Chris Wright: Games Analytics

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Analytics 101 – A crash course on why you should care
October 2011

Copyright GamesAnalytics ©2011

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Who am I?
16 years in the games industry

Involved in over 10 console games and over 100 mobile games

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Analytics, boring?

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How Zynga changed the world

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Analytics Tips For Games

Focus on the player `


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Focus On The Player

Focusing on the Player

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Focus On The Player
• Build a player centric view of game design

• Model your expected user base

• Understand how different players interact with the game

• Customise the game based on player behaviour

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Focus On The Player
• Aim to make the players enjoy the gameplay – in the different ways
they play – sociable, completers, explorers

• Length of gameplay is generally a good indication of monetisation

• Analytics allows the game to be tailored to individual types of players

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Collect the right
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Data


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Collect The Right Data
• Understand the information you want to analyse

• Focus on player level, not game level information

• Identify significant events in the game

• Build good data integrity

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Collect The Right Data
Good Events Bad Events
Player Progress Browser & Device Type
Player Tasks Bugs and Crashes
Items Bought & Sold Movement
Items Gifted Buttons Clicked
Levels Page Views
Missions
Friends

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Understand the metrics `


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Understand The Metrics
• Metrics generally means dashboards

• This provides historic information

• It tells you the health of your game

• Use metrics to identify the areas of the
game that need focus

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Understand The Metrics
• Retention • DAU / MAU

• Engagement • Player Behaviour

• Life Time Value • Demographics

• ARPU / ARPPU • Game specific metrics

• Whales • Virality

• Time to First & Second Payment

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Segment
Player
Behaviour

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Segment Player Behaviour
7%
%Volume
0.55 6%
0.34
%Paying
36% 25% 57% 7Day Ret
Virality Potential

$0.75
1.30% $4.4
0 CAC
26%
31% $2.21
0.89%
22%
Focusing on the Player $1.75
14%
12%
0.86
59%
$3.5
Early Enthusiasts
Confident Completers
0.97 7
5% 21% Social Involver
0.19 $1.9
9% 4
$2.3 Sporadic Semi Engaged
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Losing Momentum

Need Guidance
Revenue Potential Borderline Incompetent


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interaction
Social

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Social Interaction
• Connectedness

• Centrality

• Cohesion

• Reciprocity

• Social Influence

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Social Interaction
• Identify player ‘bridges’
• Isolated players
• Gaps and holes, leading to group fragmentation
• Reward highly influential players
• Manage cohesion, caused by influential players
• Reconnect isolated players
• Build bridges and connect sub networks
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Identify player value

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Identify Player Value
• Time to first payment (2-4 weeks drive high LTV)
• Payment patterns (regular, increasing, decreasing)
• Triggers for first spend (why now?)
• Time lag to second spend (be quick)
• Reasons for reactivation (paying players stick around)

• All actionable to raise LTV
• Overlay profiles to refine targets
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Pattern analysis

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Pattern Analysis
1st Event 2nd Event 3rd Event

61%

12%
9% Challenge Start

Gifted item

Visited Home
Intervention here
Use event order to predict and Invite Neighbour
encourage next action Bought Item

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Pattern Analysis
• Pattern analysis is a powerful technique

• Using it allows behaviours to be tracked and identified

• This can be used to react to next best option

• This can also be used to identify actions that precede abandonment

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Predictive Modelling

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Predictive Modeling
• Ability to predict player behaviour

• Identify players likely to undertake an action if encouraged

• Provide the means to deliver a marketing intervention that is:
• Timely

• Personal

• Appropriate

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Simple Multivariate Predictive Model
Variable Contribution
Likelihood N Y
0.25
Least 99.5% 0.5%

0.2 2 98.9% 1.1%
3 99.5% 0.5%
0.15
4 99.5% 0.5%
#Sessions
11+ Focusing on the Player
0.1
5
6
98.4%
95.8%
1.6%
4.2%
0.05 7 95.3% 4.7%
Gifted Item
8 93.6% 6.4%
Total 0
1 2 3 4 5 6 7 8 9 85.2% 14.8%
Stamina
5000+ Most 62.2% 37.8%
Highest Wounded Accepted Friend
Run Away Total 92.8% 7.2%
Level 10+ Giant Invite Count 10+

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Actionable
results

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Actionable Results
• The key to Analytics is to provide the tools to improve the game
• This can be:
• Improve Gameplay
• Increase Revenue
• Reduce Abandonment
• Increase Retention
• Reward Loyalty
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Actionable Results
• Analytics provides the means to identify these traits

• To group players into manageable segments

• To predict their future behaviour

• To intervene to change behaviours and move the graph

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Actionable Results

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Analytics in Games

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The Industry
• Analytics is becoming a key skill in game development

• Zynga has a 60 person Analytics team

• Analytics allows game design to understand the player

• Games are increasingly becoming data driven

• Games that adapt to the player is the future
(the one size fits all is dead)
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Any Questions?


Chris Wright: Games Analytics

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