¶¶Òõ¶ÌÊÓƵ-Boulder Professor Creates Model Indicating Movie Success Potential
Star Wars, Titanic, Forrest Gump and Jurassic Park — the top-grossing movies of all time. What made these films successful? A ¶¶Òõ¶ÌÊÓƵ-Boulder business professor says she knows the answer.
Ramya Neelamegham, a marketing professor at the ¶¶Òõ¶ÌÊÓƵ-Boulder College of Business, developed a mathematical model that determines which movies will enjoy success at the box office and which will fail.
"Movies cost millions of dollars, but producers still rely largely on rules of thumb when determining which films will be successful in target markets," Neelamegham said. "My model evaluates the significant factors of a movie at different stages of the filmmaking process. It quantifies what was formerly guess work."
To create the model, Neelamegham (pronounced -- ne le' may gan) gathered information on 35 movies released from 1994-95. She evaluated films from different genres, such as "Little Women," "Die Hard" and "Apollo 13." Her model evaluates star quality, box office revenue, past performance of similar films, the number of screens showing the films, the number of weeks the films run and the local distributors and foreign rights holders.
"These criteria determine how well a movie does," Neelamegham said. "Rather than simply counting on Arnold Schwarzenegger to be successful in France, we developed a system that considers more than just his popularity."
Neelamegham evaluated data during five steps of the filmmaking process:
o The market evaluation stage — studios determine which films to pursue and which markets to attract.
o Postproduction phase — sales forecasts are evaluated to establish where a film is released.
o Just before the film’s domestic launch — studios determine how many screens on which to show the film.
o After the domestic release — producers evaluate how to position the international launch.
o Just before the international launch — producers review early results to shape strategic decisions, assess the competition and determine future marketing.
"After collecting the information, we tried the model on movies that hadnÂ’t been released," Neelamegham said. "It was more accurate than any other model trying to forecast movie success. Given that this is a million-dollar industry, using scientific data makes sense."