Forecasting Blockbusters Movie studios are using AI to predict box office success.

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Screen capture of Cinelytic searching for historical data of Nicole Kidman movies' performance

Could a black box become Hollywood’s crystal ball?

What’s new: Warner Bros. is using an AI-powered tool that predicts a movie’s box-office success, according to Hollywood Reporter.

How it works: Cinelytic promotes its software as a project-management platform to help movie execs make decisions throughout a film’s lifecycle. The company says it’s looking not to automate decision making but to make human managers more effective.

  • The model draws on historical data including financial performance of a slew of films in various geographic markets along with their stars, genres, and other key information.
  • Users input details of the film they’re considering, and the tool predicts foreign and domestic box office sales plus DVD/Blu-ray, cable, and broadcast revenue. By toggling parameters such as release date or key talent, execs can see how the changes might impact the numbers.
  • Beside Warner Bros., the company’s clients include Ingenious Media (Avatar), Productivity Media, and STX.

Behind the news: Hollywood honchos have been experimenting with AI to help them home in on blockbusters and award winners for a few years. A growing number of companies are after a piece of the action.

  • Scriptbook, a Belgian company, predicts whether a movie will turn a profit by analyzing its script. The company said it has numerous Hollywood clients.
  • The Israeli company Vault predicts a movie’s success among various demographic groups by analyzing how trailers perform online.
  • 20th Century Fox published its own research on a machine learning model that analyzes audience reaction to scenes and objects in a trailer.

Why it matters: Movies can cost hundreds of millions of dollars to make, so producers are eager for any insight that can return their investment at the box office. Predictive systems could be especially helpful around film festivals, when executives often have to jump into fast-moving bidding wars.

We’re thinking: This kind of approach lends itself to many industries. We look forward to one for publishing AI newsletters.


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