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 Benegiamodaniele@unagames.com@UNA_daniele

UNAgames

http://www.unagames.com

Erika Vespaerika@unagames.com@UNA_erika