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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
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
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.
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
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
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
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’
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
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
A P P E N D I X
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
S K E T C H E S / I T E R AT I O N S
General Assembly UX Design Immersive Course - Project 1 - Media Player Assignment
General Assembly UX Design Immersive Course - Project 1 - Media Player Assignment

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General Assembly UX Design Immersive Course - Project 1 - Media Player Assignment

  • 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
  • 6.
  • 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
  • 12.
  • 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