“Nobody knows anything,” wrote William Goldman in 1983. “Not one person in the motion picture field knows for a certainty what’s going to work. Every time out it’s a guess, and if you’re lucky an educated one.” Strong words from the Academy Award winning writer of All the President’s Men (1976) and Butch Cassidy and the Sundance Kid (1969) With the rise of big data analytics in the film industry, does Goldman’s statement still hold true?
The answer is nuanced. While studios continue to get a fair number of their box estimates wrong, the levels of certainty with which studios now forecast how well their next film is likely to perform at the box office are improving with every new release. But how and where is the big data being used? And given that the typical indie writer, director and producer is more concerned with simply trying to get their passion project off the ground, why are discussions about big data even relevant to the low budget filmmaker?
Before I go on to discuss how indie filmmakers can use widely available data to empower their decision-making processes, it’s first useful to point out that data-based forecasting isn’t new to Hollywood. The major studios have been using predictive analytics to forecast films’ ticket sales for decades. This starts the moment a screenplay is seriously considered for the greenlight. At this point, historical modelling is used to compare how well similar genre films, produced for comparable budgets, with like-for-like stars, under comparable distribution factors have performed at the box office.
What has changed over the last few years is that this relatively straightforward business intelligence is now being surpassed by highly complex machine learning algorithms that can handle far larger sets of data in order to learn to identify patterns that are otherwise indiscernible to humans. This means that the impact of the complexities of everything from the screenplay’s narrative structure, through casting choices and editing decisions on audience engagement and ticket sales is increasingly becoming known.
As Mathew Marolda, Chief Analytics Officer at Legendary Pictures (Jurassic World: Fallen Kingdom (2018), Mamma Mia! Here We Go Again (2018) etc) explains:
We try and infuse data and analytics with everything we do – from the moment we are considering which film to make, up until its home entertainment release.
Data analytics inform their choices about which projects to develop, who they cast, how their films are marketed and precisely to whom. Going even further, Netflix uses their datasets of the viewing habits of their 130 million worldwide users. Together with data they have captured on their own shoots, they optimise production schedules, localise their films, and then market them to the widest possible viewer base through highly targeted campaigns. Four quadrant marketing is over, with big data analytics, the new marketing appeals to “micro segments”.
How then is any of this relevant to the indie filmmaker?
1. Big data has useful marketing statistics
With the general rise in knowledge about what makes films commercially or critically successful, low budget filmmakers are able to empower themselves to think not just creatively but also strategically about the kinds of projects that they’re most likely to be able to get off the ground. The more that is understood about factors influencing films’ success and the more this filters down into the trade papers, film schools and industry seminars, the more knowledgeable producers, investors, sales agents and distributors become, which obviously impacts on the qualities of projects they’re be looking for.
2. Big data analytics is free
Indie filmmakers now have access to a vast amount of freely available big data online. This can be used to research how similar films have performed, the size of a film’s potential audience, their likes and dislikes, and whether a film’s themes and subject matter should be expected to generate buzz.
By identifying comparable films, filmmakers can find out whether projects like theirs secured theatrical release and if so how they performed at every market across the world. If audiences grew week on week for these comparable films, was this mostly down to stellar critical reviews and word of mouth, or targeted social media campaigns? If these comparable films didn’t achieve cinematic release, what can be discovered about their downstream revenues?
All these answers are available online and can be used to guide early decision-making processes about what to write, direct or produce. That’s not to say that creative instinct shouldn’t always come first, but that it also helps to be strategic if you want to build a sustainable career.
3. Big data is how studios predict box office success
In the future it’s likely that indie filmmakers will be able to tap into the same kinds of predictive big data analytics that studios already use – for an affordable fee.
Startups like London-based Epagogix and Belgian company ScriptBook already claim to use AI to predict box office from a screenplay far more accurately than some of the industry’s best executives.
Soon we should expect to see indie production budget and scheduling optimisers, based on data from low budget film shoots across the world, as well as a whole other variety of useful tools. While the use of big data within the creative industries raises very real concerns about commerce bypassing creativity, with transparency, careful monitoring and recognition that certain artistic decisions must continue to remain sacrosanct, big data analytics have the power to offer just as many advantages to the independent filmmaker as they do film studios.
If you’re interested in learning to make the most of the big data already freely available to filmmakers, and factors affecting films’ commercial and critical success, come along to my Moneyball for Film Investors and Producers talk at Raindance Film Festival.