Artists still have the freedom of producing music or singing songs as per their or their brand’s choice. However, the music industry is evolving beyond just producing music using data science.
Big data is driving almost all industries. The automobile industry, with the help of big data and enabling technologies like AI, machine learning, data science, etc is developing autonomous vehicles. Similarly, in the retail industry, big data is used to keep pace with changing market dynamics, consumer behaviours, etc.
Data science is the process of mining valuable information from raw data using methods like data engineering, machine learning, data mining, database, data visualization, signal processing, pattern recognition, etc.
Let’s see how the music industry is leveraging big data and data science in this article.
Data-driven music production & promotion
Every artist has their own style when it comes to producing music or singing songs. So, can big data influence music?
The answer is quite complicated.
Artists still have the freedom of producing music or singing songs as per their or their brand’s choice. However, the music industry is evolving beyond just producing music.
Recording companies are under constant pressure to produce quality music. Also, producing the next big hit is a challenging task for music companies as they cannot afford to produce music that does not match their audience’s likings. After all, no music company wants to fail their audience. Furthermore, the survival of a music company does not just depend on the raw talent of the artists. Many other factors like marketing, merchandise, audience building, etc, play a crucial role in the growth and growth of a music company.
Also, technology has greatly changed the way we consume music today. Over a couple of decades ago, cassettes and CDs (compact discs) were used by companies and distributors to sell music albums. Artists would travel across the globe to connect with their fans. Now the situation has changed altogether with the rise of social media.
While cassettes have become obsolete, we can hardly find people who buy CDs to listen to music today. Instead, people use YouTube and Spotify to instantly and freely listen to their favourite tracks. Also, social media is enabling budding artists to self-promote themselves and quickly climb up the success ladder. On the other hand, this is benefitting the music companies as well. Through data science, music companies can comb through large amounts of social media data to understand the preferences of different audiences.
The dawn of music analytics
The music industry is today a big business that generates turnover in billions each year. To better understand the use of data science in the music industry, let’s take a real-time example – Spotify. Ever wondered how the music streaming app is able to provide recommendations that match the user’s preference? How the company is able to regularly release trending music albums according to their audience’s likings.
Companies like Spotify leverage data science to see through their audience and predict the next big hit. For instance, if the trend is dance music, then the companies will nudge their artists to create dance music. They then use music analytics (refers to the process of analyzing music trends) to determine the release of albums and songs.
Substantial data can improve advertising, monetizing strategies along with the apparently former belief of musicians creating a sustainable living in their songs. All in all, the huge data may improve the key use of music bringing folks together.
Data science has certainly disrupted the music industry. While data science was primely used to boost revenue, it has also benefitted the music companies in many other ways like predicting trends, determining the best time for an album release, finalizing concert dates, etc. Overall, data science is not likely to leave the music industry any time sooner and will continue to create lasting impacts.