Melodia’s context-based recommendation engine offers personalized song suggestions given the user’s current moment. These suggestions are meant to provide the user with alternative music recommendations that best fit their moment according to their unique taste and past listening patterns.
Melodia’s API offers three types of moment suggestion results:
These suggestions comprise the top track recommendations according to the user’s current context (i.e., time of day, day of week, activity, location, etc.). The recommendations are personalized to the user’s taste profile and optimized according to their listening history and feedback. The following method is used to get the suggestions: moment.getMomentTracks
When the user is about to undertake a particular activity (i.e., running, driving, etc.), they can choose to get suggestions appropriate for the given activity. Moreover, as opposed to simply suggesting generic playlists for a given activity like other music services, Melodia’s recommendations are uniquely personalized to the user’s taste and listening profile. In addition to the selected activity, Melodia’s engine also optimizes these suggestions to the user’s other contextual data (e.g., time of day, location, etc.).
Optionally, for platforms such as fitness and workout applications, Melodia also offers the ability to futher customize the suggestions to a specific range of tempo. For more information how to call the API for these suggestions, check out moment.getActivityTracks
Moment suggestions may also be grouped by genre. For example, Melodia may predict from the user’s past listening history that they will enjoy New Age music at this moment. In this case, Melodia will offer a group of personalized track suggestions with this genre as the common theme. The following method is used to get these suggestions: moment.getGenreGroupTracks