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Using predictive analytics to drive game personalisation. February 2012. Agenda. Who we are What is a nalytics? Predictive modelling and player segmentation Building personalised e xperiences A big b rother future?. ` Games Analytics. 30 + years games industry experience - PowerPoint PPT Presentation
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Copyright GamesAnalytics ©2011
Using predictive analytics to drive game personalisationFebruary 2012
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Copyright GamesAnalytics ©2011
Agenda• Who we are• What is analytics?• Predictive modelling and player segmentation• Building personalised experiences• A big brother future?
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• 30 + years games industry experience• 15+ years dedicated to online & mobile games
• 15+ years data analytics experience with finance and retail sectors
`GamesAnalytics
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`ChangeTheGame
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So what is Analytics?Analytics is the process of developing optimal or realistic decision recommendations based on insights derived through the application of statistical models and analysis against existing and/or simulated future data – wikipedia
Analytics is not
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It’s also not easy• Challenges
• Big data• Complex player behaviours• Multiple monetisation mechanics• Overly focusing on whales• Making the data drive value
• Never mind being expensive, resource and data intensive…slightly mind-bending and probably just a fad…
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The problem with Dashboards…• They almost never give you the information you actually need to
action anything useful• They tell you about the average player• They tell you old information• They always look like this
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A/B Testing1. Trial two versions and see which is most popular2. Pick the most popular and roll it out to everyone3. Repeat.
• One size fits all• The Horizon Effect ….
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Funnel Analysis• Originated from web analysis• Great for linear progress and identifying ‘leaks’
• Cohort analysis• Multiple gameplay routes• Multiple monetisation mechanics• Works for simple social games
• By its nature does not recognise multiple player types or non-linear gameplay
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Next Generation Analytics• Behavioural Segmentation
• Social Analytics
• Predictive Modelling
• Real time in game messaging
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Who are my players?• A game’s player base is made up of lots
of different player types
• Each person is experiencing the same game differently
• Understanding player behaviours is vital
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Revenue Potential
Vira
lity
Pote
ntial
31%0.89%22%
$1.75
%Volume%Paying7Day Ret
CAC25%
1.30%26%
$2.21
5%0.199%
$2.38
14%0.9721%
$1.94
Early Enthusiasts
Confident Completers
Social Involver
Sporadic SemiEngaged
Losing Momentum
Need Guidance
Borderline Incompetent
6%2.34%57%$4.40
12%0.8659%
$3.57
7%0.55%36%$0.75
`Player Segmentation
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The Power of Prediction
• Once you understand your different players…
• …You can start to predict what they want
• and use this information to deliver immediate player value
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Building Predictive Models• Core predictive models in SAS & R
• Multi-variant models can include 100+ separate variables
• Each model allows you to target a set of users precisely
• High propensity to take up the offer
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1 2 3 4 5 6 7 80
0.05
0.1
0.15
0.2
0.25
Variable Contribution
24 Hours + Gameplay
High % GiftedItem
Total Stamina 5000+
Level 7-12 Fighting Events
Accepted Invite High PVP Low Mission
Completion
• Score model at key points in the game
• Start of Session• Start of Mission• After Mission Failed
• Select players who have high model score (high likelihood to purchase)
• Send message with offer/incentive
`Predicting Purchase Behaviour
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Defectors and Engaged players behave differently in 1st 20 minutesPredict likelihood to defect and invoke retention activities before it is too late
Start 150 Events 500 Events
Early Defectors
Engaged
Defectors
AnalysisPeriod
CountryAge
Gender
Level Momentum, Average Seconds Per
Event, Socialness,Features Consumed
Detailed Events:Quests Completed,
Purchase Behaviour,Organising Tasks,Specific Missions
Apply Model at 150 Events.Treat High
Scores with Targeted Messages
`Predicting Defection
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Using Data Effectively• Games data collection benefits from huge
amounts of rich behavioural information• (When event collection is applied correctly)
• Each individual player creates a complex decision path
• Information can be mined and used to optimise gameplay
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The Players’ Views• Game design is generally focused on creating a great game
• We need to look at it from the player perspective
• Predictive analytics enables you to understand and identify behaviours to adapt gameplay to the player’s personal profile
• Creating great personalised gameplay experience
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Big Brother….
• Data protection
• Privacy
• Exploitation of user profiles
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The Adaptive Game• Analytics provides a huge opportunity to
deliver personal gaming experiences• Using the power of data for good
• A new concept in game design• An incredibly powerful way of dynamically altering
games• Adapting a game to players behaviour in real time
• Player satisfaction delivers increased revenues
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Any Questions?