The document discusses challenges with music playlist management, focusing on user interviews revealing the difficulty of finding music that resonates emotionally and the inefficiencies of current platforms. The proposed solution is an app that uses predictive data collection and machine learning to refine music recommendations based on user behavior and emotions. Additionally, the document outlines design strategies for user engagement and feedback for continuous improvement of the app's interface.

1. M O S T A W E S O M E S T P L AY L I S T E V E R
K A Z U M I T E R A D A
M A R C H 2 5 , 2 0 1 6
G E N E R A L A S S E M B LY U X D I C O U R S E W E E K 1 - P R O J E C T 1 - M E D I A P L A Y E R A S S I G N M E N T

2. M E D I A P L AY E R H Y P O T H E S I S
• Playlists are scattered and hard to manage/combine.
• Good music is subjective and hard to find.
• Music is intensely personal and emotional

3. U S E R I N T E R V I E W S - P R O B L E M S TAT E M E N T S
Tech Savvy Influencers: M, 20-30’s
SPOTIFY for albums, SOUNDCLOUD for tracks and discovery, YOUTUBE
MUSIC and HYPEMACHINE for recommendations.
- I cannot find the right music to match my emotions
- I curate my own playlist, but spend too much time
backing up depending on device size, and cleaning
up the track names.
- My tastes or moods do not always match with
genres or categories based on what’s most popular.
- I tried an open source universal playlist aggregator
but it didn't work well.

4. Torrent Hacker: M, 40’s
Uses VLS and MX player for TORRENTED music and TV shows.
- I torrent top 50 most popular songs only because I
am new to town and don't have time for discovery
or friends to recommend me stuff.
- I'm learning English, by listening to Audible
bestseller books and American TV shows I torrented.
- I also listen to music from my home country, not
featured in any American music apps.
U S E R I N T E R V I E W S - P R O B L E M S TAT E M E N T S

5. Electronic Vinyl Musician: M, 50’s
DOES NOT USE any digital media player. Makes electronic music and puts
them out on vinyl. Buys VINTAGE SYNTHESIZERS and VINYL.
- I only buy vinyl and put my music out on vinyl
only, but if I really like the song, I download the
MP3 as to not scratch the record.
- I discover music through the 20 year olds I hang
out with, but most of the time, I don't like any of
the stuff they make me listen.
- I am too busy making music and I don't have time
to go discover new music on my own.
U S E R I N T E R V I E W S - P R O B L E M S TAT E M E N T S

7. NAILED IT.
TA P O N C E O N T H E A P P A N D G E T T H E P E R F E C T S O N G

8. D E S I G N S T R AT E G Y
L I F E - T R A C K I N G P L AY L I S T
PREDICTIVE DATA COLLECTION & AGGREGATION
USING HISTORY, SENSORS, IMAGE RECOGNITION & MACHINE LEARNING
AGGREGATED DATA IS SEAMLESSLY AND INVISIBLY COMPILED AND DELIVERED
SETUP FLOW: Aggregates scanned artifacts, playlists, likes, follows, re-blogs, frequency and location of play, friends, relationship status
DAILY USAGE FLOW: App continues to collect data points (“Music triggers and contexts”) seamlessly in users’ daily life for continuous improvement of
the recommendation algorithm
ADAPTIVE INTERFACE & ALGORITHM
CONTROL DISCOVERY VARIATION, ACTIVE vs PASSIVE LISTENING
BASED ON MOOD, SITUATION, USER BEHAVIOR AND STATS, CHANGES THE INTERFACE & RECOS
Daily questions like “what are you up to” and “how do you feel” will be eliminated as soon as location and activity are consistently machine
recognizable and sensors can pick up brainwaves of emotions and ‘music in the head’

9. P R O T O T Y P I N G S I G N U P F L O W
D A I LY U S E F L O W
U S E R F E E D B A C K ( 3 r a n d o m u s e r s )
- W h a t d o y o u m e a n b y “ s c a n s t u ff ” ?
- S e p a r a t e d i s c o v e r y f ro m l a i d b a c k
- Wa n t a l o n g e r p l a y l i s t

10. D E S I G N
F I N A L
h t t p s : / / p o p a p p . i n / w / p ro j e c t s /
5 6 f 4 4 f b 5 b c a 0 6 7 c a 0 e 7 2 d 6 4 7 / p re v i e w /
5 6 f 4 4 f b 5 b c a 0 6 7 c a 0 e 7 2 d 6 4 a

11. A P P E N D I X

13. I N I T I A L D E S I G N F E E D B A C K
S I G N U P F L O W
D A I LY U S E F L O W
U S E R F E E D B A C K ( C h r i s , P a u l o , M a s h a )
- W h a t d o y o u m e a n b y “ s c a n s t u ff ” ?
- S e p a r a t e d i s c o v e r y f ro m l a i d b a c k l i s t e n i n g
- Wa n t a l o n g e r p l a y l i s t

14. S K E T C H E S / I T E R AT I O N S