We used our AI to analyze 5,200 viral songs from 104 weekly charts in the USA from 2019-2020 to see if we could discern useful patterns in Genre with actionable takeaways for artists and labels.
Chartmetric’s Trigger Cities were driven by rigorous analysis of user behavior. The question is, are there any underlying, purely musical factors driving this behavior? We use our AI to investigate.
What makes a hit? We used our Hit Potential algorithm to analyze two commercial hits – Dynamite by BTS and Girl Like Me by Black Eyed Peas and Shakira – by the second.
Many commercial music decisions are made based solely on gut feel. But given that 21m+ tracks are released on streaming platforms yearly, A&R executives know what it’s like to be inundated in low quality demos. The question: Can an AI be trained to help in this process?
Xiao’an puts our AI to the test as he explores how the tags of each constituent part of a song differ, and how this impacts the tags assigned to the complete song.
Our AI listened to the two different versions as Xiao’An explores the aspect of music covers.
Major Is Happy, Minor Is Sad? If you’ve ever heard anything about chords and harmony,…
In this post, we take a deep dive into the effects of musical interpretation, where we explore different musicians performing the same classic music.
Which Southeast Asian country should you market your music in? In this article, we learn how we can apply data to our decision making.
How can one tell when a piece of music is going to go viral? We look at each of the weekly top 20 viral tracks on Spotify in Southeast Asia to extract information about different tastes in the region.