Legendary is reshaping Hollywood through data analytics.
Legendary Pictures is an American entertainment company that produces film, television, web and comic book content. Although it is not a household name like Disney, it is behind some of the biggest hits in the last ten years: The Dark Knight, The Hangover, Godzilla, Interstellar, and Jurassic World. But even if you don’t buy into the McConnaisance or Batman is too political for you, there is something special about Legendary that sets it apart from the rest of Hollywood: its data-driven approach to movies.
A rarity in the industry, Legendary has a Chief Analytics Office, Matthew Marolda, and a 50-person team that focuses on data analytics. The group deliberately operates far away from Hollywood in Bostonm which insulates them from Hollywood groupthink. Data come primarily from Twitter, Facebook, and other social media, as well as traditional sources like hourly box office figures. It specifically has 500-600 million emails, metadata on films since 1989, and theatre data from the last 10 years. Legendary developed proprietary software that analyses personal, social media, and content data in real time so it can take advantage of the available data. It is considering licensing this software as another way to create value, although it has not yet done so.
Data analytics informs creative decisions.
Legendary uses data in nearly every aspect in move making: conception evaluation, trailer testing, sequel feasibility, cast evaluation, fan screening/profiling, title testing, theme testing, story evaluation, and choosing a release date.
For instance, when casting a male lead for an upcoming film, Legendary picked a less expensive and lower tier A-lister who generated passion on social media instead of a more expensive and higher tier A-listed who was more divisive on social media. This decision will ideally allow Legendary to capture more value by reducing the casting budget and hopefully generate more box office returns. Additionally, Legendary receives thousands of scripts, but only very few reach production stage; data streamline this process by helping measure each concept’s likelihood of success.
Data analytics transforms marketing.
Traditional marketing in Hollywood involves a “spray and pray” approach: three to four weeks before a movie comes out, the film is marketed to the public. Marketers segment the public into four categories: male under 25, male over 25, female under 25, and female over 25. Legendary rejects this approach as narrow and inefficient. Instead of just seeing four categories, Legendary strives to create 80 million groups of four.
The Legendary approach plays out like this:
- Use data analytics to identify hard core fans.
- Make the hard core fans aware of the movie, but do not waste too much money on them because they will probably go no matter what.
- Use data analytics to identify persuadable people.
- Target the persuadable people.
Godzilla‘s success proves that a data-driven approach works.
Data analytics allowed Legendary to ensure Godzilla‘s success long before it was released in the United States on May 16th, 2014. Godzilla had all the makings of a hit: a well-known story, previously successful instalments, and passionate fans; however, Hollywood frequently snatches defeat from the jaws of victory.
To avoid this fate, Legendary used data analytics to create a trailer that generated maximum excitement and buzz. Marolda and his Boston team 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. Legendary consequently listened to the data and created this trailer:
After releasing the trailer, Legendary partnered with Google to identify the most persuadable people, which turned out to be 24-39 year-old women. It then shifted more resources targeting this demographic. In the end, Godzilla spent 10% less on media than estimated, and exceeded domestic box office estimates by $30 million.
Data analytics is imperfect, but still the way forward.
A data-driven approach in Hollywood inherently has challenges. For instance, sometimes data overrepresent small, but vocal communities or opinions. And the data available are more limited in scope than those from Amazon, Pinterest, and others. Data is also no replacement for creativity. Nonetheless, data analytics is still an innovative way make a more profitable and more beloved movie.