gsummit sf 2014 - recognizing behavior with big data + gamification by ross smith @42projects
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TRANSCRIPT
+
Gamification and Big Data
Ross SmithMicrosoft
Using Game Mechanics to Improve Data Science
+ about me
+cultural change
+our world is changing
new workforce
global demographics
technology revolution
social connectivity
‘user’ experience
is key
+IM
AG
INE
1964
San Francisco event
The Beatles arrive in the US San Francisco - Cow Palace – 19 Aug 1964
+7.2 billion humans1804 – 1 billion1927 – 2 billion1960 – 3 billion
2025 – 8 billion2050 – 9.6 billion2081 – 10 billion
Population growth rate is slowing !
+ the internet
87% of American adults now use the
internet
99% of households earning $75,000 or
more
97% of young adults
97% with college degrees
68% of adults connect via mobile
+ internet of things
+ mobile video
> 50% of all global growth by 2025 will come fromBRIC countries plus South Korea and Indonesia
Global Shift: Arrival of Emerging Economies
+ China
1.6 gamers in China for every American
citizen
517 million
28% play more than 1 hour a day
In a global village of 100 61 would be Asian, ~80 would have
mobile,11 would be from Europe…
and 70 would be gamers…
Global Shift: Diverse and Distributed Workforces
+ why is big data so hyped?
“big data” was added to Merriam-Webster in 2014 edition…
an accumulation of data that is too large and complex for processing by traditional database management tools
+ “bigdataUX” – user research
+ game design
+ testing
A B
+ marketing
+ productivity gamesusing games to get the data you need
+where games work best
Skills-Behaviors
Matrix
Core Work Skills
Unique Work Skills
Expanding Work Skills
In-Role Behaviors
Organizational Citizenship Behaviors
+Lync Test Games
Build a Story
Landmarks
Road Signs
Mobile Fest
+lan
gu
ag
e q
uality
gam
e
+Results
Significant Quality Improvements for Windows 7
Positive Impact on Ship Schedule
Team Morale and Subsidiary Engagement
Total Screens Reviewed: Over 500,000
Total Number of Reviewers:
Over 4,500
Screens per Reviewer: Average 119
Significant Quality Improvements for product
Positive Impact on Ship Schedule
Team Morale and Dogfood User Engagement
Players Over 1,000
Feedback increase > 16x
Feedback received: 10,000+
Players vs. non-players 67% of players participate vs. 3% of non
Results
+ data scienceusing games to get the data you need
+
‘given enough eyeballs, all bugs are shallow’
Eric Raymond, The Cathedral and the Bazaar
+Gamified Transactions
Data Authenticity
Pre
cisi
on
Hig
hLo
w
HighLow
GamifiedTransactions
SyntheticTransactions
“Authentic”Transactions
A/B Tests
+
passive monitoring
and
inferential analytics
Visitors Randomly Distributed
50
%
Version B is better than Version A
Version A(Control)
1.2% of users with a Page View clicked on Signup
2.8% of users with a Page View clicked on Signup
Version B(Treatment)
50
%
Is the observed difference statistically
significant?
YE
S
User interactions instrumented, analyzed and compared
Page Title
Signup Here
Title of Page
Signup Here
authentic transactions
+synthetic transactions - examples
test in production methods
outage detection
call quality
slow performance
video frame rate
+ gamified transactions (GT’s)
use game mechanics to direct crowd activity
carefully designed not to impact service load
cluster analysis for user groups and scenario determination
generate A/B comparative studies
predictive analytics
beware of the observer effect
+ types of elicited information what can we use GT’s for?
+ usage studies
games that get users to try new features
teach best practice of product use
measure before and after usage patterns to determine stickiness of feature
can impact the long-term product use
+ scenario coverage studies
direct crowd to use features that require more testing
use early adopters willing to accept lower quality to prepare for late majority that require high quality
requires knowing the impact to the user population
measure the observer effect – are gamers acting differently?
+crowd reputation scoring
the value of
gamified transactions
hinges on our ability to trust user’s
feedback
Good
Fair
Needs work
Poor
Reputation Scores
+ data science and feedback quality especially important when rewards are used
use the crowd to test each others results!
develop a probability function for each gamer indicating the chance of a correct item of input
reputation score is the Bayesian prior for correctness calculation
reputation is categorized using percentile
provide games that train to improve reputation
+ the opportunity GT’s bring to cloud
gamified monitoring experience tuning and
optimization scenario feedback performance marketing data crowdsourced testing
+
marriage of gamification andbig data
is the future
+42Projects
Collaborative Play Trust Management
Innovation
www.42projects.org
