Use Game Analytics to understand your players and your monetizers. Anyone can do it! Alison Bilas, VP of Product in GameAnalytics, explains how to best integrate your data and optimize your game accordingly.

1. Data scientists need not apply:
How anyone can do game analysis
Casual Connect, November 2014
@allisonbilas | allison@gameanalytics.com

2. Using data to
understand your
players and
monetizers.

4. Analyst
Jr. Producer Producer Monetization Mgr.
Developer Senior PM

5. Descriptive Exploratory Inferential Predictive Causal
Quantitatively
describing data
Looking for
previously unknown
relationships in
data
Testing theories
with a sample of
data
Analyzing current
events to predict
future events
Measuring what
happens to one
variable when you
change another
Distribution;
5-number
summary;
Before/after
Directionality;
Visualizations
Regression models;
Chi squared
Modeling, machine
learning, data
mining
A/B testing
OBSERVE EXPERIMENT

6. Descriptive Exploratory Inferential Predictive Causal
Quantitatively
describing data
Looking for
previously unknown
relationships in
data
Testing theories
with a sample of
data
Analyzing current
events to predict
future events
Measuring what
happens to one
variable when you
change another
Distribution;
5-number
summary;
Before/after
Directionality;
Visualizations
Regression models;
Chi squared
Modeling, machine
learning, data
mining
A/B testing
“EASY”

7. ‣ Quantitatively describing data
‣ Distribution of data; 5-number summary;
Outliers
Score Percentiles by Boost Used
0
28
56
84
112
140
10. 25. Median 75. 90. 99.
Valentine Winter
Prism Ruby
Blaze Burst
Stone No Boost
Descriptive

8. ‣ Looking for
previously unknown
relationships in data
‣ Visualizations are key
component
Exploratory
Monetizers by Amount Spent per Customer
0
1,000
2,000
3,000
4,000
$0 - $5 $5 -$10 $10 - $25 $25 - $60 $60 - $280 $280 - $2975
Total Bookings by Amount Spent per Customer
$0
$25,000
$50,000
$75,000
$100,000
$0 - $5 $5 -$10 $10 - $25 $25 - $60 $60 - $280 $280 - $2975
4% 6%
16%
22%
35%
17%
34%
18%
24%
15%
9%
1%

9. ‣ Measuring uncertainty in analysis
‣ Linear regression; Chi squared
Inferential

10. Three Big Questions
INSTALLS
How many people
have installed my
game?
DAU
How many people are
playing my game?
REVENUE
How much money is
my game generating?
Acquisition Engagement Monetization

11. Really good analysis…

12. Revenue declined by $2K (-5%)
week-over-week after the re-
engagement campaign ended.
This was caused by a 3% decline
in DAU, which in turn reduced
the number of monetizers by 3%.
Those that did spend continued
to spend at the same ARPPU of
$7.29.
Reporting Analysis
DAU = 1.25M
Revenue = $41.4K
ARPPU = $7.29
Conversion = 0.45%

13. Revenue declined by $2K (-5%)
week-over-week after the re-
engagement campaign ended.
This was caused by a 3% decline
in DAU, which in turn reduced
the number of monetizers by 3%.
Those that did spend continued
to spend at the same ARPPU of
$7.29.
Reporting Analysis
DAU = 1.25M
Revenue = $41.4K
ARPPU = $7.29
Conversion = 0.45%

14. Revenue declined by $2K (-5%)
week-over-week after the re-
engagement campaign ended.
This was caused by a 3% decline
in DAU, which in turn reduced
the number of monetizers by 3%.
Those that did spend continued
to spend at the same ARPPU of
$7.29.
Reporting Analysis
DAU = 1.25M
Revenue = $41.4K
ARPPU = $7.29
Conversion = 0.45%

15. Revenue declined by $2K (-5%)
week-over-week after the re-
engagement campaign ended.
This was caused by a 3%
decline in DAU, which in turn
reduced the number of
monetizers by 3%.
Those that did spend continued
to spend at the same ARPPU of
$7.29.
Reporting Analysis
DAU = 1.25M
Revenue = $41.4K
ARPPU = $7.29
Conversion = 0.45%

16. DAU = 1.25M
Revenue = $41.4K
ARPPU = $7.29
Conversion = 0.45%
Revenue declined by $2K (-5%)
week-over-week after the re-
engagement campaign ended.
This was caused by a 3% decline
in DAU, which in turn reduced
the number of monetizers by 3%.
Those that did spend
continued to spend at the
same ARPPU of $7.29.
Reporting Analysis

17. ‣ Continue to use push
notifications to re-engage
users and support DAU
‣ Prioritize dev work for daily
prizes to increase return
rates
‣ Consider creating a high
priced gem package to
increase ARPPU
Recommendations

19. You do see,
you just don’t observe.
Sherlock H.

20. Allison Bilas, VP of Product
@allisonbilas
allison@gameanalytics.com
Additional Reading:
https://bitly.com/bundles/sparklingallison/
We’re
hiring!

21. UNESCO Game Design Challenge
$100K Prize
Incubate a game on
peace, sustainable development
and global citizenship.
http://mgiep.unesco.org/

22. BEST CHART EVER!