Music is a highly personal experience. Ask 100 people for their favorite song, and you will get 100 different answers. We are in an era where listeners have more choice in musical content than ever before, but finding that balance between the comfort of familiar songs and exploration has created a new challenge for labels and streaming services alike: loyalty. A la carte culture has left major music players scrambling when it comes to giving users the type of musical experiences they crave while protecting their own intellectual property. Regardless, one thing is clear – data is transforming the music industry and those with a handle on it are the ones who will succeed.
First, some numbers. According to Digital Music News, “Audio on-demand streams set a new record high in the US of 534.6 billion total streams. This number rose 42% over 2017… Total on-demand streams also set a new high last year with 809.5 billion streams, up 35% over 2017’s 598 billion.” Simply put, streaming is how people are listening to music, and this is unlikely to change anytime soon. Streaming services, such as Spotify, TIDAL, and Apple Music provide whatever music a listener wants. But most people still want that radio-like feel of not quite knowing what song will be played next. This is one major aspect that those major streaming companies will use data.
Both Spotify and TIDAL have begun to experiment with personalized playlists. Spotify’s popular rap workout playlist, Beast Mode, has become personalized, where the goal is that no two listeners would get an identical version of the same playlist. The trick is for the algorithm to personalize the experience so that it says something about the listener. Spotify is trying to build an ‘a la carte’ experience that simulates those passionately curated playlists we used spend countless hours making, but generated through data.
Data is also being used to try to address a travesty that has plagued the music industry since its inception: the treatment of the artists. TIDAL, a streaming company created by major artists such as Jay Z, Beyonce, Madonna, and others, are trying to give artists their fair due. Their website states, “TIDAL pays the highest ratio of royalties vs. revenues to music creators of any streaming service and equal rates are paid to artists regardless of whether they’re signed to a major label, an indie label, or not signed to label at all.” This equity equality does more than just right a wrong—it helps with branding, marketing, and bringing in new talent.
Tencent Music, a Chinese company, is trying to monetize music in China, which has over 1.3 billion sets of ears, and where a whopping 99% of the music was pirated as recently as 2011. Tencent is using data to find the best reasons for consumers to pay for their service. In Tencent’s case, it is the listener’s ability to use music in shareable videos. “To capitalize on this new wave of consumption, artists cannot solely rely on digital music downloads alone anymore — so getting their work onto a leading short video platform has become one of the biggest music promotional opportunities of this generation,” Rebecca Yang, co-founder of entertainment production company IPCN, recently wrote in Music Business Worldwide. If companies can crack how to monetize Chinese listeners, it will lead to a tremendous windfall in a giant and largely untapped market. Soon, China may be as important to the music industry as it is to the film industry.
Meanwhile, smaller companies are using data to help undiscovered artists break out. As Martin Talbot, chief executive of the Official Charts Company states, there “is a new generation of smaller companies coming through who are more aware of data as a starting point rather than as afterthought.” Darren Heitner, of Inc. cites, “Snafu Records uses big data from YouTube, SoundCloud, and other platforms to find undervalued musical artists. Snafu aims to provide a platform that scrapes the Internet for undervalued music by looking at performance analytics such as fan sentiment, musical similarity to other hits, and machine-learning driven prediction models. Once a song is flagged as an early riser, Snafu Records seeks to buy the rights to the song and market it further after purchasing the rights, betting that the cost of acquiring the rights will be less than the net gain of that song’s performance over time.”
This is a good example of smaller, tech-savvy companies using custom tools to harvest and extrapolate data in order to give them an advantage in finding the next big thing. To learn more about how Lineate connects the music industry to the data they need, drop us a line on our contact us page!