Users Agree That YouTube Music Does One Thing Better Than Other Streaming Services

One of the best things about using a music streaming service is getting to discover new artists, bands, and tracks while enjoying your old favorites. Services like Apple Music and Spotify can create personalized recommendations for you based on your listening history, taking into account factors such as your downloaded and favorited tracks, playlists, searches, and genre tastes to serve you up new music that their algorithms determine you'll like. However, these recommendations aren't always on the money.

As a result, some are ditching these music streaming services in favor of YouTube Music, which, according to Reddit users, offers a superior algorithm and therefore more accurate recommendations than its rival companies. For example, Spotify users have reported that the platform's recommended playlists and radio queues regularly feature the same tracks and artists largely based on recommendations from your perceived genre taste rather than more nuanced factors. These recommendations often feature tracks that listeners simply don't like and have to skip. This repetitive algorithm is just one of the many uncomfortable truths about using Spotify — though Apple Music has its disadvantages, too.

As a Spotify user, when I opened the YouTube Music app for the first time, I was impressed to find the platform had already created playlists for me based on my prior YouTube watching history. As a result, rather than simply recommending the same rock tracks that Spotify tends to do, it had created a '"Supermix" of songs across my tastes that not only included some familiar favorites, but tracks, artists, and deep cuts I've never heard before. These recommendations become more specific the more you listen, as this allows YouTube Music's algorithm to craft your taste profile.

Like other music streaming platforms, YouTube Music takes into account factors such as whether you click like or dislike on a song, the songs you repeat, and the length of time to listen to tracks to create your taste profile. YouTube Music's algorithm places more emphasis on your interactions with its recommended content, such as its playlists, helping to fine tune the music it suggests. A successful recommendation is determined by signals such as the user completing the song, saving or replaying the track, and explicit feedback, such as liking or disliking, with skipping a track holding little weight. In addition, YouTube Music will pull in information from your YouTube and Google searches and watch history and third-party partners to better understand your preferences and make more suitable recommendations.

While it can take time for the algorithm to fine tune and improve its recommendations, many users agree that YouTube Music's algorithm is much better than that of other music streaming services, including one user on Reddit who said the service is "criminally underrated." Another user said: "Just keep listening to music and eventually it will figure out what you like. I swear their algorithm is ahead of the other streaming services by a long mile." This user pointed out how the algorithm helped them discover artists or tracks they otherwise wouldn't have listened to: "In my opinion ytm is good at introducing me to new songs or artist that I actually end up enjoying." Other posts show support for YouTube Music because of its regularly updated "Supermix" playlists that incorporates various genres, how its playlists are less repetitive than Spotify's, the accuracy of many of its recommendations, and the convenience of its inclusion in YouTube's Premium Individual membership.

A 2025 poll on Reddit shows that the majority of users are satisfied or very satisfied with their experience when it comes to this streaming service, but, as always, there are disadvantages to YouTube Music, including no desktop app and playlist shuffling limitations. Some users have expressed frustrations over the platform's recommendation of AI-generated music, who have found that the algorithm's focus on recommending tracks based on your recently listened to music and the lack of options to exclude certain music from your taste profile can result in some odd recommendations.