can one lens see bi and ux developconf

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Page 1: Can one lens see bi and ux   developconf
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CAN ONE LENS SEE BI AND UX?

Heather StarkKinran

@HAStark

[email protected]://slideshare.net/heather.stark

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http://kaleidoscope.kontagent.com/wp-content/uploads/2012/06/Kontagent-kScope-Top-Growth-in-Revenue-2011-20121.png

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Design = Change

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Design = Change

Analytics powers change

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Analytics is a process

not a product

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not an afterthought

Analytics is a process

not a product

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Roger Dickey, Creator of Zynga’s Mafia Wars

“Putting stats in pre-launch is absolutely the best thing you can do for your product”

http://blog.betable.com/roger-dickeys-hacks-for-game-monetization/

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not an afterthought

Analytics is a process

not a product

Analytics is a discovery processAnalytics is a design process

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Think

Look

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Think

Look

Change

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Think

Look

Change

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Think

Look

ChangePlanned

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There is only one outcome

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There is only one outcome

LTCV

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No KPI is good but thinking makes it so

RetentionEngage-ment

Virality

Monetis-ation

LTCVCAC

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Virality and valueDiffusion dynamics of games on online social networks, Wei, Yang, Adamic, de Araújo and Rehkihttp://www-personal.umich.edu/~ladamic/papers/FBgames/FBgameDiffusion.pdf

Recruited by friend

Other

Play after day 1?

No Yes

10% of inviters responsible for 50%of successful invitations

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Engagement, retention, and value

Which pattern is best?

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Almost none

Monetisation and valueAlmost all

A few

Nothing A bit A lot

How manypeople

A whole lot

Even fewer

Pay how much?

Individualdifferences• interpretable or• stochastic

Experiencedifferences

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Time and value

http://www.gamasutra.com/blogs/NickLim/20120626/173051/Freemium_games_are_not_normal.php

Data: Sonamine, aggregatated over >12 casual games

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clickclickclick click click

clickclick

click

clickclick

clickclick

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Context is complexSequential

goal

loss

risk

loss

choice

reward

actionor

event

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Context is complex

Concurrent

Sequentialgoal

loss

risk

loss

choice

reward

Factual

unease momentum suspenseresource level friend presentaction

or

event

Imputed

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Who what how where when

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Context is complex

Concurrent

Sequential

Imputed

goal

loss

risk

loss

choice

reward

Factual

unease momentum suspenseresource level friend presentaction

or

event

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Analytics

Experiencetypes

KPI

LTCV

Events

ActionsPlayertypes

reveals these relationshipsby pulling focus

Context

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TOOLS AND PROCESSESTrends and lenses

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Tools

Logging Reporting Exploratory Model-testing

App tracking

BI frontend

Data science

Activities

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Which is bigger?

12 16

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It depends

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Tools trends

Logging Reporting Exploratory Model-testing

App tracking

BI frontend

Data science

graph dbpredictives

Activities

cloudservices

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Predictives: segmentation

e.g. Player Lifecycle Management ™ConvertSoon™ChurnSoon™PurchaseMoreSoon™InfluenceSoon™source: Sonamine

e.g. graph-based

there are many techniques for identifying groups

new ones are emerging

expected future behaviour is a strong focus

esp. behaviours which link to KPIs

what you do with the groups is a different question...

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Segmentation can suggest action

Revenue Potential

Vira

lity

Pote

ntial

31%0.89%22%

$1.75

%Volume%Paying7Day Ret

CAC25%

1.30%26%

$2.21

5%0.199%

$2.38

14%0.9721%

$1.94

Early Enthusiasts

Confident Completers

Social Involver

Sporadic SemiEngaged

Losing Momentum

Need Guidance

Borderline Incompetent

6%2.34%57%

$4.40

12%0.8659%

$3.57

7%0.55%36%

$0.75

Source: Games Analytics

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It can also be opaque

“We have tested over 60 individual and game-specific metrics. None of them are critical enough to cause churn. None of them! We haven't found a silver bullet -- that magic barrier preventing players from enjoying the game.”

Dmitry Nozhnin, Head of analytics and monetisation, Innova:

http://gamasutra.com/view/feature/170472/predicting_churn_datamining_your_.php

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?

?

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Do tools matter?

http://www.legoturingmachine.org/

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PROCESSESTrends in

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Which is better?

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Sometimes people do 1-2 A/B tests per week and then complain that it doesn’t work for them – they probably need to 5-10X their A/B test output in order to get a win or two per week. Andrew Chen, 2 July 2012

http://andrewchen.co/2012/07/02/what-does-a-growth-team-work-on-day-to-day

Most fail.

We do hundreds and

hundred of experiments

every quarter.

Ken Rudin, General Manager, Analytics, Zyngahttp://tdwi.org/videos/2010/08/actionable-analytics-at-zynga-leveraging-big-data-to-make-online-games-more-fun-and-social.aspx

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Quant variation rules

‘you need to invite 3 friends to get to the next level on Bubble Witch

Saga….’

Alex Dale, CMO King.comFacebook Mobile HackLondon March 2012

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Quant variation rules

‘you need to invite 3 friends to get to the next level on Bubble Witch

Saga….’

Alex Dale, CMO King.comFacebook Mobile HackLondon March 2012

not 2, not 4

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Answers don’t always make senseWe don’t understand what’s going on. All we know is we’re going to keep running these experiments to try and understand better what it is that our customers are telling us. And there are clearly things that we don’t understand because a simple analysis of these statistics implies very contradictory yet reproducible results. So clearly there are things that we don’t understand, and we’re trying to develop theories for them. It’s just an exciting time but also a very troubling time.

Gabe Newell, Founder, ValveOct 23 2011http://www.geekwire.com/2011/experiments-video-game-economics-valves-gabe-newell/

June

23

2012

Val

ue h

ires

Gre

ek

econ

omist

in re

side

nce

to lo

ok a

t sh

ared

cur

renc

y is

sues

.

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What’s the question?

http://www.youtube.com/watch?v=rt-zIMaMD24

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Inclusive vs extractiveWhirly Fizzle Shape:Height: 74Breast Size: 69Breast Buoyancy: 8Breast Cleavage: 32Hip Width: 73Hip Length: 44Butt size: 50Belly Bounce: 5, 87, 30, 67Breast Bounce: 19, 33, 45, 64Breast Cleavage: 5, 28, 41, 53Breast Sway: 8, 15, 17, 36Butt Bounce: 7, 41, 12, 72Butt Sway: 8, 34, 15, 50Advanced: 12, 39, 9, 14, 6, 10, 10, 22, 61

http://wiki.phoenixviewer.com/doku.php?id=phoenix_avatar_physics

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Discovery-driven design

Design-driven analytics

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