How to Leverage Music Algorithms for Music Curation and Getting Discovered as an Artist

Music discovery algorithms are systems that use music consumption data, such as listening habits, search histories, and genre preferences, to recommend new songs to users. They then generate playlists and recommendations, focusing on factors like genres, tempos, moods, and listening histories to create personalized experiences for each user. Recommendation-centric playlists, autoplay features, and “For You” sections are all driven by such systems.

In this context, artists need to know that algorithms can shape how their listeners discover their music. Next to the previously mentioned factors, metrics like song skips, saves, and completion rates can further decide which ones of their tracks get pushed to a wider audience and which ones don’t.

Most widely used platforms provide algorithm-based music discovery tools. For instance, YouTube does so through its suggestions on its home page, which change every time you refresh the page. It also shows a list of suggestions on the right side of each video you watch on the platform.

Spotify has multiple options for music discovery, ranging from artist, song, and album radios to algorithm-based, personalized playlists such as daylist or release radar. While each radio consists of a list of tracks and artists similar to the track or musician you accessed it through, its playlists often consider your broader taste in music, allowing you to explore songs across multiple genres. SoundCloud revolves around a similar system with its song stations that can be accessed by clicking on the box with three dots under each uploaded track.

Finally, TikTok and Instagram take user engagement data (from likes and comments to watch time) to show similar content to the one you regularly engage with. Although the platforms are not strictly limited to music, they can help a lot with finding tracks that match your taste.

Artists can optimize their presence on algorithm-driven platforms by making sure their tracks contain accurate metadata, which they can add during the music distribution process. Submitting to playlists—both editorial and user-generated—and posting your music on social media platforms can further boost visibility. The latter may work even better when the visual content is engaging, as it gives users reasons to spend more time with your content. Finally, those willing to invest in their marketing on social media can pitch their music to larger pages, which can then use it as a sound in their content to expose a larger audience to their track.

If you’re looking to leverage algorithms for music discovery, we’re happy to give you some suggestions as to how to do it best! First, decide what exactly you are looking for—is it a genre you want to dive into, or are you trying to gather a selection of songs that encapsulate a specific mood?

• Chosics. Before diving into how to use your platforms of choice, we recommend trying out Chosic, an online Spotify playlist generator. The tool allows you to create playlists with similar songs, artists, genres, moods, BPM, or even playlists. It is a more detailed, intentional way to leverage the Spotify music database.

• Spotify reel-style scrolling feature. Regarding Spotify, we recommend finding the reel-style scrolling feature integrated into the dashboard of a song you like. This way, you can explore song snippets and find new tracks quickly.

• Spotify recommendations. Another benefit of Spotify is using its playlist recommendations under the last track in your playlists or, as mentioned earlier, using song, album, or artist radios to discover similar tracks to the ones you enjoy.

• YouTube. Regarding YouTube, it would make sense to set up a separate account to avoid receiving content suggestions that have nothing to do with music.

Instagram & TikTok. The same applies to Instagram and TikTok. Here, it also makes sense to follow pages that revolve around music discovery and have their content recommended to you in your feed/FYP regularly.

While algorithms can open doors for discovery, they’re not always predictable and can sometimes prioritize trends. Additionally, they are not always accurate, especially when it comes to niche genres or artists who sound somewhat more specific than their mainstream counterparts. Finally, while algorithms can pick up on underground music, they do not necessarily prioritize rather unknown artists. As a result, you might end up encountering more popular tracks that you already know than the lesser-known, nuanced ones that you’re looking for.

This is where human curation and deep, time–consuming research can help. If you do not have enough time for it, you can at least try to discover playlists curated by humans (like ours!) to discover new songs. Finally, let’s not ignore that the two approaches often go hand in hand, with individuals taking their time to explore algorithm-based suggestions and then diving deeper into the artists they come across, their collaborators, or members of the labels they are signed to.