How Hollywood Embraced Data Analytics?

Ranjith Raja Business Intelligence Analyst October 11, 2017 12:04 6 min read 1505 views so far!

Did you know that Will Smith used the power of analytics in his early career? He worked along with his manager to apply their own form of cluster analysis to pursue his film career. They analyzed the top 10 highest money-grossing movies of all time to discover new patterns. They observed that 10 out of 10 had special effects. Nine out of 10 had special effects with alien story. Eight out of ten had special effects with creatures and a love story. The rest is history. Smith was in Independence Day, Men in Black, I, Robot, and I am Legend. He is the only movie star whose films earn predictably over $20 million. The application of statistical analysis has improved the likelihood of Will Smith to be in a film generating high incomes.  

Are the audience of Hollywood or movies in general have become just a passive receptacle? We are not appreciating a good film, not because we are indifferent to what we have seen, but because there is no one to applaud. But it would be very wrong to think that audiences have no role in Hollywood film industry. Instead, the role has changed. We now throw our tomatoes (be it a good or rotten) online - in blogs and Twitter feeds and Facebook posts. What is the role of data analytics in the Hollywood film industry? Let’s have a look.

Data analytics play a major role in film industry from conception/story evaluation, title testing, cast evaluation, fan profiling, trailer testing and also more importantly choosing a release date.

Conception/Story Evaluation

For instance, from thousands of scripts, only very few reach production stage. The concept’s likelihood of success can be measured from predictive analysis of the movie theme. By combining deep understandings of both content and audience, studios will be able to choose and tailor their movies and arrive at best screenplay for the script based on the suggestions from data analytics.

Godzilla had all the qualities of success: a well-known history, previously successful divisions and passionate amateurs; however, Hollywood often gives you defeat from a favorable success. To avoid this fate, data analytics was used to create a script that generated maximum excitement and buzz for Godzilla (2014).  Marolda and his Boston team from Legendary Studios learned from social media data that fans were more interested in conspiracy theories and actor Brian Cranston’s role in the film than the monster, the military, and destruction to make it a block-buster success.

Title Testing

What's in a name? Well, in films the name attracts more than 50% of crowd. Initially Timothy Dalton's second outing as 007 ‘License to Kill’ was named ‘License revoked’ as the British Secret Service and sets off on a brutal personal vendetta against a master criminal. But this was changed after test screenings revealed that US crowds associated the term with driving. Obviously License to kill was chosen to attract more crowd.

Cast Evaluation

Casting does not mean only to choose the best actors. If a movie wants to earn successful box office returns, casting plays an important role. A male lead for an upcoming film can be either selected as lower tier A-Lister, who generated passion on social networks instead of a more expensive and higher one, who was more divisive on social networks. This decision will ideally allow to take more value by reducing the casting budget and hopefully generate more box office returns.

Fan Profiling

In the film industry, one of the traditional segmentation being used is the quad segment- “Male. Female. Over 25. Under 25.” It's essential what the studios use in terms of segments when they make panels and polls. This blunt technique is being replaced by computers that can make accurate segmentation by taking over the traces of digital data we leave online and build them into predictive models of what we like and dislike. As a result, the quad segment approach to the public profile is replaced by a profusion of very thin sliced profiles that more accurately represents the spectrum of the sensitivity of a modern audience.

Trailer Testing

Trailers were once a brief thrill limited to Cinema. They were forgotten once the main feature was rolled out. Now Trailers are major events – with high expectations, obsessed over, dissected and reworked for fans. Trailers will always be the best way to feel a movie. Trailers are tailored to attract different kinds of people. The likes of targeted audiences can be verified through data analytics. Six trailers for ‘Finding Dory’ were released, for different markets around the world geographically, considering the geographic distribution of the audiences.

Release Date

Release date has to be chosen strategically considering various factors like regional holidays, cultural events, political situation, sports events, social network reach, competition movie release dates, movie genre and cast of the film. For instance cultural events, sports events like the FIFA World cup, political events – elections, protests affect the box office returns of a movie.

Heard of short film SunSpring? The script and movie were the product of director Oscar Sharp and Ross Goodwin, a New York University AI researcher. A so-called recurrent neural network (AI), which named itself Benjamin, was fed the scripts of dozens of science fiction movies including such classics as Highlander Endgame, Ghostbusters, Interstellar and The Fifth Element. Benjamin was asked to create a screenplay including actor directions, using a set of prompts required by the Sci-Fi London film festival’s 48-hour challenge. The result was a weirdly entertaining, strangely moving dark sci-fi story of love and despair. The sentences made sense in isolation, although the dialogue was not well taken when identified together. “As soon as we had a read-through, everyone around the table was laughing their heads off with delight,” said Oscar Sharp.

The robots might be coming, but screenwriters have nothing to fear for the time being. The analytics can be used to build a predictive model to guess the success percentage. But creativity should come from the scriptwriter who should determine whether or not the suggestions should be taken. AI or Data analytics cannot replace humans where creativity is needed. Making a film definitely requires creativity.


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