|Experts stated that the growth of the music streaming industry is due to the internet. / Photo by: Horth Rasur via Shutterstock|
Technology has fueled the growth of the music industry for the past several decades. Its evolution from vinyl records and cassettes to CDs and MP3s to the current music streaming platforms show how it has benefited from the rapid technological advancements.
The Recording Industry Association of America (RIAA) reported that the 2017 net profit of paid music subscriptions reached $1.49 million, which is an increase of 49.5 percent. This is the highest yearly growth since 1998. Experts stated that the growth of the music streaming industry is due to the internet. The technological advancements of the internet increased at a rate of 200 percent between 2000 and 2018 across the globe, taking the industry to new heights.
Comparitech, a pro-consumer website providing information, tools, and comparisons to help people to research and compare tech services, reported that there has been a strong shift toward streaming music in 2017 as downloads revenue declined by over 20 percent and physical revenue by over 5 percent. In the same year, streaming revenue accounted for 38 percent of all music industry earnings with a total of around $6.6 billion. By the end of the year, there were over 125 million paid music streaming subscription accounts.
Music services are also improving every year as major music service providers Spotify, Apple, Pandora, and Amazon are integrating artificial intelligence into their music streaming platforms. Today, music streaming services are utilizing technology to understand users’ tastes through AI.
Improving User Experience
Most of the music streaming platforms are using AI in several ways, including improving search engines, increasing storage, and enhancing the overall experience. At the same time, they are using machine learning to take the industry toward a whole new path. Back in the day, users had to physically shop for vinyl records and cassettes. Then the time came when we were able to search for songs and artists online. With AI and machine learning, music streaming platforms are bringing new songs, albums, and performers to us.
This has happened as algorithms learn the preference of the users in terms of genres, albums, and performers. Not only AI and machine learning remember users' streaming history, but they also analyze the vocal styles, chords, and even the pitch of a song to find similar playlists. They analyze the data so they can suggest new songs, artists, and albums that the user might like. The good thing is that the more the systems are fed with data, the more accurately they can process similar information in the future.
For instance, Spotify offers weekly music recommendation service called Discover Weekly based on users’ previous playlists and personal preferences. According to PreScouter, an online site that provides research support services to help business leaders make better R&D, product development, and corporate development decisions, the music streaming platform skims 100 million users to find people who are listening to similar playlists. To make accurate recommendations, it finds songs based on the users’ listening tastes and on the music that other users with similar tastes listen to.
|Spotify offers weekly music recommendation service called Discover Weekly based on users’ previous playlists and personal preferences. / Photo by: r.classen via Shutterstock|
Improving the Quality of Streaming
On the video-streaming platform YouTube, some videos tend to load longer than others. This is because AI orders the data systems which videos users are more likely to click on. It will then ensure that the bandwidth usage increases. On music streaming, AI gathers data on what users stream the most and when they stream through data science, a mixture of scientific methods and processes to glean insights from data.
This allows the music streaming platforms to know when they need to cache websites on regional application servers for shorter loading times. According to an article by Media Update, an online publication dedicated to reporting on the latest news and information, this is important because the amount of data available continues to increase.
Identifying the Next Musical Stars
AI has allowed music streaming platforms to constantly experiment with a wide range of applications. Personalized recommendations not only benefited the consumers but also the artists. It serves as an avenue for many amateur artists across the globe to showcase their work and present it to the world, allowing many musicians to have a direct audience even before gaining popularity. This has paved the way for many artists to be discovered not only by the listeners but also by music producers.
For instance, Sodatone, a Toronto-based tech startup, has an algorithmic platform that combines social, streaming, and touring data to identify promising unsigned artists. The company was acquired by Warner Music Group in March 2018. Aside from Sodatone, tech giant Apple has also been investing in this after acquiring Asaii, a startup that specializes in A&R-boosting music analytics. Both of the acquisitions show a trend toward searching for technologies that can analyze various industry data points to predict who the next big stars may be.
According to Entrepreneur, an American magazine and website that carries news stories about entrepreneurship, small business management, and business, the vast amount of user data collected by music streaming platforms will help discover talented musicians, signifying the creation of a symbiotic avenue for growth in the industry.
Through AI and machine learning, users can ultimately enjoy listening to songs that fit their music tastes. It will become easier to listen not only to the music of their favorite artists but also to those of newcomers in the industry, helping to make their music be heard across the globe.