Delivered at Casual Connect Eastern Europe 2018. Data analysis for game does not end at campaign management. How to optimize content of games, onboarding, monetization techniques based on Google Analytics for Firebase? From simple tips and tricks to advanced data mining using BigQuery integration. Presentation based on games case studies and practical examples. Examples of tests and analyses with the goal to improve ARPU and Buyer rate.

1. How to Optimize Games
Based on Firebase Data?
Mariusz Gasiewski
Head of Mobile Gaming and Apps Poland
Google

4. Analytics framework
Test like
crazy
Look for
value
Go deep
Start easy

5. 1.2M
monthly
active apps

6. Analytics framework
Test like
crazy
Look for
value
Go deep
Start easy

7. Is tutorial really important?

8. Did it succeed?
All users
Tutorial
completed

9. Going deeper with the data

10. ...and segment

11. Analytics framework
Test like
crazy
Look for
value
Go deep
Start easy

12. Go deeper with raw event data in BigQuery

13. Go deeper with raw event data in BigQuery

14. It is not a problem...

15. Data Studio reports based on Big Query data

16. Exporting Crashlytics data to BigQuery

17. ...with ability to use Data Studio

18. Tutorial step by step
Source: https://cloud.google.com/solutions/mobile/mobile-firebase-analytics-bigquery#visualizing_exported_crashlytics_data_with_data_studio

19. Analytics framework
Test like
crazy
Look for
value
Go deep
Start easy

20. Feature selection

21. Imaginary view
...reality
Red dots represent users that made in-app purchase
Blue dots represent users that didn’t make in-app purchase

22. A supervised learning algorithm that builds
multiple decision trees and merges them together

23. ...and example outcome

24. Analytics framework
Test like
crazy
Look for
value
Go deep
Start easy

25. Comparing 3 different mechanics

26. Firebase predictions
Learn (features) Predict (label)
Past 100 days

27. Firebase predictions
Learn (features) Predict (label)
Past 100 days

28. Firebase predictions

29. Firebase predictions
Used Firebase Predictions to
boost retention by 20% in their
hit game Dan the Man using
the Churn Prediction.

30. Dan The Man

31. Using predictions
1-Day Retention Rate 7-Day Retention Rate
Group 0: No Promotion 59.52% 25.35%
Group 1: Gift After Level 3 59.07% 25.34%
Group 2: Predicted
Churners
62.12% 30.24%

32. Maybe ads?

33. GAGEX used Firebase remote config
to optimize ad configurations
How can I test different ads configurations?
Will increasing rewarded video frequency help
or hurt my app’s user experience?

34. Finding optimal ad settings
Variant Total Session
Duration
Avg. Session
Duration
Number of
Sessions
Ads Revenue
Default 17m 42s 3m 20s 5.30 1x
Rewarded 2x +
Interstitial 2x
20m 56s
(+18.3%)
4m 16s
(+28.0%)
4.90 1.25x (+25%)
Longer session
duration
18% Increase in total
revenue
25%

35. Summary
Test like
crazy
Look for
value
Go deep
Start easy

36. Questions?
gasiewski@google.com