If you haven’t already heard, data-assisted moviemaking is the next big thing. Through the use of big data analytics, movie productions of all sizes are set to become huge. Big data will impact every part of a movie’s production and distribution.

Everything from the plot to how the movie is marketed will soon be guided by big data. This feedback will allow the movie makers to make decisions based on what audiences will like and dislike. The expected returns on investment will be huge.

Data-assisted moviemaking will also streamline movie production by helping to reduce waste such as ineffective traditional blanket marketing.

Companies such as our very own Largo are leading the way in developing this pioneering new data science. To date, Largo has already helped filmmakers from all over the world to improve their films as well as gaining an accurate predicted gross for their movies.

If you are wondering how to use big data analytics to help improve your movie then this is the guide for you.

How Data-assisted Moviemaking Works

The concept of using data to help improve your movie is not a new one. For years, movie studios have used pre-release screenings and marketing data to help improve the movies they were making.

In the advent of the internet age, the use of data took a giant leap forward. Since nearly all of us now have a smart device of some kind, we are constantly transmitting data to and from our app and product providers.

Sites that include feedback forums are a gold mine for learning the exact thoughts and opinions that we have about movies and TV shows.

movie making

Every single week, hundreds of gigabytes worth of reviews and feedbacks are added to the web. Such a volume of up-to-date data is an invaluable source for companies such as Largo.

We use a whole range of datasets that includes past movie reviews, film gross details, plot and cost information, etc., to allow our sophisticated big data analytic program, LargoAI to identify trends or patterns that might provide valuable insight into our clients’ movies.

However, since LargoAI took several years of development by some of the leading minds in the big data analytics field, not every film production is lucky enough to have one of their own.

If you are interested in using LargoAI to improve your film, you can contact Largo for a free demonstration.

Making Your Own Data-assisted Movie

Making a data-assisted movie involves getting hold of as much data as possible and extrapolating trends or patterns from it.

Without the use of big data analytics software, this could be an enormous task. Keep in mind that the more data that you have, the more accurate the predictions are likely to be. However, it is possible to use data on a much smaller scale. So let’s take a look at where you can use big data to improve your movie.

Plot

The most obvious application of big data other than marketing is with the plot of the film.

With a little painstaking work, through sites like IMDB, it is possible to browse movies by genre and plot to establish the kinds of responses that they have received from critics as well as audiences.

Let’s take a look at the example of the Mafia movie.

A quick search on IMDB for Mafia movies by the year that they were made reveals a best of list from 1970 to the present.

The most obvious pattern you can extrapolate from data such as this is the popularity of Mafia movies during the mid to late 1970s.

Thanks to several international blockbusters such as Francis Ford Coppola’s The Godfather and Godfather 2, the Mafia movie rode high until the 1980s when its popularity decreased.

In the early 1990s, the Mafia movie again gained popularity with audiences.

Once again, it began to wane during the late 1990s, and despite the popularity of TV shows such as The Sopranos and Broadwalk Empire in the 2000s, the Mafia movie was seemingly absent from movie theaters during this time.

With deeper research, it is possible to identify that the mid-70s and early 90s Mafia movies made on average at least double their budget in ticket sales.

However, the vast majority of Mafia movies made in the last decade have struggled to break even. The most recent, Kevin Connolly’s 2018 movie Gotti, could only scrape back $6 million of its $10 million budget.

Despite starring Hollywood legend John Travolta as John Gotti, and receiving reasonably warm critical reviews, the film remained unpopular with audiences. From these to single data points, it is possible to extrapolate a distinct global lack of interest in Mafia movies at the current time.

While the data from the 1990s does show that Mafia movies are capable of making a comeback, the data does indicate that moviemakers should steer clear of this genre at the current time.

Follow Big Data Trends

The same method as highlighted above can be used to identify a range of other patterns. One example is the suitability of a particular actor or actress for a role.

The reason that most Hollywood actors tend to remain within the genre for which they are known is simple, it better guarantees success. If you are thinking of hiring an actor or actress, it is possible to research their background to establish whether or not they are suitable for the role.

So for example, if you were planning to cast Jim Carrey as a Mafia hitman, you can begin by researching whether or not he has played such roles before and what success he is had with them.

A screen test will establish whether or not Carrey can play the part, so this research is simply to establish his bankability and the appeal of him playing such a role to audiences.

By using such an approach it is possible to use relatively small datasets to get a clear picture of certain patterns.

However, such an approach should only be regarded as a basic guide due to the extreme limitation on the amount of data that can be processed by human beings.

For much more accurate data you will need to hire a big data analytics company such as Largo. For more information head to our website.