Sonamine casual connect july 2011 beyond metrics - predictives
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Sonamine presentation at Casual Connect July 2011. Beyond Metrics - Predictives with lessons and perspectives from other industries.
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Sonamine casual connect july 2011 beyond metrics - predictives
- 1. Nick Lim Casual Connect CEO Online Social Games Track Sonamine July 21, 2011 (Revised: DRS, July 28) Beyond Metrics: Predictives With lessons and perspectives from other industries
- 3. © 2009-11 Sonamine LLC. Confidential and proprietary Chapter 1 What are predictives?
- 4. Predictives help you avoid spamming your players © 2009-11 Sonamine LLC. Confidential and proprietary Source: â Capital OneâŠover 20 credit card offers in 3 weeksâ Consumerist July, 2011
- 5. From metrics (reporting) to predictions © 2009-11 Sonamine LLC. Confidential and proprietary Source: Competing on Analytics Davenport & Harris
- 9. © 2009-11 Sonamine LLC. Confidential and proprietary Chapter 2 How to identify a predictive
- 13. © 2009-11 Sonamine LLC. Confidential and proprietary Chapter 3 Using Predictives (A Crash Course)
- 14. © 2009-11 Sonamine LLC. Confidential and proprietary Behavior Random selection Without predictives, every segment has equal concentration of a future behavior
- 15. © 2009-11 Sonamine LLC. Confidential and proprietary Behavior Random selection Predictive Predictives allow segmentations that concentrate the target behavior
- 19. © 2009-11 Sonamine LLC. Confidential and proprietary Object for which youâre predicting (In games: usually the player ) Score that ranks the players Higher score ïš player is more likely to behave in a certain way (Examples: convert, churn, buy) What predictive output looks like
- 21. © 2009-11 Sonamine LLC. Confidential and proprietary Chapter 4 Myths, Lessons, & Tips
- 26. © 2009-11 Sonamine LLC. Confidential and proprietary Chapter 5 Case Studies
- 29. © 2009-11 Sonamine LLC. Confidential and proprietary Case Study #2: Korean Social Game
- 31. © 2009-11 Sonamine LLC. Confidential and proprietary 63% Higher Case Study #2: Conversion rates
- 32. © 2009-11 Sonamine LLC. Confidential and proprietary Case Study #3: Portal/developer of multiplayer casual social games
- 34. © 2009-11 Sonamine LLC. Confidential and proprietary Case Study #3: Conversion rates (160% higher than no promotion)
- 35. © 2009-11 Sonamine LLC. Confidential and proprietary 150% higher Case Study #3: Conversion rates (150% higher than random promotion)
- 37. © 2009-11 Sonamine LLC. Confidential and proprietary A final note Games as a service will profit from predictive player relationship management
- 39. © 2009-11 Sonamine LLC. Confidential and proprietary For more about predictives and Sonamineâs free trial program
Editor's Notes
- 3 weeksâ worth of CapitalOne credit-card offers! This diagram is taken from a recent blog post on consumerist.com http://consumerist.com/2011/07/capital-one-sends-you-over-20-credit-card-offers-in-3-weeks.html Predictives make sure you donât get sent mail you donât want.
- Metrics = measuring things. After you measure things, you have to tell people what you measured. Then you can ask questions about what you measured, and you can be notified regarding measured things. This diagram is taken from the popular book Competing on Analytics by Tom Davenport and Jeanne Harris. http://www.amazon.com/Competing-Analytics-New-Science-Winning/dp/1422103323
- If that example top decile has 4X lift, it will therefore have 40% of the total player-conversions. For more on lift, including a curve showing the front-loading effect (the cumulative gains) of predictions, and a lift curve: http://www2.cs.uregina.ca/~dbd/cs831/notes/lift_chart/lift_chart.html
- True-positive rate = sensitivity False positive rate (α) = FP / (FP + TN) = 1 â specificity False negative rate (ÎČ) = FN / (TP + FN) = 1 â sensitivity