This document summarizes key metrics and trends in the Chinese mobile games market from 2009-2013 based on data from TalkingGame. It finds that card battle genres are growing in popularity while casual titles remain popular. However, most titles are unprofitable with low retention and LTV. Competition is intense with homogenization and high user churn. It recommends improving user experience and retention through better tutorials, engagement features, and optimizing difficulty curves. Data-driven optimization of a sample card game title improved metrics like day 1 and 7 retention through technical upgrades and gameplay adjustments.

1. Mobile Games
in China
August 2013

2. 2009～2014 China’s Market Size Of Mobile Game
Source: iResearch Annual Data Report On Mobile Game 2012

3. ？数据Q1-Q2 2013 Sum-up？

4. Share of New Titles by Genre
38.92%
16.02%
9.34%
8.95%
8.14%
Casual
Strategy
Card Battle
Action
Sport
RPG
Card
Adventure
Other
Card battle titles became the new hot spot.
While casual titles are still CP’s first choice for entry to market.
Data Source: TalkingGame

5. Revenue Share by Genre
36.8%
11.7%
16.2%
20.9%
4.7% 5.0%
2.2%
0.8% 1.7%
0%
10%
20%
30%
40%
Card Battle Strategy MMORPG T-RPG Action Card Tower Def Casual Other
Data Source: TalkingGame

6. Main stream titles are quality challenged
0%
10%
20%
30%
40%
Rating for main steam titles in China
Homogenization of titles are overwhelming. Copycats everywhere right after the entry of new
starred titles
TalkingGame
Matrix for Rating
Metrics for Rating: TalkingData Analytics Mobile Game Evaluation Matrix
Data Source: TalkingGame
RevenueShare
ARPDAU
Retention Rate
Day7
Retention
%
Day14
Retention%
Day14
Retention%
15-day LTV
Game
Mechanic
User
Life time
Organic
Users
UE
Marketing
Forces
R&D
Forces

7. 35%
25%
22%
14%
3%
1%
0% 50%
<￥1
￥1～$2
￥2～￥3
￥3～￥5
￥5～￥10
>￥10
Titles…
Passing Line: LTV￥3
80% of all titles are Non-profitable
2.3
3.2
2013 Q1 2013 Q2
CPA nearly doubled from Q1 to Q2, 2013
60%+
80% titles still unbalanced for a new user
30 days after the acquisition
CPA￥3
Data Source: TalkingGame

8. 盘点 ！建议
User Behavior
Changes
？

9. Mobile game user playing time is fragmented
20.1
18.2
18.8
16.8
17.4
16.7
15.5 15.7
16.6
15.6
14.7 14.6
15.2
10
15
20
25
2012-6 2012-7 2012-8 2012-9 2012-10 2012-11 2012-12 2013-1 2013-2 2013-3 2013-4 2013-5 2013-6
3
4
5
6
每日游戏次数 每日游戏时长
Playing time per user spends on each game is dropping significantly from Q2, 2012
although total number of game sessions per user per day is keeping steady
Mins Sessions
Daily Game
Sessions
Daily Playing
Time
Data Source: TalkingGame

10. Day1 Retention Trend For New Plays Q1-Q2, 2013
Too many options for users in the crowded market. Significant dropping trend of the
Day1 retention for each individual title
30.6%
28.4% 28.8% 28.6% 28.7%
27.1%
26.5%
25.8%
26.4%
25.6%
25.1% 25.2%
24.7%
20%
25%
30%
35%
40%
2012.6 2012.8 2012.10 2012.12 2013.2 2013.4 2013.6
Competition is intense. The red sea is coming?
Data Source: TalkingGame

11. 盘点 ！建议Q3-Q4
Outlook
？

12. LTV still keeping down
1.9
2.4
2.8
3.0
1.8
2.3
2.7 2.8
0
1
2
3
4
3-Day LTV 7-Day LTV 14-DayLTV 30-Day LTV
Q1 LTV(￥) Q2 LTV(￥)
Compared with Q1，Q2 LTV fell down instead of rising up as expected
LTV : Revenue contribution after certain days since acquisition per new user
 Q1LTV boosted by the
Spring Festival season
 The massive market
does not look
optimistic
Data Source: TalkingGame

