DSPs and Radios

Streaming has transformed the way people listen to music by providing them instant access to an extensive library of songs, which is the opposite of traditional radio.However, streaming services have started to resemble traditional radio broadcasts over time.Spotify and YouTube Music have debuted new features that imitate traditional radio broadcasts.Spotify's feature includes an AI-powered voice DJ that will explain to users why certain songs are included in their personalized mixes. Meanwhile, YouTube Music offers users more control over streaming radio stations by allowing them to select up to 30 artists, specify genre, artist frequency, and determine the balance between chosen artists and new recommendations.For instance, algorithmically-generated playlists and ready-made mixes are now commonly used to enhance daily activities such as working out and cooking.Moreover, Spotify's AI-powered voice DJ provides listeners with contextual information on their curated mix of songs, which is similar to what a radio DJ would do. Additionally, streaming "stations" have been introduced.All these features raise the question of where this trend is headed.

It's commonly believed that most consumers tend to be passive. While music streaming services tend to encourage passive listening habits, this is not necessarily a problem as the majority of consumers fall into this category, making them a valuable market segment. Spotify and YouTube are popular platforms with a broad audience, so it's logical for them to focus on serving the mainstream market. Additionally, background listening is a significant revenue source for both streaming platforms and rightsholders. However, the success of traditional radio was partly due to its counterpart, physical music sales, which catered to more active music fans.On the other hand, streaming platforms provide a similar, relatively passive experience for all users, without necessarily catering to those seeking more interactive or engaged experiences with music.I think there are two potential outcomes for the future of music streaming. The first possibility is that platforms like Spotify may become the mainstream hub for passive listening, serving as the modern version of radio, while other platforms like TikTok or SoundCloud could be where fandom and culture thrive. Alternatively, streaming services could strive to cater to both active and passive listeners, which would benefit everyone involved. This approach could include introducing new revenue sources such as fandom badges, NFTs or a "plus" tier with social features, resulting in a better experience for fans and allowing artists to nurture their fandoms.

Spotify and YouTube's latest features offer consumers more control over algorithms, creating three distinct types of users that one individual might switch between depending on their needs; active music fans who are dissatisfied with the current streaming experience and crave a more engaging, passive consumers who are content to rely solely on algorithms and lean back while listening to music, interactive experience, consumers who fall somewhere in the middle, who prefer algorithms to do the work but want to have some level of control and input over the music they listen to.

When users first sign up for music streaming services, they are often asked to create lists of their preferred artists. However, this process should be ongoing as streaming services seek to better understand users' needs. Currently, streaming services offer either fully on-demand or algorithm-based listening experiences, with little in between. Ideally, users should have the ability to continually customize their algorithmic experiences and provide active signals, both positive and negative, to improve their listening experience.If the playlist and section icons on the Spotify home screen were more like widgets on an iPhone, users would have more control over what they see and could add, delete, or move them around based on their interests. Additionally, AI could play a role in this process, with tools like PlaylistAI allowing users to generate hyper-specific playlists based on specific requests and even images. For example, users could request "upbeat music for working out, all female artists, nothing from the '80s."By allowing users to have slightly more control, streaming services can gather a wider range of active signals that algorithms can use to improve the listening experience.