The music industry is learning a new rhythm through the instrument of artificial intelligence. AI is revolutionizing insights and business strategies and fine-tuning the way we work, connect, learn, and play around the world. Expected to become a $70 billion market by 2020, AI is shifting traditional practices to more sustainable digital spheres.
In the music industry, emerging AI tools are helping reorchestrate the way audiences consume music content. One of the most effective marketing tools industry pros can utilize is the consumer data mined through AI’s machine learning.
In the future, AI-driven data can help the music industry fine-tune its marketing strategies, offering improved insights to maintain harmony between artists, the industry, and fans — all while maximizing profits.
AI is no stranger to the music industry. Since their apps launched, audio and music-facing tech companies like Shazam and SoundHound have utilized AI technologies that analyze a large catalog of songs using spectrograms to measure the various frequencies. But the access to AI-enabled data is starting to shift the music industry into more sophisticated arenas.
Major recording companies like Sony Music and Universal Music Group own most of the content, along with shares of consumer platforms such as streaming services and apps. While major recording companies are granted access to consumer data, it’s the streaming services, such as Spotify and YouTube, that control how people consume music and, thus, who has access to AI-driven data.
Independent artists own a small portion of all the music content available, but they gain data from direct-to-fan platforms like Hive or Pledge Music. Yet many recording industry professionals are just learning how to access and analyze emerging data tools to help maximize their profits.
Here are four machine learning metrics that music industry professionals should use.
Engagement data offers insight into how audiences respond to new music genres, trends, artists, and songs. It can show the number of collections, changes in followers, and the number of plays per payer, all calibrated by the number of saves or collections that include a specific song. Professionals from across the music industry can use this actionable engagement data to attract increased visibility for their signed artists, thereby reaching more fans. Music labels can target audiences and track patterns to make improved business decisions, all while stimulating revenue.
By 2030, Goldman Sachs reports, streaming services will create $34 billion in revenue for the music business. These services will simultaneously generate a consistent and credible source of data that improves insight and outreach to various audience demographics.
Each niche of the music industry has a specific need for data. Streaming services like Spotify use filtered data to transition non-paying listeners into paying subscribers. A major label, on the other hand, operates differently.
A label’s goal is to create filtered data that can help them market songs and turn mediocre fans into dedicated superfans. Spotify tapped into this data by creating Found Them First, a microsite that allows users to see which musicians they listened to on Spotify before they became popular. For labels, this monetizes the idea of early fandom.
Ultimately, these insights are used to motivate subscriber growth, driving fans’ desire to explore artists earlier in their careers.
