Online Games Analytics - Data Science for Fun

1Dataiku04/10/2023

04/10/2023 2Dataiku

Collocation

Big Apple

Big Mama

Big Data

Games AnalyticsCurrent Life:CEO, Dataiku

Tweet about this@dataiku@capital_games

Past Life: CriteoIsCool EntertainmentExalead

Hello, My Name is Florian Douetteau

Available on:http://www.slideshare.net/Dataiku

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The Stakes - Summary

Million Events Billion $

Billion Events Million $

Classic Business

Social Gaming

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Meet Hal Alowne

Dataiku

Big Guys• 100M$+ Revenue• 10M+ games • 10+ Data Scientist

Hal AlowneBI ManagerDim’s Private Showroom

Hey Hal ! We need a big data platform

like the big guys.Let’s just do as they do!

‟”European Online Game Leader

• 10M$ Revenue• 1 Million monthly games • 1 Data Analyst (Hal Himself)

Wave PoxCEO & Founder W’ave G’ ames

Big DataCopy Cat Project

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MERIT = TIME + ROI

Targeted NewsletterFor New Comers

Facebook Campaign Optimization

Adapted Product/ Promotions

TIME : 6 MONTHS ROI : APPS

Build a lab in 6 months (rather than 18 months)

Find the right people

(6 months?)

Choose the technology(6 months?)

Make it work (6 months?)

Build the lab (6 months)

Deploy apps that actually deliver value

2013 2014

2013

• Train People• Reuse working patterns

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Our Goal

It’s utterly complex and unreasonable

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Our Goal

It’s utterly complex and unreasonable

Our Goal:

Change his perspective on data science projects

(sorry, we couldn’tfind a picture of Hal Smiling)

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Do the Basics

Understand Analytics

What to expect out of analytics

Quick Agenda

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Don’t skip the first steps

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Do you track ? ◦ Customer Goals For

most important features

◦ Time Spent Level Progresison Money Spent

◦ Campaigns and generated campaign Value

Suggestion #1Check The Basics

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Do A/B Tests ◦ Use Proven Solutions

◦ Start small (button size and color)

◦ Check Impacts

◦ Treat new and existing users differently

◦ Don’t give up after the first A/B Test

Suggestion #2DO A/B Tests (and not yourself)

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Register Now / Give Email Graphics:From 25% to 2X More Clickshttp://bit.ly/VOruXt

Changing button from green to red: Up to 21%http://bit.ly/qFEBdK

Some ResultsA/B Tests

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Statistical Signifiance

http://visualwebsiteoptimizer.com/ab-split-significance-calculator/

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Can be Built on top of your production systems

Do you have◦ Cohorts◦ Daily $$ Reports◦ Basic $$ Segments

Suggestion #3Have the Basic BI

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Defined Customer Segments◦ New Installs◦ Engaged Users◦ Engaged Paying Users◦ …?

Defined Customer Sources◦ Social Ads / Social Posts / .. Top Charts / … ◦ Country Segments

Do you have for each segment, evey day ◦ Rolling last 30 days ARPUU ?◦ Rolling last 30 days DAY ?

Do you follow every week◦ The Segment Conversion Rate per source

?

Sample Check list(Gaming)

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Embodiment of Knowledge

Find your core business avantage

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Product Success driven by Quality

Margin / Customer Value / Traffic / Acquisition

At the Beginning

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Margin for new customers might decline …

Margin for new

features might decline …

Is your business really scalable ?

But when you continue growing

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Existing Customers

Existing Product Assets

Existing Specific Business Model

And your KNOWLEDGE of it

Where is your core business advantage ?

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Data Driven BusinessWhat your value ?

Number of Customers

Customer Knowledge

Increase over time with:- Time spend in your app- User relationship (network effet)- Partner / Other Apps Interactions

Your Value

1,409,540$1,03

$2,57$4,08

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To Apply It ?

Product Optimization

Customer Acquisition Optimization

Recommender/Targeting for newsletters

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Dark Side◦ Technology

Bright Side ◦ Business

Apply It !!

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The Dark Side

Technology

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Technology is complex

HadoopCeph

Sphere

Cassandra

Spark

Scikit-Learn

MahoutWEKA

MLBase

RapidMiner

PandaD3Crossfilter

InfiniDBLucidDB

Impala

Elastic Search

SOLR

MongoDBRiak

Membase

Pig HiveCascadingTalend

Machine Learning Mystery Land

Scalability CentralNoSQL-Slavia

SQL Colunnar Republic

Vizualization County Data Clean Wasteland

Statistician Old House

R

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Machine learning is complex

Find People that understand machine learning and all this stuff

Try to understand myself

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Plumbing is not complex(but difficult)

Implicit User Data(Views, Searches…)

Content Data(Title, Categories, Price, …)

Explicit User Data(Click, Buy, …)

User Information(Location, Graph…)

500TB

50TB

1TB

200GB

Transformation Matrix

Transformation Predictor

Per User Stats

Per Content Stats

User Similarity

Rank Predictor

Content Similarity

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The Bright Side

Technology

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People Microsoft Excel

How did you build your great product ?

