Powering a Player-First Culture with Massive Gameplay Data

A Sneak Peek into Data and Electronic Arts

Navid Aghdaie, PhDSr. Director of Data Science & EngineeringSep 2015

About Me

UCLAComputer Science PhD

Distributed/Fault-Tolerant Systems

Comparison Shopping Startup

Ask.comSearch Engine Core

Web/News Search Components

VP Data Systems

Electronic ArtsDigital Platform, Data

Science & Engineering

New Large Scale Data Platform

Unlock Value of EA’s Rich Gameplay Data

Outline

3

• EA and Games Why Data Matters

• Large Scale Data Platform Design and Architecture for Gamer & GamePlay Data

• Data in Action Examples of Data Usage

EA Overview

• Rich history of games, founded 1982Current Strategic Goals:

• Digital Transformation• Player First Culture

• Dozens of games, multiple platforms: console, pc, mobile• Sports: FIFA, Madden, NHL, NBA• DICE: Battlefield, StarWars Battlefront• Bioware: Dragon Age, Mass Effect• Maxis: The Sims Franchise (Sims4), SimCity• Need for Speed, Bejeweled, Plants vs. Zombies, Simpsons Tapped Out, etc…

• 10s M players/day, across the world4

Data Usage at EA (Gameplay Data)

Game Design and Development• Game updates, new features, new games

Live Services• Game operations• Gameplay optimization• Fraud

Marketing• Player acquisition, re-engagement• Cross Promotions• Advertisement

Customer Service• Player Facing Issues with Game

Executive Decisions5

Advert Push NoteEmail Personalizedfeatures

In-game Banner

Acquisition

CE

Customer Experience

Example Player Journey through EA Ecosystem

Digital Platform: Data Science & Engineering

7

Core Tech Principles

Leverage Open-Source• Join the community and ride its progress – requires investment in talent

Embrace the Benefits of the Cloud• Downward price trend• Lowers risk of volume/game success mispredictions• Build and spend only as needed• Avoid vendor lock-in

Build with Scalability, Extensibility, Reliability from the Start• One platform for all EA games• Standards with flexibility to support variations of use

Invest in “Crown Jewel IP” Data Components• Data Science, Algorithms, Data Layer Tools• Smart build vs buy decisions

8

Data Sources

Access & Applications

Storage & Processing

Reporting & BI Tools

Game Analytics

Subscription API

GameServers

Marketing, Ads, …

External Sources

And More…

Access Layer

Player 360

Segmentation Manager

Engagement Manager

ExperimentationApplications

Lightning (Streaming Ingestion & Processing) Tide (Batch Ingestion)

Capture &Ingestion

AccessAPI

Live Viewer

Bug Sentry

River(Capture layer)

Shark(Processing)

Ocean(Hadoop storage)

Pearl (RDBMS)

Black Pearl (RDBMS)

Pond (Hive)

Data Platform Architecture

Surf(Data Science)

PlatformServices

Data Capture & Ingestion

Data Sources

• Client Telemetry (mobile, console, pc)

• Server Telemetry

• EA Internal Services• e.g. online e-comemerce, micro txn, virtual goods purchase/trade, etc

• 1st Party (e.g. sales data from xbox, playstation, android, ios)

• 3rd Party (e.g. acquisition marketing, ads)

• EA web sites traffic

Challenges:• Definition and Enforcement of taxonomy standards• Silos and Duplication

10

Streaming and Lambda Architecture

Tech Stack• Kafka

• distributed pub/sub messaging• Storm

• stream event processing

11

Storage & Processing Engine

Storage: multi-tier approach

• HDFS

• Cloud Storage

• Archive/Backup

Tradeoff: cost vs performance

Processing Engine

• Apache Hadoop Stack: Hive, Oozie

12

Data Access & Applications

• Reporting & Dashboards

• Adhoc Analytics• Hive (HQL)

• RDBMS (SQL)

• APIs, Data Subscription

• Closed-Loop Data Driven Online Applications• Personalization/Targeting Systems• Recommendation Engines

13

Data in Action: Examples

14

Dynamic Player Experience

Real-time recommendation engine

• Modify game configuration to optimize for targeted metrics

• Example:

Maximize retention by manipulating game difficulty according to user state

15

16

Initial Configurations Dramatically Affect Win-RatesLevel: Deep Sea Creature

• Initial seed affects the starting board configuration

• # of orange, green, and purple pegs

• Potential locations of the pegs

• Win ratio ranges from 10-50% depending on the seed

• Effective knob for us to create a better experience

17

Game Client

Recent Gameplay

Historical Profile

Predicted Churn Risk

(0% – 100%)

Mapping to Chosen Difficulty

Recommended Levers to Pull

Targeting Recommendation

Churn Risk

How Dynamic Experience Works

Managing Player Relationships

18

Provide the right value

Data Science

What to show them?

Optimization

How to reach them?

Engagement

Who to target?

Segmentation

A set of tools to curate the player journey through differentiating and improving the

player engagement

EA Games

A self-serve tool which enables granular targeting of EA players.

Segmentation

Manage and deliver targeted messages to players in-game, out of game, across the EA network

Engagement

Identify the best placement to engage, track, and test messages to our players

Optimization

Optimize the Player First experience using Data Science

Data Science

Player Relationship Management – Application Components

• Player Profile

• Segmentation via Indexing of key attributes, leverage Lucene• Examples: demographics, game ownership, play time, etc

• within seconds

• Run-time Decisioning Engine

• Communication Channels• Email, PushNote, in-game msg

• Campaign management

• Recommendations, optimizations

19

Anomaly Detection and Reacting to Issues

20

Thank You!

21

We’re Hiring!Data Scientists & EngineersContact me! Navid Aghdaie naghdaie@ea.com