By Lloyd Marino
Would it be fun to know what’s around the next corner? Yeah, yeah, knowing what’s coming next takes the fun out of life. After all, spontaneity and the unexpected make life worth living, right? On the other hand, think of all the crap you could avoid? I mean how many things would you have done differently if you’d known the outcome in advance?
In these tough economic times, there are few industries that wouldn’t label themselves as “risk averse.” Entrepreneurs, in particular, like to think of themselves as willing to bet the house to live out their dream, but as Ben Casselman observed in the Wall Street Journal, the risk taking spirit seems to be in ever diminishing supply these days. The movie industry, in particular, has always been soft on risk, explaining why it was so willing to embrace the promise of Big Data. And the industry as a whole has certainly made good use of Big Data analytics, allowing production companies and studios to parlay customer feedback into strategically sound and financially wise marketing decisions.
While Big Data can certainly help studios on the business end, can the data explosion help on the creative side as well? Can Big Data better inform scriptwriters on content, or provide insight into the sorts of screenplays that sell best? Can Big Data really tell a multiple Academy award winning director like James Cameron how to direct, what actors to hire, or how to shoot a particular scene (and would he even listen)?
Answers to these questions really take an understanding of human psychology. Good, bad or indifferent—a film’s qualities always will elicit an audience feedback. The key is taking these responses and breaking them to the down to find out what works and what doesn’t?
Hollywood and Archetype
Increasingly, Hollywood is using Big Data to help inform character archetype. After all, why put out a film featuring characters that audiences don’t relate to or recognize? Warrior, heroine, damsel in distress or more often, a combination of personality types—writers have always created characters they thought would resonate with audiences. Dorothy from The Wizard of Oz was certainly an innocent, but the case is easily made that she was equal parts explorer and heroine. AMC, home to Mad Men, Breaking Bad, and Walking Dead, among other wildly popular programs, has started grouping horror films into genres such as “haunting” and “killer” and then breaking these archetypal categories down into smaller, sub-categories, as a way to more accurately assess audience reaction, inform content creation and carve out little niches and even define areas of expertise.
The Big Data archetypal approach has also been utilized to brand and market popular television networks, including AMC, which is now known as the “home of the anti-hero,” and features programming that fits into the anti-hero archetype.
Big Data and Program Design
Netflix literally saved itself from extinction by using Big Data to design original programming. Netflix uses a complex algorithm that distills movie content into more than 70,000 characteristics, creating a detailed movie genre mosaic that provides a greater understanding of content and audience. This algorithm factored heavily into Netflix’s decision to remake House of Cards, which soon after its release became the most streamed piece of content in the United States and 40 other countries as well, according to the New York Times. The best part for Netflix is that company executives knew they had a winner long before the show went into production.
Even more remarkable than the success of House of Cards, which Netflix promoted heavily, is the story behind its third original series, Orange is the New Black. The show didn’t benefit from the same hype and momentum as its predecessor, and lacked a big name director and actors. Yet, the show pulled in more viewers during its fits week than House of Cards and Arrested Development, Netflix’ other popular original program. So how do we account for OITNB’s early runaway success: Big Data of course. Company bigwigs knew its users would watch this show about a woman sent to jail for a crime she committed years earlier, whether or not they hyped it to the moon.
By creating a “database of American cinematic predilections,” as Alex C. Madrigal described it in a recent piece in the Atlantic, Netflix has taken the guesswork out of guessing what folks want. “The data can’t tell them how to make a TV show, but it can tell them what they should be making,” he writes.
In fact, Big Data is behind all of Netflix big gambles, and has given the company an unprecedented look at audience temperament, sentiment and preference. As I explained in last week’s blog, the entertainment industry has always relied heavily on data, but Netflix has upped the ante, and is the first high tech company to distribute and produce content, thanks in large measure to its ability to look inside in the consumer mind in real time.
How much information does Netflix have access to exactly? Said the New York Times, Netflix looks at “30 million ‘plays’ a day, including when you pause, rewind and fast forward, four million ratings by Netflix subscribers, three million searches as well as the time of day when shows are watched and on what devices. That was in 2013. Today, Netflix may account for a 1/3 of peak time Internet traffic in the US alone, and last year, the company reported that it had signed up 50 million subscribers worldwide. And Netflix collects data from each and every one of these subscribers.
Big Data and Script Writing
Big Data has even made its way to the artistically hallowed ground of script writing. Indeed, Big Data solutions have eliminated elements endemic to the script writing process that may prevent a film from bombing long before it reaches its intended audience. How else to explain the popularity folks like Vincent Bruzzese, a former statistics professor and currently the CEO of C4, a Hollywood based entertainment research firm, and the man to whom Tinsel Town executives frequently turn to analyze scripts pre-production and suggest changes that might make them more audience friendly.
Bruzzese, who gets $20,000 and up to review scripts, also has gained insight into script elements that separate success from failure. He found, as an example, that audiences prefer demons that target a specific character; ala the Exorcist, as opposed to those summoned by a Ouija Board. As Bruzzese told The New York Times, “Demons in horror movies can target people or be summoned . . . If it’s a targeting demon, you are likely to have much higher opening sales than if it’s summoned. So get rid of that Ouija Board scene.” He also suggested that films that include “bowling scenes pop up [and] fizzle,” and so it would be “statistically unwise to include one in your script,” and that “a cursed superhero never sells as well as a guardian superhero . . .like Superman.” Who Knew?
While some in the film industry may cry foul and lament the loss of creativity, many producers, studio executives and financiers have praised Big Data’s contributions. And if we look at the history of cinema, the vast majority of films follow fairly rigid formulae. So, why not use Big Data to give people something they don’t even know they want, or better yet, something they don’t even know could exist? Sure, it’s good to stretch the bounds of creativity, but let’s not forget that Hollywood is a business. It’s “show business,” but it’s still a “business.”
Image By: Christian Joudrey