Because I didn’t want my case study to be too long to consume, I decided to put a few details on this site so that the interested individuals can take a look at them here.
This part includes :
- Competitive Research
- Prioritization Matrix
- Affinity Mapping
- Information Architecture
- Useful links backing up my conclusions from secondary research
- Initial Wireframes
Competitive Research :
While there is no particular app with this exact solution provision in place, the mainstream applications such as Spotify, Apple Music, YouTube music etc. all have “mood” playlists which are just one size fits all playlists available a search away and are music apps by nature.
None of these applications also have an active mood tracker nor do they have a concert suggestion feature which can increase artist listening rates and ensure a more cohesive bond with the user by allowing them to accomplish one more task related to music experiences.
Yet here’s a quick advantage and weakness split of the two most popular applications :
- Spotify:
- Strengths: Spotify utilizes algorithms to offer personalized playlists like Discover Weekly and Release Radar, which update weekly based on user listening habits. The app integrates social features for music sharing.
- Weaknesses: While Spotify offers robust music discovery features, its recommendations may not always be as precise or diverse as desired by users. Additionally, concert suggestions or mood analysis as a feature are not as prominently featured compared to other aspects of the app.
- Apple Music:
- Strengths: Apple Music employs machine learning to curate personalized playlists and recommend new music based on user preferences. The "For You" section provides tailored recommendations, including new releases and curated playlists.
- Weaknesses: Apple Music's recommendations may not always feel as personalized or dynamic as those of its competitors like Spotify. The platform's social features for music sharing and community engagement are also less developed.
Prioritization Matrix :