Your workout buddy boosts your athletic performance.
Beast Pulse is a mobile application enhances user's workout experience by playing series of songs matching to user's heartbeat rate. It scans the user's heartbeat rate through devices like Fitbit and plays the song when it detects the heartbeat rate change.
I first began investigating at pre-existing music players like Spotify, SoundCloud, and Google Play.
In the case of Spotify, it had a cross-platform app that allowed users to search for music, and get recommendations based on what they’ve listened to. As a discovery platform for music of all kinds, it provides playlists categorized by the beats per minute in songs. Spotify has curated playlists, song radios, and and a variety of recommendation features based on user data algorithms.
What is the Problem?
Does your workout sesison the often get extended due to searching for the right songs?
The problem of using the current music player apps(like Spotify) is that they categorize workout songs by bpm. Unless users do exercise that keeps their heart beat consistent, it can break the user’s workout flow by playing unmatched tempo songs(too fast, or too slow) or play genre of songs that they are not into. The users have to manually switch the song whenever this happens. I conducted a survey with over 50 people from both online and in person to confirm my hypothesis. One of the common response from people was that when their training is being paused, they tend to take longer break than they initially planned. It often results in extended workout time and for those who are tight on their schedule have no option but ending their workout as uncompleted. For heavy lifters, many said songs mismatch with their activity level and result in a lack of concentration, ultimately failing to hit desired workout goals. As an alternative, people responded that they build their own playlist, in spite of the time investment.
One solution for this problem is offering users a personalized playlist. Nowadays, it is common for apps to deliver tailored information, for example, websites like Medium ask newly signed up users to select multiple topics to read about in order to deliver articles they’d be interested in. The same goes for the mobile applications. After the sign-up process, the personalization starts through the selection of genres, then artists who users want to listen. The home page displays a variety of music stations created, based on their preferences. created the following wire frame to map out a good user flow.
These mock ups are for explaining the mechanism of the solution in depth. Let's imagine a scenario that users are playing one of the track from the playlist generated by the app. The users will naturally skip the song to the next one if it is not the song they want to hear while working out. they can skip the song by scrolling the bar up. Then the app displays the text asking the user if they want to skip the song. Once the users press "Skip it" button, it will play the next song immediately. All the songs are not skipped by the users will be added to their playlists. In Your Playlist tab, the users can manually edit their playlist to refine their track list. Therefore, it can significantly reduce the overall time to browse through the playlist to find right songs. Also the app plays the most appropriate song based on their heart rate.