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Game Optimization through Large-Scale Experimentation Game Optimization through Large-Scale Experimentation

Game Optimization through Large-Scale Experimentation - PowerPoint Presentation

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Uploaded On 2016-04-02

Game Optimization through Large-Scale Experimentation - PPT Presentation

Erik Andersen PhD student Center for Game Science University of Washington Computer Science Dept Music Gameplay Sound effects Art engagement retention revenue AB Testing AB Testing ID: 273032

animations players time 100 players animations 100 time coins refraction foldit result worlds objectives tutorials secondary lee levels experiment

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Slide1

Game Optimization through Large-Scale Experimentation

Erik Andersen

Ph.D. student

Center for Game Science

University of Washington Computer Science Dept.Slide2

Music

Gameplay

Sound effects

ArtSlide3

engagement

retentionrevenue

?Slide4

A/B TestingSlide5

A/B Testing

A

BSlide6

Metrics

Levels completed Time played

Return rateSlide7

Aesthetics

Secondary Objectives

TutorialsSlide8

Foldit

Refraction

Hello WorldsSlide9

RefractionSlide10

Rating: 3.8 / 5

400,000 playsSlide11

Hello Worlds!Slide12

Rating: 4.2 / 5

1,385,000 playsSlide13

FolditSlide14

240,000 playersSlide15

Player Tracking

Flash cache / login nameNew players onlySlide16

Statistical significance

95% confidence level (p<0.05)Slide17

Experiment #1: Audio

Sound Effects

MusicSlide18

Result:

Music and sound effects did not

matterSlide19

Experiment #2: AnimationsSlide20

Result:

Animations improved engagementSlide21

No Animations

RefractionSlide22

No Animations

RefractionSlide23

No Animations

RefractionSlide24

No Animations

Hello WorldsSlide25

No Animations

Hello WorldsSlide26

Experiment #3: Secondary Objectives

(Super Mario Bros., Nintendo 1985)Slide27
Slide28
Slide29

Levels

% of

players

100

0Slide30

Levels

% of

players

100

0

With Coins

HypothesisSlide31

Levels

% of

players

100

0

With Coins

RealitySlide32
Slide33
Slide34

Time

% of

players

100

0

What about time played?Slide35

Time

% of

players

100

0

With Coins

HypothesisSlide36

Time

% of

players

100

0

Hypothesis

With CoinsSlide37

Time

% of

players

100

0

With Coins

Reality: Many Players Quit SoonerSlide38

Time

% of

players

100

0Slide39
Slide40
Slide41

Result:

secondary objectives harmed

engagementSlide42

(Assassin’s Creed,

Ubisoft

2007)Slide43

Maybe easier is better?

(Super Mario Bros., Nintendo 1985)Slide44
Slide45
Slide46
Slide47
Slide48

Time

% of

players

100

0

Off-path CoinsSlide49

Time

% of

players

100

0

On-path CoinsSlide50
Slide51
Slide52

Result:

secondary objectives were good if they supported the primary objectivesSlide53

Experiment #4: TutorialsSlide54

No Animations

FolditSlide55

No Animations

FolditSlide56

Refraction and Hello Worlds:

no effectSlide57

Result:

text tutorials helped

only in the most complex gameSlide58

Number of concepts

11

13

24Slide59

Context-sensitivity

Context-sensitive

Context-insensitiveSlide60

Result:

context-sensitive help was better

(if tutorials helped at all)Slide61

No Animations

FolditSlide62

No Animations

FolditSlide63

Let’s gather more data

Let us A/B test your games!Slide64

Coauthors

Yun-En Liu

Richard SniderRoy SzetoSeth CooperEleanor O’Rourke

Jeff LowdermilkDavid TruongZoran

PopovićSlide65

Acknowledgements

Kongregate: August

Brown and Anthony PecorellaLogging:

Kefan XuRefraction Team: Erik Andersen, Yun-En Liu, Marianne Lee, Eric Butler, Brian

Britigan, Stephen Sievers, Roy Szeto, Mai Dang, Christian

Lee, Ethan Apter, Emma Lynch, Happy Dong, Zorah Lea Fung, Justin Irwen, Seth Cooper, François Boucher-

Genesse, Zoran PopovićHello Worlds Team

: Rich Snider, Michael Eng, Marianne Lee, Blake Thompson, Jeff Flatten

Foldit Team: Seth Cooper, Adrien Treuille, Firas

Khatib

, Janos

Barbaros

, Joshua Snyder, Alex Cho Snyder, Jeff Flatten, Jeff

Lowdermilk

, Dun-Yu Hsiao,

Jeehyung

Lee, David

Salesin

, David Baker,

Zoran

PopovićSlide66

e

land@cs.washington.edu