General approach to working with (f2p) (mobile) (social) game analytics for based on idea that there is a semantic difference between data gathered and assumptions made from this data.

2. ..little game

3. Present-day game
normally features tool*
allowing to collect
data about every
player's move
* tracking

4. Tracking data
is intended to be used to
tune player's experience
and increase revenue
performance figures
demographics
heat-maps
… etc

5. Key metrics concern
• audience
• retention
• monetization
Other metrics log
choices made by players
during gaming sessions

6. Assumption:
If I would know what sort of content players love in my game,
It will answer what content should I do.

7. Assumption:
If I would know what sort of content players love in my game,
It will answer what content should I do.
If I would know what weapon my players do purchase,
I'll do more weapons like this and have more revenue.

8. Assumption:
If I would know what sort of content players love in my game,
It will answer what content should I do.
If I would know what weapon my players do purchase,
I'll do more weapons like this and have more revenue.
If I would know what missions my players like to play,
I'll do more missions like this...

9. Assumption A:
If I would know what sort of content players love in my game,
It will answer what content should I do.
If I would know what weapon my players do purchase,
I'll do more weapons like this and have more revenue.
If I would know what missions my players like to play,
I'll do more missions like this.....bullshit

10. This idea leads only to making copycats.

11. This idea leads only to making copycats.
Even if you manage to do 'good' copycat of yours
most successful content, it will simply cannibalize the original.

12. Assumption A:
If I would know what sort of content players love in my game,
It will answer what content should I do.
If I would know what weapon my players do purchase,
I'll do more weapons like this and have more revenue.
If I would know what missions my players like to play,
I'll do more missions like this...yeah, it makes
the flowers grow

13. Another (less specific) assumption:
If I would know who plays my game, I'll know what they want.

14. Another (less specific) assumption:
If I would know who plays my game, I'll know what they want.
My typical player is 35+ years old housewife, so
I'm adding more vanity items: they love shopping.

15. Another (less specific) assumption:
If I would know who plays my game, I'll know what they want.
My typical player is 35+ years old housewife, I'm adding
more vanity items: they love shopping.
...

16. The question is
how to use analytic
beneficially

17. #1
Understand
the verge between data
and it's interpretation
Data
...
Analysis

18. #1
Understand
the verge between data
and it's interpretation
1. Data
Information, raw facts
2. Metrics
Measurement, comparison
3. Analytics
Interpretation, opinion

19. 1. Data
— Biased depending on how it's collected
— Is a common knowledge and is neither opinion nor answer

20. 1. Data
— Biased depending on how it's collected
— Is a common knowledge and is neither opinion nor answer
2. Metrics
— Depends on questions asked and measurements made
— Help to answer certain, specific questions

21. 1. Data
— Biased depending on how it's collected
— Is a common knowledge and is neither opinion nor answer
2. Metrics
— Depends on questions asked and measurements made
— Help to answer certain, specific questions
3. Analytics
— Is about future, not about already happened events
— Relies on asking questions (metrics)

22. #2
Question everything,
and ask the right questions
What sort of content
players love in my game?
Who are my players?
WHY players love this?
WHY and HOW players
are playing this game?

23. #3
Outline your goals

24. The process:
1. Define the design goals

25. The process:
1. Define the design goals
2. Measure and identify characteristics of feature / game

26. The process:
1. Define the design goals
2. Measure and identify characteristics of feature / game
3. Analyze to develop and design alternatives

27. The process:
1. Define the design goals
2. Measure and identify characteristics of feature / game
3. Analyze to develop and design alternatives
4. Design an improved alternative, best suited per analysis

28. The process:
1. Define the design goals
2. Measure and identify characteristics of feature / game
3. Analyze to develop and design alternatives
4. Design an improved alternative, best suited per analysis
5. Verify the design by checking 'pilot' characteristics

29. thanks!

30. Two useful links:
Leveraging Analytics and User
Segmentation to Drive Revenue
// Eric Benjamin Seufert
The Importance of Everything: A Crash Course in Design-Related Analytics
// Jim Brown (GDC Europe 2014, available in GDC Vault)
http://www.gdcvault.com/play/1020844/The-Importance-of-Everything-A