Are you trying to keep your game fresh for long-time players but don't have the resources to keep building new handcrafted content? Join this session to learn how to launch dynamic content for groups of players without relying on static techniques like instancing or spawn points. We dive into Amazon Kinesis and Amazon Kinesis Data Analytics for real-time data collection and hotspot detection, and machine learning for encounter-building based on observed player behavior.

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How Rovio Uses ML to Acquire,
Retain, and Monetize Users
Vesa Siivola
Senior Data Engineer
Rovio
G A M 3 0 4

3. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Rovio © 2018
2003
FOUNDED IN
CREATOR OF
BUSINESS UNITS
GAMES
3 STUDIOS
BRAND
LICENSING
< 400ROVIANS
ESPOO, STOCKHOLM, LONDON,
SHANGHAI, LA
PEOPLE
4BSINCE 2009
DOWNLOADS
$350M
BOX OFFICE SEQUEL
SEPTEMBER 2019
Rovio in an eggshell

4. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Agenda
Live Operations
Data at Rovio
Predicting
churning
spending
app install propensity
Customizing user experience, technology overview

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Live operations
Run and tweak
events
player support
user acquisition
over the game lifecycle

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Rovio © 2018
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1010111101001010101010101010101
001110010100010010100101010100
100101100100101010101010101001
0100101011010111001010100011010
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Single truth Sharing is caring We own our future
???
Our data philosophy

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Beacon
Platform for game teams
client SDK
game services
charts and reports
customization
A/B testing
…

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Overview of analytics data flow
Lake of wisdom
Real-time
Flink streams
Amazon
EMR
Orc format
with schemas
Amazon
S3
Amazon
EC2
Amazon
EMR
Secor, Spark,
Hive
Player profiles, KPIs
Advanced analytics, ML
Amazon
Redshift
Amazon
Athena
Amazon
EMR
Amazon
EC2
Amazon
Athena
Amazon
EMR
Dashboards, App personalization
Event
gateway Kafka
mobile client
Services
Amazon
EC2
Amazon
EC2
Amazon
EC2
Services
Amazon
EC2
Services
Amazon
EC2
HenriHeiskanen:Building a Lakeof Wisdom
https://www.youtube.com/watch?v=pmfIi-adXcM&t=595s

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time spent last month 123 hours
country FI
distinct days played 11
device type iPhone X
money spent $34
first event date 2018-10-01
…
Player profiles
Basis for most of the player based modeling
Simple demographics, aggregates and events:
Amazon
DynamoDB
Amazon
EC2
Amazon
Redshift
Amazon
S3

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Player churn
Definition: Is a player going to stop playing the game?
If we can predict that, can we do something about it?
First end-to-end ML solution over the whole game portfolio for us

11. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Rovio © 2018Rovio © 2017 Confidential
MIN 2 WEEKS
TRAINING
2 WEEKS
HOLD OUT
2 WEEKS
OBSERVATIONS
Extract features
Reserved - act to change the player
behavior
Any game sessions?
Time windows for churn prediction

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Rovio © 2018Rovio © 2017 Confidential
fit(train_set) MODEL
Churn ML overview
MIN 2 WEEKS
TRAINING
2 WEEKS
HOLD OUT
2 WEEKS
OBSERVATIONSMIN 2 WEEKS
TRAINING
2 WEEKS
HOLD OUT
2 WEEKS
OBSERVATIONSMIN 2 WEEKS
TRAINING
2 WEEKS
HOLD OUT
2 WEEKS
OBSERVATIONSMIN 2 WEEKS
TRAINING
2 WEEKS
HOLD OUT
2 WEEKS
OBSERVATIONS
predict(current_profile) MIN 2 WEEKS
FEATURES
future 0.8MIN 2 WEEKS
FEATURES
future future

13. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Churn prediction set up
Template agile ML project
continuous integration
end-to-end
simple data flow
automated accuracy monitoring
Gradient Boosted Trees:
simple, fast modeling
easy to handle categorial features
importance of each feature for crude analysis

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Churn prediction data flow
Each game has its own model
Model trained weekly, scores re-estimated daily
Lake of wisdom
Amazon
S3
Amazon
EMR
Amazon
EMR
Amazon
EC2
Amazon
Athena
Model accuracy dashboard
Amazon
EC2 Amazon
EC2

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Show one forced
interstitial and only
show xpromo
reward videos for
churning players
xpromo = adsof other Roviogames

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Rovio © 2018Rovio © 2017 Confidential
27% more xpromo users
0% retention impact

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Churn prediction: Pros and cons
no game specific features
+ works for any game
but are we taking a hit on accuracy?
set up to model more dedicated players - requires some history data
+ simple data flow
- no churn prediction for first 2 weeks of game play
churn score and player support

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Predicting player spending
Can we find players that are likely to do in-app purchases for our games?
Should we adjust the game experience even before they start spending?

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Predicting player spending with neural networks

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Simplified spender prediction data flow
Amazon
EC2
Internet
Lake of wisdom
Amazon
S3
Amazon
EMR
Amazon
EMR

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Impact of player spend score
No improvement in user acquisition with look-alike audiences
Exploring customizing in-game user experience

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Spender lifetime value prediction (ongoing)
Prediction based on 7 first days of player profile
Random forests to predict
is the player going to be a spender ?
how much he is going to spend ?
Early evaluation of our ads campaigns / ads partners outside of our own
games
Improving ads shown in our own games

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Predicting game install propensity
Is the player going to install the game we show an ad for?
If there is a very low chance, maybe we should show something else.

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Rovio © 2018Rovio © 2017 Confidential
fit(train_set1,
target_game1)
Model
target game 1
Install propensity training
fit(train_set2,
target_game2)
fit(train_set3,
target_game3)
Model
target game 2
Model
target game 3

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Features: player_profile, source_game, ad_zone
Train target: Game install event exists
Algorithm: Random forest classifier / Spark MLlib
Fitting weekly, scoring daily
Game install propensity model setup
source game
time spent
time zone

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Model type comparison
Random forests
accurate
easy to train and integrate
Logistic regression
more work with categorial features, discretization of continuous values
DNN with client events time series
computationally expensive (both ETL and training)
hard to integrate to the platform
the most accurate

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App install propensity in production
Amazon
DynamoDB
Amazon
RDS
Amazon
RDS
Internet
mobile client
Amazon
EC2
Amazon
CloudFront

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Funnel conversion rates

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Live ops tools, customization

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Customizing user experience
mobile client
Amazon
EC2
Amazon
EC2
Amazon
RDS
Amazon
EC2
Amazon
RDS
Amazon
EC2 Amazon
EC2
Amazon
CloudFront

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Amazon
EC2
Push notification service
Amazon
Athena
Amazon
EC2
Amazon
EC2
Amazon
EC2
Amazon
EC2
Amazon
EC2
Internet
mobile client
Lake of wisdom
Amazon
S3
Amazon
EMR

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Thoughts on customizing user experience
Built on fairly low level AWS services
Real-time model evaluation?

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Thoughts on ML – Taking a step back
Agile ML projects?
Start with simple models
Continuous Integration with daily automated metrics
Business value vs. modeling accuracy vs. running costs
SageMaker?

34. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Thoughts on ML – What else can we try?
Now: ML for ads / user acquisition
Next: Game development oriented ML
Verifying level designs
Game QA
Content creation (levels/graphics/characters)
Automated A/B tests

35. Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
vesa.siivola@rovio.com

36. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.