The spotify-algorithm is great but it is tailored to a broad audience to work for everyone. If you are looking for specific music recommendation-patterns or try to circumnavigate situations, in which the algorithm is stuck in a direction you dont want to go in, you are out of luck under the current system.
I suggest implementing a UI that allows users to adjust the statistical model of the algorithm. I have two primary options in mind:
1. Focus Width from narrow to broad 2. Number of neighbours from high to low
By focus width I mean the statistical deviance the algorithm is set to. A lower value would lead to results that stay closer to the source material (Genre, artist, other songs listeners like) and a higher value would lead to more variety but less correlation with the source-data.
By number of neighbours I mean the number of songs in for example a playlist that are accounted for to recommend a song. A lower value would mean that a smaller set of songs leads to any individual recommended song, which produces songs that closely match each just a few source-songs. A higher value would take a larger set of songs into account for any single recommendation.
There are two more related options I would like to propose:
1. Change direction 2. Forget timeframe
Change direction is similar to reload under playlist recommendations but doesnt just load a new batch, but also changes the source-parameters taken from the playlist a bit, to yield different results
Forget timeframe is quite self-explanatory and is just an option to not take listening-behavior from a set timeframe into account anymore. This allows users to listen to music they dont want recommendations for without having to remember to activate a private session. It also allows user to act retroactively.
At last I want to recommend an option to import a friends algorithm settings, if they share it with you, so you can change to their algorithm in the settings and experience the recommendations as they do.