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Chris Wright: Games Analytics
The document is a crash course on analytics in the gaming industry, emphasizing the importance of understanding player behavior and preferences to enhance game design and monetization. It discusses the collection of relevant data, understanding key metrics, and the use of predictive modeling to improve player engagement and retention. The content highlights that data-driven game design is essential for future success in the industry.
Chris Wright: Games Analytics
- 1. ` Analytics 101 – A crash course on why you should care October 2011 Copyright GamesAnalytics ©2011
- 2. ` Who am I? 16 years in the games industry Involved in over 10 console games and over 100 mobile games 2 Copyright GamesAnalytics ©2011
- 3. ` Analytics, boring? 3 Copyright GamesAnalytics ©2011
- 4. ` How Zynga changedthe world 4 Copyright GamesAnalytics ©2011
- 5. ` Analytics Tips ForGames Copyright GamesAnalytics ©2011
- 6. Focus on theplayer ` Copyright GamesAnalytics ©2011
- 7. ` Focus On ThePlayer Focusing on the Player 7 Copyright GamesAnalytics ©2011
- 8. ` Focus On ThePlayer • 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 8 Copyright GamesAnalytics ©2011
- 9. ` Focus On ThePlayer • 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 9 Copyright GamesAnalytics ©2011
- 10. Collect the right ` Data Copyright GamesAnalytics ©2011
- 11. ` Collect The RightData • 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 11 Copyright GamesAnalytics ©2011
- 12. ` Collect The RightData 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 12 Copyright GamesAnalytics ©2011
- 13. Understand the metrics ` Copyright GamesAnalytics ©2011
- 14. ` 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 14 Copyright GamesAnalytics ©2011
- 15. ` 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 15 Copyright GamesAnalytics ©2011
- 16. ` Segment Player Behaviour Copyright GamesAnalytics ©2011
- 17. ` 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 8 Losing Momentum Need Guidance Revenue Potential Borderline Incompetent Copyright GamesAnalytics ©2011
- 18. ` interaction Social Copyright GamesAnalytics ©2011
- 19. ` Social Interaction • Connectedness •Centrality • Cohesion • Reciprocity • Social Influence 19 Copyright GamesAnalytics ©2011
- 20. ` Social Interaction •Identify player ‘bridges’ • Isolated players • Gaps and holes, leading to group fragmentation Focusing on the Player • Reward highly influential players • Manage cohesion, caused by influential players • Reconnect isolated players • Build bridges and connect sub networks 20 Copyright GamesAnalytics ©2011
- 21. ` Identify player value Copyright GamesAnalytics ©2011
- 22. ` 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 22 Copyright GamesAnalytics ©2011
- 23. ` Pattern analysis CopyrightGamesAnalytics ©2011
- 24. ` Pattern Analysis 1st Event 2nd Event 3rd Event 61% 12% Focusing on the Player 9% Challenge Start Gifted item Visited Home Intervention here Use event order to predict and Invite Neighbour encourage next action Bought Item 24 Copyright GamesAnalytics ©2011
- 25. ` Pattern Analysis • Patternanalysis 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 25 Copyright GamesAnalytics ©2011
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- 27. ` Predictive Modeling • Abilityto 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 27 Copyright GamesAnalytics ©2011
- 28. ` Simple Multivariate PredictiveModel 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+ 28 Copyright GamesAnalytics ©2011
- 29. ` Actionable results Copyright GamesAnalytics ©2011
- 30. ` Actionable Results • Thekey to Analytics is to provide the tools to improve the game • This can be: • Improve Gameplay • Increase Revenue • Reduce Abandonment • Increase Retention • Reward Loyalty 30 Copyright GamesAnalytics ©2011
- 31. ` Actionable Results • Analyticsprovides 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 31 Copyright GamesAnalytics ©2011
- 32. ` Actionable Results 32 Copyright GamesAnalytics ©2011
- 33. ` Analytics in Games Copyright GamesAnalytics ©2011
- 34. ` The Industry • Analyticsis 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) 34 Copyright GamesAnalytics ©2011
- 35. ` Any Questions? Copyright GamesAnalytics ©2011