filmmaking. Financiers never quite liked it, and it never was quite a gamble, but there was an agreement in place. There was a sense that a film could fare well in its own niche market.
But in this day and age, commercial films don’t just target broad groups such as ‘boys under 25’. They target absolutely everyone, and this unsubtle assault is not due to lazy market segmentation. In an age of polarisation, despite the great financial crisis we’ve gone through, ‘too big to fail’ seems to be the motto of a number of corporations. Disney, Fox and Comcast have understood this. Netflix certainly has, too. In fact, in May 2018 Netflix passed Disney in market cap. While stocks fluctuate with time, this is an eerie symbol of how the media landscape is changing.
Big data is taking over
‘We don’t have any idea who went to see Star Wars in the cinemas.’ This shocking admission came from Disney chairman Bob Iger after the release of The Force Awakens, the first Star Wars film produced by the Mouse House which went on to be one of the handful of films to gross over $2 billion at the global box office. It is fascinating to see that the behemoth that is Disney does not have a granular understanding of its audience when the new kid on the block Netflix has built its business model on that.
Not only do they know how you’re going to watch the content, and what content is best for your tastes, they also know that you get bored within 90 seconds of scrolling through the menu, and that certain films are only meant to be watched up to 70% because they are just too scary to finish. But once they know what the audience looks for in content, they can order or buy films and series that push just the right buttons, and know which audience members to push those to.
The problem is that studios don’t have the data that distributors or cinema chains have about consumer behaviour, therefore they are not able to predict accurately how a film will succeed or fail. This is why Netflix’s place on the market is unique: it knows what audiences want, how they want it and when they want it, and have the power to choose their content. This puts the traditional partnership of studios and distributors at a disadvantage.
Big Data Analytics are just a tool
There is a massive difference between Netflix and Disney. Netflix knows when I scrolled to another tab, paused for a pee break, when I switched to another episode, which shows I like to binge on, which series I’ll take more time to watch: from a number of patterns, they’ll know their user’s taste better than the user. In comparison, Disney has no way to know that I was bored out of my mind by the latest Avengers, they’re just happy I bought a ticket.
And yet: Avengers grossed over $2 billion, and I tweeted about it. We don’t know how much money Queer Eye made for Netflix -probably enough for them to invest $1 billion in European content-, but I’ve also tweeted about it quite a lot. At the end of the day, analytics are one tool among many, including experience and creativity.
In most film schools –not ours-, screenwriting students are not taught how to approach the industry. They’ll leave university with a Bachelor’s Degree and no idea as to how to put together a one-pager or a one-sheet that will sell their film. Creativity remains the one singular, irrepressible human quality that can’t be reduced to analytics, patterns and trends. At a time when the old-timers are trying to approach analytics and wrap their heads around that while limiting artistic products to ready-made bite-size unengaging products, the new kid on the block has already mastered this new tool in a way that does not stifle creativity, and gives agency to both creatives at one end of the pipeline, and users at the other end.
Now let’s get creating.