Big Data Hits the Big Screen (Part I of II Parts)

Big Data Hits the Big Screen (Part I of II Parts)

By Lloyd Marino

Traditions change. It’s just the nature of life. Sometimes the change happens gradually. Other times, it’s forced on us. For millions of Americans, myself included, a trip to the movie theater was probably one of those hallowed traditions that would never run its course. So woven into our cultural fabric and collective consciousness was the movie ritual that we felt nothing could ever take its place.

First, there was all the build up weeks before the film’s release. Your local theater—there was just one—would get a single, large film reel from a distributor and display the title until the next reel rolled into town.

You might remember on premiere day the excitement surrounding getting into your family car. Then you’d purchase the tickets from a little ticket booth before grabbing some candy, soda, and of course, that massive bag overflowing with hot and buttery popcorn.

You’d settle into your comfortable leather chair, and wait patiently through a couple of perfunctory previews, before your feature finally appeared in crystal-clear focus on the big screen. The whole experience was pure magic—even when the movie reel spooled out and the projectionist took a few minutes to reset another one, summoning a cacophony of catcalls from restless moviegoers who didn’t have the benefit of OnDemand, Hulu or Netflix, and were subject to the whims to 20th century film technology.

My how times have changed.

In 2016, Hollywood studios are embracing new paradigms for direct moviegoer engagement.

Predictably, Big Data is playing a role in all of this. Specifically, predictive analytics are increasingly seen as a way to boost studio film promotion and marketing, vital to an industry struggling to stay current with a cultural zeitgeist that seems to change daily. In fact, massive data sets have helped Hollywood more wisely spend its promotion and advertising dollars, which number in the billions.

Looking Back to See the Way Forward

It’s useful to put this Big Data analytics model into some historical context. In the halcyon days of the old Hollywood, studios were “vertically integrated,” meaning the five major film studios functioned as de facto distribution companies since they owned the bulk of theaters. This gave the studios direct contact with moviegoers and film fanatics. This practice effectively ended in 1948 with the landmark Paramount Studios antitrust case that went all the way to the US Supreme Court. In the old system, ticket sales were all but guaranteed because studios simply put their own films into their own theaters. However, once the theaters became free market entities, there was no way to forecast how much, or how little, a studio might rake in. The court ruling translated to a small number of films making extraordinary profits, whereas the majority made little or no money at all. Through all of this, Hollywood lost its most important asset: direct connection to consumers.

Now thanks to what the Atlantic Monthly described as the convergence of “Big Data and big entertainment,” studios are recapturing lost magic and reconnecting with their most valuable asset: filmgoers. Following the model created by Activision and other companies, all of whom collect information from the naturally occurring data sets that are an outgrowth of product consumption, studios are gathering and analyzing massive quantities of movie-goer information and translating them into meaningful, actionable, and ultimately profitable insights into what works and what doesn’t, “altering how movies get made, marketed and distributed,” noted The Atlantic.

Predicting Success

One Big Data approach involves the creation of a predictive analytics model for financial success based on online user habits. For the longest time, studios relied—with uneven results—on a metrics hodgepodge that included, among other things, the Monte Carlo Method to forecast box-office numbers, and TV ratings. They might, as an example, try to gauge a film’s popularity by measuring and analyzing the buzz and concordance surrounding an announcement on sites like Wikipedia and IMDB. The drawback of this approach—and there were many—is that it didn’t really benefit studios since they were collecting data about a film that was already wrapped. Though budget overruns are common in Hollywood—25% in not unheard of—they take a huge toll. Between 2013-14, the big four studios racked up $18 billion in loses, due in large measure, to cost overruns on already astronomical production budgets.

How can Big Data help? Unlike 30 or 40 years ago, when consumers paid for their movie, tickets in cash, making them anonymous and untraceable, today’s moviegoers leave a trail of virtual breadcrumbs; they almost exclusively use credit cards on sites like Fandango, share their purchases on social media, and review the films on any number of fansites. Just like the game companies, movie studios can use information collected to streamline their marketing strategies and make better distribution film distribution decisions (offer the film in more theaters in certain areas).. In fact, retail giants such as Walmart and Bed, Bath & Beyond rely on these sort of pre-order metrics to inform final purchase decisions.

A great thing about collecting data from Rotten Tomatoes, Fandango and similar sites, is that it allows studios to make real-time opinion assessments and even tweak a movie after it’s been made. While this won’t help lower the cost of the an already over budget films, studios might be better able to recoup some their outlays by giving moviegoers more of what they say they want.  

This very model was used to great effect to forecast the success of the most recent Star Wars film, Episode VII: “The Force Awakens.” Using data visualization comparing revenues for the previous six Star Wars movies, the box office receipts for comparable films, and the relative popularity of the 23 actors who’ve had roles in all films (based on box office revenues for films in which they appeared, particularly in leading roles), analysts were able to predict with great accuracy the success of the most recent installation.

Indeed, there’s nothing incidental about the Star Wars franchise’s massive success. Fan loyalty was in full view when over 130,000 lined up for midnight store openings to view and purchase the new lineup of Star Wars toys. Still, in a world where nothing is a sure bet, Hollywood executives can use predictive analytics to help make strategic decisions about which films they should throw their support behind. By using past data— analysts can predict whether or not a film will be a hit. Clearly, Big Data’s predictive analytics are a “force” to be reckoned with. (Check back next week for Part II)

Image By: Michael Haslim

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