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Data Team Data Tools

How will you continue growing your great product(s) ?

The Business Guywho knows maths

The Crazy Analyst that reveals patterns

The Coding Guy That is enthusiastic

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data lab, (n. m): a small group with all the expertise, including business minded people, machine learning knowledge and the right technology

A proven organization used by successful data-driven companies over the past few years (eBay, LinkedIn, Walmart…)

TEAM + TOOLS= LAB

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Short Term Focus Long Term Drive

Business People Optimize Margin, …. Create new business revenue streams

Marketing People Optimize click ratio Brand awareness and impact

IT People Make IT work Clean and efficient Architecture

Data People Get Stats Right, make predictions

Create Data Driven Features

It’s just a new team

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Data !

Product Designe

r

Business &

Marketing

Engineers

User Voice

Data Innovation: fill the gap!

Targeted campaingsPrice optimization

A common ground to federate your product

teams towards a common goal

Personalized experience

Quality AssuranceWorkload and yield

management

User Feedback (A/B Test)Continuous improvement

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You can’t « design » insights, you explore and discover them…

Iterate quickly with constant feedback

Try a lot, don’t be afraid to fail!

Freebut not as “free beer”

Function

Form

Experience

Emotion

Surprise

Culture

Explore and

Refine

Experiment

Generate Ideas

Select & Develop

Enhance or

Discard

Gather Feedbac

k

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Prepare for some Geeky Porn

Architecture Patterns

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Classic Columnar Architecture

Some data Some Place To Pour It In

Some Tool To To Some Maths And Graphs

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Classic Columnar Architecture

Lots of data Some Place To Pour It In

Some Tool To To Some Maths And GraphsWeb Tracking Logs

Raw Server Logs

Order / Product / Customer

Facebook Info

Open Data (Weather, Currency …)

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The Corinthian Architecture

Lots of dataSome Place To Perform Rapid Calculations

Some Tools To Do Some Maths And Charts

Some Place To Pour It In And Clean / Prepare It

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Lots of dataSome Place To Perform Rapid Calculations

Some Tools To Do Some Maths And Charts


Statistics

Cohorts

Regressions

Bar Charts For Marketing

Nice Infography for you Company Board

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Lots of dataSome Database To Perform Rapid Calculations

Some Tools To Do Some Maths Some Other To Do Some Charts


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The One Database won’t make it all problem

Lots of dataSome Database To Perform Rapid Calculations



JOIN / Aggregate

Rapid Goup By Computations

Direct Access to the computed Results to production etc..

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The Roman Social Forum

Lots of dataSome Database To Perform Rapid CalculationsAnd some databasefor graphs



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The Key Value Store

Lots of dataSome Database To Perform Rapid CalculationsAnd some databasefor graphs And Some Distributed Key Value Store



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Action requires Prediction

Lots of dataSome Database To Perform Rapid CalculationsAnd some databasefor graphs And Some Distributed Key Value Store



Draw A Line For the future

What are my real users groups ?

Should I launch a discount offering or not ? To everybody or to specific users only ?

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The Medieval Fairy Land

Lots of data Some Tools To Do Some Maths Some Other To Do Some Charts and some MACHINE LEARNING


Some Database To Perform Rapid CalculationsAnd some databasefor graphs And Some Distributed Key Value Store

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Applied Discoveries

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Launch A Marketing campaign

After a few days PREDICT based on behaviours◦ Total ARPU for users

after 3 months◦ Efficiency of a campaign◦ Continue or not ?

Example Marketing Campaign Prediction

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A very large community

Some mid-size communities

Lots of small clusters mostly 2 players)

Correlation◦ between community size

and engagement / virality Meaningul patterns

◦ 2 players patterns◦ Family play◦ Group Play◦ Open Play (language

community)

Example Social Gaming Communities

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Two-Way Clustering◦ Assess customer behaviours◦ Assess items equivalent classes

Modeling + Simulation◦ Evaluate free items / item bought

ration per item kind ◦ Simulate future rules◦ Sensibility to price evaluation

Enhance customer buy recurrence

ExampleFremium Model Optimization

BusinessModel

User Profiling

Simulation

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Questions

Online Games Analytics - Data Science for Fun

Technology

Transcript of Online Games Analytics - Data Science for Fun