How Can Operators Thrive in the 5G Driven Application Economy?
Economy of free games and technologies for data-driven game design
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Transcript of Economy of free games and technologies for data-driven game design
Economy of free gamesand
technologies for data-driven game design
UNAgames
http://www.unagames.com
December 2013
Daniele Benegiamo Erika Vespa
Economy of free games
Tapsteroids: the game
Tapsteroids is a throwback to retro games which picks up on the asteroid genera with a new fresh and different asteroid shooter.
It puts players in charge of protecting spaceships from asteroids.
This is done by launching missiles from the space station at the center of the screen to destroy waves of asteroids tapping on them.
Tapsteroids: paid version
Free promotion days
September 5, 2011: 17,000 downloads
August 10, 2012: 4,000 downloads
Monetization models for free games
Freemium Free-to-play Ad-supported
Tapsteroids v1.2
Tapsteroids v1.2
Tapsteroids v1.2
Tapsteroids: free version
Advertising networks
Advertising networks
Projections
26,500 active users $270 ads revenue
↓$0.0102 ARPU
Average Revenue Per User
1,000,000 MAU
to earn $10,000/m
Technologies for Data-Driven Game Design
Data Driven Game Design
Design
Analyze
DevelopData
Metrics
● Problem:– UX / Engagement / Flow are not
quantitative traits
– Unknown “cause-effect” dynamics
● Solution:– Measure events with quantitative traits
affecting the dynamics of the system
– Key Performance Indicator (KPI)(DAU, MAU, WAU, Stickiness, Retention, Churn, Duration,ARPU, DARPU, ARPPU, k-Factor, Lifetime, LTV, LNV, …)
“Hosted” systems
● Flurry (free)
● Apsalar (free)
● Localytics (free community edition, open source client)
● Countly (hosted, open source client & server)
● Google Mobile App Analytics (free)
● Kontagent
Analytics System
● “What is it?”– Data logger (Client/Server)
– Data analyzer
Data Logger
● Client– Lightweight
– Fault tolerant
● Server– Stateless
– Secure
● Database– Write-
bounded
– Distributed store
Client
● Runtime performances● Multi-threading● Data caching● Compressed chunks (gzip vs bandwidth vs HTTPS)
● Distributed “session id” (UUID, stateless server)
Server
● PHP– Problem: database connection pooling
– Solution: application server (Java servlet, …)
● Tolerant to duplicated data
Database
● PostgreSQL● Key / Value store
– hstore (NoSQL)
● Horizontal scaling– Load balancing
Data analyzer
● Data store– Read-bound
● Numerical analysis– CPU-bound
– Memory-bound
– “Knowledge”-bound
Data store
● Re-arrange data into suitable formats:– Reduce loading times
– Reduce memory consumption
– Optimize data for used access patterns
– In R: saveRDS(), readRDS()
Database
Data store
Data store
Data store
Numerical analysis
● Mostly statistical analysis● R (or Scilab, Octave, Matlab, …)
R tips
● Package “bigmemory” (allows analysis of datasets larger than available RAM)
● Package “data.table” (faster operations on large data.frame)
● Package “parallel” (explicit parallelism for multi-core CPUs)
● Vectorization, vectorization, vectorization!● http://cran.r-project.org/web/views/HighPerformanceComputing.html
Problems
● Big Data● Scalability of numerical algorithms
– In the future (maybe): Hadoop, Mahout, …
– Currently: Amazon WS (large instances: 64-bits, 32 v-cores, 244 GB RAM)
● Most useful analysis are game-dependent– You need the right data
– You have to spot the rightformulas
Thanks!
Daniele [email protected]@UNA_daniele
UNAgames
http://www.unagames.com
Erika [email protected]@UNA_erika