Inside the movie industry, the words on everybody’s lips are data-driven movie making.

Not since the advent of sound has such a potentially revolutionary new technology been introduced to film.

You only need to take a quick glance at the history of film to see how disruptive the advent of sound was during the 1920s and 30s. This single new innovation radically changed the industry forever.

Everything from the way films were staged, how the action was conveyed onscreen, to the way that many movie actors were simply not able to adapt to this new medium, transformed the face of the industry and the films that it produced.

Legendary film actors such as Charlie Chaplin, who was once the most famous person in the world, and Theda Bara were left behind in the wake of this new technology.

Many at the time doubted that sound would even last, let alone make such a big impact on the industry.

Today, we stand at a new crossroads, thanks to a new innovation called big data analytics.

What is big data analytics

For those of you who have not yet heard of big data analytics, this is a technology that is certainly not unfamiliar to you.

Already, if you are using a computer online or a smart device such as a phone, tablet or watch, you are already benefiting from big data analytics.

Before the advent of the Internet, it was not practically possible to collect masses of people’s personal data. However, once the Internet arrived, and we all became interconnected, it became possible for companies to collect data about their users.

Companies such as Amazon were able to beat their competition by mining the vast amount of data being collected from its users’.

Every time a user selected a particular product on the Amazon website or made a purchase, for example, Amazon was able to record and store this data for later analysis. This meant that Amazon was now able to extrapolate patterns of behavior that related to shopping preferences, money spent etc.

With this data, Amazon was able to vastly improve the way it did business. By dramatically improving customer satisfaction and the services it offered, Amazon was able to grow into the world’s largest company within a matter of 15 years.

Today, its founder Jeff Bezos is the richest man alive, and most of it is thanks to the interpretation and use of big data.

Naturally, it was not long before all kinds of industries were trying to cash in on big data analytics.

The Birth of Data-driven Moviemaking

The film business also saw massive gains to be had from implementing big data solutions.

In what become known as data-driven moviemaking, big data analytics empowers filmmakers to change their films to make them more appealing to audiences before they are even released.

This revolutionary advancement in predictive analytics means that filmmakers now have a magic wand with which to improve their films to ensure that they will be more commercially viable.

Moviemakers are now able to get accurate feedback regarding everything from the script to the choice of cast. This information, if acted on properly, will almost guarantee better audience reaction and therefore make them more commercially appealing.

Companies such as Largo Films are now offering this powerful new service to all segments of the industry. Data-driven movie making is set to change everything.

Largo AI

But what about the choice of actors and actresses?

Data-driven Moviemaking: Finding The Best Cast

For over 100 years now, movies have been cast by a process that is both inefficient and time-consuming.

Production companies are required to enlist the services of agencies or to go it alone by placing adverts calling for actors and actresses to apply.

The application procedure involved actors and actresses sending in resumes by the 1000s, which would then need to be analyzed by the casting director and their staff. Not only does this process take hours upon hours but it also means that production companies are forced to invest large sums of money into paying for this process.

Once the resumes have been sorted and the shortlist of potential actors and actresses finalized, the casting director must arrange for a casting session to be organized so that they can review potential candidates.

This process requires each of the actors and actresses to be contacted by either phone, email or letter, something which adds to the time and financial burdens of the production.

Once the actors arrived to the casting session, the casting director, the director and other members of the production are required to watch performances by each applicant. This can take hours, often days, and so is very draining on all involved.

Since humans are only humans, mistakes are made and sometimes candidates are overlooked when they might be suitable for the role or at least another role in the production.

It is important to note that the entire cast is finalized according to the opinions of just a few people.

Often, in the case of foreign productions trying to break the American market, for example, the production will cast actors and actresses from the United States to boost appeal.

This can ruin what would otherwise be a good movie. One example is the casting of the American actress Rosanna Arquette in the otherwise excellent Luc Besson movie The Big Blue.

Big data will entirely revolutionize this process by allowing fully automated cast selection based on an actor or actresses’ real suitability to the role and their appeal to the movies’ target audience.

This process will allow the automatic selection of the most suitable actor or actress from casts of thousands of potential candidates.

This will mean that for the first time ever, each part in a movie will get the most suitable actor or actress, including those minor ones such as cameos and bit parts.

The days of the casting director are soon to be truly over.

No longer will personal opinion hamper getting the best choice to cast of a movie, something will mean better movies and the best return on their investment.

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