the importance of the future

THE IMPORTANCE OF THE FUTURE

Lloyd Melnick

Casual Connect 2012

Agenda

BackgroundCurrent state of analyticsAnalytics 2.0Summary

BACKGROUND

Lloyd Melnick

CapitolBroadcasti

ng

FiveOneNine

GamesEW Scripps

FiveOneNine Games

Our Business Strategy

GAME DEVELOPER

• Campaign Story launches next month

GAMEPUBLISHER

• Publishing Program launched this week

7

Analytics and gaming

In-Game Analytics Tools

Statistical ToolsPredictive ModelsData Mining

Analytics and Gaming

In-Game Analytics

(Dashboards)• What Happened?

Statistical Tools

(Predictions) • What will Happen?

Customer Lifetime Value Most Important Metric

Current Lifetime

Value

Future Predicte

d Lifetime

Value

Better Business Decision

s$$$$

CURRENT STATE OF ANALYTICS

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

12

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)

ANALYTICS 2.0

14

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

15

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

16

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)

17

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

18

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

19

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

SUMMARY

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

Thank you!

Lloyd.melnick@fiveoneninegames.comTwitter: Lloyd Melnick

http://lloydmelnick.com/