By: Shraddha Gopalakrishnan

 

Exponential growth of technology has brought about a new industry called “Database Marketing.” This type of industry collects, aggregates and brokers personal data and information. Data brokers represent this wave of change that primarily deals with how personal information is handled both online and offline. This dramatic shift has created a new movement towards what is known as “Big Data”.

Big Data is simply made up of raw “little data” which give deep personal insight into a consumer’s individual and purchasing profile and the consumer’s habits. For example, Big Data is demanding the music industry to change its business model from what it traditionally was. Online streaming services such as Spotify, Pandora, iHeartRadio and many others have changed the way music is distributed and how it is discovered. These services are being able to customize user experience based on the customer’s personal “on-platform” behavior and music preferences.

This blog is all about “How Big Data is revolutionizing the Music Industry” and it’s going to surprise a lot of people. You might think how can data influence Music? Well, the truth is there’s actually much more going on behind the scenes than just producing the music.

When it comes to the music industry, we have music software companies or record companies with goals of producing quality music and they are well aware of not creating music which people dislike. Their mission is to attract a broader spectrum of audiences into music with additional entertainment media such as albums, concerts and merchandise related to hit songs where big data comes as an aide.

The way people listen to music has changed in the past 20 years. In Prior years there were cassettes and CD’s available at the stores; the sale of the cassette or CD was the end for music companies’ data. These formats of music data could be played once or thousands of times but there was no way anyone could know that person’s listening preferences. Both contained multiple songs that may or may not be played or skipped.

Music sellers in the past decade have mastered the art of virtually eliminating bad tracks, which removes the artist’s creativity in music. One cannot help but ponder what if you only have good music; will you ever have new music i.e., the music the music apps don’t want to publish?

Music sensations would go on world tours and meet their fans in-person which is clearly not the case with newer technologies. Everyone turns to either YouTube, SoundCloud or Spotify for tunes. Hence, the real-time data i.e., currently what music the general public listens to can be closely monitored using data management which most companies are trying to practice in order to get monetary benefits.

 

How does real-time data act as an advantage?

The companies are now able to easily figure out patterns and predict the next hit song. There are various kinds of songs on every platform— Pop, Rock, Indian, Classical, Jazz, Melodies, Retro and patterns based on the genre of music their users are listening to. These are released regularly by Spotify or Amazon. Music and entertainment companies benefit from music analysis and are able to see the potential of songs getting targeted to huge crowds. For e.g., if the trend goes more towards classical music, companies will urge the artists to create songs in that area. Moreover, marketing departments plays an essential role in ensuring the songs sold are highly promoted – the more the promotions, the more the audience speaks about it on social media. This which in order gives the companies a feedback pattern which allows for an idea of when to release the music/video and when to schedule the concerts.

The basic strategy is music companies have greater insights and hence your liking of songs has changed from what you genuinely like to what music companies recommend or nudge you with. There are also numerous tuning apps out there which can make a really soothing song upbeat and push those elements into your sound playing interface. Producing a “hit song” has become cardinal for music companies and it is sad that songs nowadays are a hit not just based on pure talent. There is strategy, analysis and, prediction behind a song being targeted to a listener.

 

How AI identifies a new genre?

Being someone who listens to A LOT of music, I got curious as to how AI can manipulate a song. Imagine a computer being able to understand how sound works to a point where it can not only tell the difference between genres, but it is able to change the genre of any song you give it.

These AI agents involve unsupervised machine learning models, libraries and neural networks while training the models to ignore certain characteristics so as to avoid instrument bias. Further, AI agents help to power human creativity for music. To implement a model where the genre of a song is shifted, we provide it with a picture representation of the song. After that, we merge it with the style of a song from another genre to create the new song.AI has the capabilities to potentially revolutionize the music industry because of how advanced it’s understanding is of the music when trained properly.

Figure 1: A bar graph comparing number of technical papers on Neural Networks spanning 2 decades.

The visual validates the increased contribution of AI market post 2016 and that there is a high demand for using bid data concepts in AI analytics.

 

How can RIG’s solution contribute?

RIG has the most powerful service – Dynamic Trust that can act as an AI Validation solution for any Music Streaming Apps. This robust tool will pull data from different social media websites, music-related platforms for millions of artists around the world and help a Streaming company define and validate music data needs and of course their budget. The idea is to bring to the table an exploratory springboard while watching the field of music analytics evolve.

 

How long can the advantage last?

Every process in this world, has it’s pros and cons. Though, the music companies are benefiting a lot from data science algorithms and mere predictions, it is true that not everything lasts forever. Companies are now able to know what people prefer listening to; but the question is are people’s preferences of songs determined by the rhythm, melody and tune or simply maneuvering a successful record? Going forward, will our choice even matter? Is it a never-ending-cycle where history of our songs list is utilized to influence and predict our current likings which in fact will impact our future favorites? Give it some thought and reflect.