the importance of the future
TRANSCRIPT
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THE IMPORTANCE OF THE FUTURE
Lloyd Melnick
Casual Connect 2012
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Agenda
BackgroundCurrent state of analyticsAnalytics 2.0Summary
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BACKGROUND
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Lloyd Melnick
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CapitolBroadcasti
ng
FiveOneNine
GamesEW Scripps
FiveOneNine Games
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Our Business Strategy
GAME DEVELOPER
• Campaign Story launches next month
GAMEPUBLISHER
• Publishing Program launched this week
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Analytics and gaming
In-Game Analytics Tools
Statistical ToolsPredictive ModelsData Mining
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Analytics and Gaming
In-Game Analytics
(Dashboards)• What Happened?
Statistical Tools
(Predictions) • What will Happen?
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Customer Lifetime Value Most Important Metric
Current Lifetime
Value
Future Predicte
d Lifetime
Value
Better Business Decision
s$$$$
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CURRENT STATE OF ANALYTICS
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In-Game Analytics Tools
11
Lifetime
DAUSessio
n Times
2-day retenti
on7-day retenti
on
Virtual Goods Sold
K-Factor
Visualization of Game Metrics
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In-Game Analytics• Easy Visualization of high level
metricsExecutive Dashboards
• Ability to address immediate concerns Ad-Hoc Reports
• Where exactly is the problem?Query/Drilldown
• What actions are needed?Alerts
Kontagent, Mixpanel, Honeytracks, CollectTM & MeasureTM (by GamesAnalytics)
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ANALYTICS 2.0
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STATISTICAL Analysis • Are there statistically significant
associations among factors?Correlations and CHI SQ
• Are there statistically significant differences among groups in usage or monetization?
T-tests & ANOVA
• What are the factors (i.e.: gender, age) that “significantly” impact revenue and by how much?
Regression Analysis
• How are the high value players monetizing differently than most players?
Outlier Analysis
Excel, R, SAS, SPSS, STATA, SWRVE, PredictTM
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Forecasting
• How much revenue will we bring in next quarter?
• How many users will we have in the future (near term)?Time Series Analysis
Excel, R, SAS, SPSS, STATA
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Predictive Modeling
• Who is more likely to monetize? • Who is more likely to react to in-
game messaging? Logistic Regressions, Decision Trees, etc.
• What will be the lifetime of a user?
• How long will it take for users to monetize? (time to first purchase)
• What factors impact the retention of the users?
Survival Analysis
R, SAS, SPSS, STATA, PredictTM, MeasureTM (by GamesAnalytics)
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Data Mining• Are there clear “segments” among
our users that could be approached differently?
Clustering (Segmentation)
Analysis
• Are there items that sell “together”?Association Analysis
• How do users feel about our games?• What are the main topics of
conversation for our Twitter followers?
• Are comments on our Facebook page mostly positive or negative?
Text Mining (Consumer
Sentiment Analysis)
SAS Enterprise Miner, SPSS Modeler, Weka, PredictTM
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Simulation
• How long do tasks in our game take to play on average?
• What happens if we tweak the rules of the game?
Monte–Carlo Simulation
Excel, R, Risk Solver, SAS, SPSS, STATA
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Optimization
• What is the optimal price for the virtual goods?Price Optimization
• What is the optimal allocation of resources for supporting the game?Linear Programing
R, Risk Solver, Oracle Cristal Ball, SAS
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SUMMARY
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Huge opportunities to use analytics better
Analytics is the foundation of business and games deep insight
They help you optimize production and marketing decisions
They help improve the game and the user experienceAdding predictive modeling to in-game analytics lays the foundation for additional optimization of business decisions