In this presentation, COO of Aeria Games, Dr. Stefan Behrens took a look at how using metrics in making operational and corporate decisions has built significant value for Aeria Games. Careful interpretation of the data is needed for success and this presentation will show what Aeria Games has learned in the past, and how these lessons have helped to build a successful company based on data analysis.

1. Data driven decision making:
Avoiding pitfalls and building value
08.04.2012, Quo Vadis, Dr. Stefan Behrens

2. 1
Aeria Games and ProSiebenSat.1 Games have
combined forces on April 1, 2014
Industry leading monetization
Unparalleled marketing power
Strong developer relationships
Best-in-class operations
Global communities & reach
Top 3 player in
Europe
&

3. 2
Some facts on the combined business
Registered Users
Countries Serviced
Game Licenses Operated
Mobile Share of Revenues
35
77m
16%
39
&

4. 3
Data driven decision-making effectively drives almost all
aspects of our business at Aeria
Talent Product Acquisition Retention Monetization
Values

5. 4
At Aeria, decision making starts with strong values
VALUES

6. 5
Hiring the right talent is the basis for success
• Don’t hire (only) gamers
TALENT
• Put them through „boot camp“
• Let them crunch numbers
• Keep setting the bar higher & higher

7. 6
Picking the right games is not an easy feat
PRODUCT
Target Group Fit
Committed Developer
Proven Success
Adequate Art Style

8. 7
Lifetime Value
(365d ARPU)
Customer Acquisition Funnel
Buy & Spend
Aeria Points
(7d Conversion)
Return to
Play
(3d Retention)
Game
Login
(Reg-to-Play)
Landing Page
Registration
(Click-to-Reg)
Click on
Ad Banner
(CTR)
CTR: 0.23%
Clicks: 107,000
Click-to-Reg: 5.6%
Regs: 6,000
Reg-to-Play 33%
Players: 2,000
3d Retention: 45%
Retained: 900
7d Conversion: 8.5%
Spenders: 170 $14.09
Max CPC:
0.13 USD
Max CPL:
2.35 USD
Max CPP:
7.05 USD
Marketing: Maximum Customer Cost Calculation
Successful acquisition is about balancing a
simple, but fundamental equation...
ACQUISITION

9. 8
…but the equation can get mighty complex
$-
$5
$10
$15
$20
$25
Jan-12
Feb-12
Mar-12
Apr-12
May-12
Jun-12
Jul-12
Aug-12
Sep-12
Oct-12
Nov-12
Dec-12
Jan-13
Feb-13
Mar-13
Apr-13
May-13
30d LTV (a) 90d LTV (a)
1yr LTV (a) 1yr LTV (e)
Actual Predicted
Predictive LTV ModelingMulti-Channel Optimization
Search
22%
Display / Ad
Networks
38%
Branding
1%
Facebook 4%
PR
5%
TV
30%
ACQUISITION

10. 9
Retention rates can tell you a lot…
0%
10%
20%
30%
40%
50%
60%
70%
29.09.
02.10.
05.10.
08.10.
11.10.
14.10.
17.10.
20.10.
23.10.
26.10.
30.10.
02.11.
05.11.
08.11.
11.11.
14.11.
17.11.
20.11.
23.11.
26.11.
29.11.
02.12.
05.12.
08.12.
11.12.
14.12.
RR 3 days organic RR 3 days paid
Game Case: 3 Day Retention Rate (RR)
RETENTION

11. 10
…if you know how to read them
0%
10%
20%
30%
40%
50%
60%
70%
29.09.
02.10.
05.10.
08.10.
11.10.
14.10.
17.10.
20.10.
23.10.
26.10.
30.10.
02.11.
05.11.
08.11.
11.11.
14.11.
17.11.
20.11.
23.11.
26.11.
29.11.
02.12.
05.12.
08.12.
11.12.
14.12.
RR 3 days organic RR 3 days paid
Game Case: 3 Day Retention Rate (RR)
RETENTION
Technical issue
with a patch
Secondary accounts
of existing users

12. 11
However, sometimes, the answers are
less than obvious
30%
35%
40%
45%
50%
55%
60%
6.1.2012
6.3.2012
6.5.2012
6.7.2012
6.9.2012
6.11.2012
6.13.2012
6.15.2012
6.17.2012
6.19.2012
6.21.2012
6.23.2012
6.25.2012
6.27.2012
6.29.2012
7.1.2012
7.3.2012
7.5.2012
7.7.2012
7.9.2012
7.11.2012
7.13.2012
7.15.2012
Germany
UK
Game Case: 3 Day Retention Rate
RETENTION

13. 12
Especially, when soccer is involved
30%
35%
40%
45%
50%
55%
60%
6.1.2012
6.3.2012
6.5.2012
6.7.2012
6.9.2012
6.11.2012
6.13.2012
6.15.2012
6.17.2012
6.19.2012
6.21.2012
6.23.2012
6.25.2012
6.27.2012
6.29.2012
7.1.2012
7.3.2012
7.5.2012
7.7.2012
7.9.2012
7.11.2012
7.13.2012
7.15.2012
Germany
UK
Euro Cup!
Game Case: 3 Day Retention Rate
RETENTION

14. 13
Good sales strategy is fueled by analytics
Monthly Product Sales PlanContinuous KPI Analysis
1 [ 0- 5 )
2 [ 5- 50)
3 [ 50-100)
4 [100-200)
5 [200-400)
6 [400+)
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
0
None
1
[
0-5
)
2
[
5-50)
3
[50-100)
4
[100-200)
5
[200-400)
6
[400+)
1 [ 0- 5 )
2 [ 5- 50)
3 [ 50-100)
4 [100-200)
5 [200-400)
6 [400+)
Item Saturation
TS Redemption
CCU
Spender Buckets
Retention
MONETIZATION

15. 14
Season #1
 Price: $12 per spin
 No. of Spins: 16
 No. of Jackpots: 1,500
Season #2
 Price: $25 per spin
 No. of Spins: 14
 Number of Jackpots 1000
 Optimized composition of weapons
Season #3
 Price: $20 per spin
 No. of Spins: 20
 Number of Jackpots 500+500
 Optimized weapons and Jackpot
Shooter Game Case, Revenue 2013 Jun-Dec Event Optimization
Event
Season #1
Event
Season #2
Event
Season #3
Execute, analyze, optimize for best results
Jun Jul NovOctSep DecAug
MONETIZATION

16. 15
Beware… It’s a trap! (at least sometimes)
 Data consistency can be a b*tch
 Correlation ≠ Causation
 What get’s measured can be improved,
but what about intangibles?
 You can plan a pretty picnic,
but you can’t predict the weather!
PITFALLS

17. Data driven decision making:
Avoiding pitfalls and building value
08.04.2014, Quo Vadis, Dr. Stefan Behrens