How Data Science is Transforming the Film Industry?

Data science, armed with pioneering technologies like Artificial Intelligence and Machine Learning, is creating waves of transformation across all domains of the industry. From the IT sector to healthcare and governance, Big Data and Data Analytics are reshaping the usual business processes to make way for innovative and “intuitive” ones.

We say intuitive because of the greatest strengths of Data Science is that it leverages data to gain useful insights into the customer’s mindset and the market situation. 

Big Data refers to large amounts of data gathered from multiple sources such as social media, public data sources, and company databases after which it is analyzed using AI/ML techniques and tools to make accurate data-based predictions.

Ever since Big Data has come to the limelight, it has become a prime attraction for enterprises and organizations. Every company wants to leverage Big Data’s potential to extract valuable information hidden within the data and use those insights to shape future business decisions. 

Continuing its tradition of expansion, Data Science has made it to the film industry as well. Data Science in the film industry aims to leverage Big Data and Predictive Analytics to provide a highly personalized user experience, predict customer preferences, find ways to optimize content and make an array of predictions that can help minimize losses. 

Data Science in Film Industry

Data Analytics is a game-changer for the future of the film industry. Informed decision-making is critical to a film/show’s success, and hence, acquiring high-quality, relevant industry and customer data can be excellent for customer retention and boosting profits.

Predictive Analytics can help filmmakers/producers, production companies, and marketing executives to understand viewer habits and taste better, predict pre-release trends, and most importantly, take data-oriented decisions. 

Some of the major parameters that Analytics experts use to predict the success of a movie/TV show are star value, the popularity, and sentiment created by the same among which particular segment of the audience. By analyzing these insights, Analytics experts can get a general idea of the pre-release buzz and help filmmakers and producers shape the production and marketing strategies accordingly.

One of the biggest guarantees or driving forces behind a film’s success is accurately predicting what the audience expects from the movie or wants to see in it. In 2018, 20th Century Fox (now acquired by Walt Disney) revealed how it uses ML to analyze the content of movie trailers.

By combining Google servers and TensorFlow, 20th Century Fox developed Merlin, an “experimental movie attendance prediction and recommendation system.” In a test run, Merlin analyzed the trailer of “Logan” to predict other movies that might interest the viewers of “Logan.” Surprisingly, eleven out of twenty predictions made by Merlin were correct!

Thus, by collecting relevant data from various movie trailers and comparing and analyzing those trailers, Merlin can predict what kind of films might interest the people who watched a particular movie trailer. Of the twenty predictions of Merlin, five of the actual movies were chartbusters – 

  • Batman v. Superman: Dawn of Justice
  • John Wick: Chapter 2
  • X-Men: Apocalypse
  • Doctor Strange
  • Suicide Squad

Merlin’s analysis of Logan’s trailer pointed out that the audience was interested in superhero movies that starred a “rugged male action lead.” And even though Merlin’s predictive capabilities aren’t perfect, it is certainly an excellent example of how far Data Science has evolved in the past decade.

How can Data Science help the Film Industry?

Here’s how Data Science helps the film industry:

1) Choose The Right Star Cast

Casting the right actor befitting for a particular role is one of the toughest decisions to be made in a film. One cannot help but wonder, what if instead of actor X, actor Y played a certain role, would it be as successful? For instance, if Leonardo Di Caprio played the role of Captain Jack Sparrow instead of Johnny Depp, would he suit the part better?

Thanks to advancements in Data Science, you no longer have to wonder – you can get concrete results. Cinelytic is a platform that uses ML to predict how a movie would perform in the box-office if a member of its cast is replaced with someone else.

It uses historical data of the past movie performances of actors and matches it with the actor’s talent and the theme and genre of the movie in question to find out if an actor would be fit for a specific role in a film.

2) Screenplay Analysis

Using AI/ML for analyzing the screenplay of films can greatly help to improve the quality of movies. ScriptBook is an excellent case in point. It can analyze movie scripts and provide you with a detailed report within minutes. 

All you have to do is, load a PDF file of a movie script into ScriptBook, and it will generate an analysis report in just five minutes. The report will contain the analysis of the movie’s characters, the protagonists and antagonists, the emotional quotient of individual characters, the age rating of the film, the target audience of the film, and the possible box-office performance.

3) Enhancing Ad Performance

According to a recent study by the University of Iowa, Predictive Analysis can analyze every aspect of advertisement campaigns of films for higher marketing success. The regression analysis of the study highlighted the most crucial factors for a movie’s success. 

 Thanks to Data Science techniques, filmmakers and marketers can now predict their ad campaign performance even before they launch it. In 2018, Walt Disney proved this with “Solo: A Star Wars Story.” While the movie was made at a budget of $250 million, it failed miserably at the box office.

However, the film did manage to earn around $213 million. How? From the revenue generated from its ad campaign. The ad for the movie came out way before the teaser (a month early) and earned in full swing.

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4) Personalized Recommendations

Video-content streaming platforms like Amazon, Netflix, and Hulu have long been leveraging the power of recommendation engines to create personalized recommendations for individual customers.

These platforms harness data to understand the kind of content a user resonates with the most and creates an exclusive list for the user based on his/her taste, liking, and search patterns.

If the movie industry were to use customer data to understand their demands better, half the problem would be solved. Filmmakers would know what content they should base their movies on and what kind of films would perform well at the box-office.

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Concluding Thoughts

Thus, Data Science holds immense potential for the film industry. With the right data at their disposal and the right Data Science tools, Data Scientists can help filmmakers overcome many challenges involved in the film-making process.

It can make nearly accurate predictions related to the box-office, create targeted marketing campaigns, choose the right cast for a film, and so much more. 

In the future, as Data Science advanced even further, we can look forward to many more such intriguing things in the film industry.

How does Netflix make use of big data and AI?

You may have noticed that after watching one series/show on Netflix, you automatically get a list of the shows you may like (recommendations). Now that’s possible only with the help of data science. There is a varied selection of posters for each Netflix program, each of which caters to a distinct set of fans. The algorithm offers a better response in recognizing the users' genre since it accumulates data and information about the user based on the thumbnails. Who doesn’t talk about the streaming quality of Netflix? With the help of AI, viewers may stream high-quality video without interruption even during busy hours thanks to the pre-positioning of video assets closer to subscribers.

What are AI scripts?

Advanced Insight Scripts (AI-Scripts) provide devices the intelligence they need to automatically identify and report hardware and software failures, as well as other functional anomalies, in order to maintain optimal network uptime. A device is considered to be AI-Scripts-enabled if AI-Scripts are installed on it. When any defined event happens, such as a failure to allocate memory for a process or a hardware failure, an AI-Scripts-enabled device may automatically identify the event and notify it to the network operator.

Is Alexa an example of artificial intelligence?

Alexa and Siri have found a place in many households now. They aren’t just convenient, user friendly digital tools but they are great examples of AI. So, yes, Alexa is an example of artificial intelligence.

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