Non-traditional (and surprising) applications of big data analytics
Big data analytics have become a standard in many industries and it has been a game-changer for many businesses around the world.
Around 55% of companies around the world use big data analytics to improve their performance and keep an eye out for changes in the market and customer behaviour.
Over the years, big data analytics have opened new horizons for all kinds of industries. That being said, big data is also being used in some very surprising ways that we would have never imagined in the past.
In this post, we’ll take a look at these non-traditional applications of big data analysis.
Smart transport solutions are quickly becoming a feature in most modern cities around the world and where there is smart transportation, smart parking technology will follow.
Today, real-time big data and information from the payment systems in parking lots are used to provide smart parking solutions to drivers.
With big data on weather patterns, daily events, the amount of time a car spends in the lot and the time of day, parking lot staff can find ways to maximise parking prices and utilise the space in the parking lots effectively.
Organisations that require large parking spaces, like hospitals, airports and community centres can optimise their revenue and staffing strategies effectively thanks to big data analytics.
According to Wen Sang, the CEO of Smarking, airports generate about 20% of their revenue through parking; this revenue can potentially increase if airports adopt big data analytics.
Demographics like age, race, social standing, gender and sexuality play a major role in determining how potential customers will react to marketing. Understanding the emotions that these marketing campaigns and advertisements instil is also important.
The emotional effect an advertisement has on people will determine how they will see the product and how they will interact with the business. Now, big data analytics can be used to measure the emotional impact these campaigns have on people.
Data collected using facial recognition software on videos or photographs of people reacting to the advertisements is analysed to gain insight into what emotions people feel when they viewed the advertisements.
If people displayed emotions a business expected from them, the advertisement would be a success and they can predict how potential customers will approach them and their product.
Using this emotional data, businesses can further optimise their campaigns for desired reactions from their customers.
Big data analytics on emotions is also being used in the movie industry, especially to measure how people react during horror movies. With big data, movie studios can identify what kind of content brings out fear in their audience and make horror movies that scare people the way they want to be scared.
Movie scripts and casting
Film production companies want their movies to engage their audience and their cast to be relatable.
Nowadays, film companies use big data gathered from streaming services and social media to get an idea of the kind of stories people want to watch, with the actors that viewers feel are most suited for certain roles.
According to some filmmakers, movies have become very commercialised and tend to follow similar patterns and stories. Major film companies do this to protect their investment in these movies.
Big data helps film companies have a better understanding of the current trends and what moviegoers are interested in, enabling the creation of more unique and diverse content that can satisfy a range of audiences.
Every decade or so, a new musician walks into the scene and quickly becomes popular with the masses.
Thanks to the internet, social media and data collection technology, it’s possible to predict who will become a superstar in the music industry.
Recording companies are always keeping an eye out for new talent and today, they use big data analysis to find their next profitable music icon.
These companies use data analysis software to gather big data from a potential music icon’s social media to gauge their popularity and decide if they are worth investing in. They can also use this data to identify which social media platforms the musician has the biggest following on, and use this platform for their marketing campaigns.
Big data analytics pave the way for many new possibilities
The number of potential uses for big data analytics is seemingly endless.
From filmmaking to measuring emotions, big data analytics can cater to virtually every industry and leverage their success.