13. 0
1
2
3
4
LT-1
LT-3
LT-5
LT-7
LT-9
LT-11
LT-13
LT-15
LT-17
LT-19
LT-21
LT-23
LT-25
LT-27
LT-29
LT-35
LT-45
LT-55
LT-90
IAPs and campaigns only focus on short term, perform insufficiently for long term development.
Revenue growth nearly stops after 2 weeks for new users since acquisition.
3d 1.3
7d 1.8
14d 2.7
30d 2.85 90d 2.95
Main stream titles operation is unhealthy
UA-focused can not push effective monetization
Data Source: TalkingGame

14. 盘点 ！建议
Operation for
Chinese Market？

15. UA Channels: Fragmented
3rd Party App Store Social Network
Other
Ad NetworkPlatform
CPA：Android ￥3～6；iOS ￥5～20
Conversion%（click->install）：Android 1%～3%；iOS 1%～5%
Data Source: TalkingData Campaign

16. 5%
30%
5%
10%
50%
0%
20%
40%
60%
Background
Relationship
MarketManual Taste
Data
Key Factors For Evaluation
• Background
– CP’s branding awareness and background
influence deeply on PR and promotion
result
• Relationship
– This is must-have in China
– Especially with special resources
• Reference
– Proven references from other platforms or
the market add significant credit
• Manual Taste
– Manually test on genre, mechanic, art,
compatibility, tutorial and every aspect is
the most direct way to evaluate
• Data
– Test with trial promotion resources and the
performance data will tell the truth
Mobile Game Evaluation System For Publishing Platform

17. Quick Key Metrics Evaluation System
Key Metrics Questions Answered Calculation Reference
Organic New Self-promotion & viral
capability
Avg. daily organic
installs
>200
Day1 Retention First time experience
reflection
Day1 retained user
counts / Day0 new user
counts
30%
Day 7 Retention Sustaining activation of
users
Day7 retained user
counts / Day0 new user
counts
12%
Monthly Paying
Rate
Ratio of paid users Monthly paid user
counts / MAU
Depends on
genre
2～5%
14-day LTV Rev contribution after 14
days per user since
acquisition
Rev. within 14 days
from new users / Daily
new user counts
￥2.5
60-day LTV / 30-
day LTV
Long term monetization
potential
60-day LTV / 30-day
LTV
1.3
Data Source: TalkingGame

18. Key Metrics Evaluation & Comparison
41.2%
3.7%
9.0%
28.4%
21.8%
10.9%
39.8%
8.5%
16.3%
31.2%
24.2%
12.1%
0% 10% 20% 30% 40% 50%
One-day user%
Day30 Retention%
Day7 Retention%
Day1 Retention%
30-day Active%
7-day Active%
Card Battle Genre Avg. Total Avg.
Data Source: TalkingGame

19. 数据观察 Succeed with Data！

20. Data-driven Success
20
Data-driven Success A
A
RR
R
• Metrics System
• Tool to power up
• Workflow

21. TalkingData AARRR Metric System
21
Refer
Revenue
Retention
Activation
Acquisition
Monetization
Conversion
Engagement
Acquisition

22. TalkingData AARRR Metric System
22
• Install / Sign-ups
By campaign/channel
CAC（Channel）
Conversion （Channel）
• Organic Users
• Marketing Users
• Click -to- Install -to- Sync
• Fake Users
• New User Perception
Perception by Channel
• DAU
• MAU
• Next Day Activities
• Usage
Login times
Login length
• Monthly Active Days
• DAU/MAU
• Retention
1 day/
7day
30day
• Engagement
Monthly Logins per User
Lifetime sessions
1～10-day activity after Install
• User lifetime
RetentionActivationAcquisition
ACQ = F(Campaign,channel,
Users，CAC, Conv%)
ACT = F(First time Experience，
Usage,Design/UX)
RET = F(User guide，
operation，task，alert)
Players & Channels Engagement

23. TalkingData AARRR Metric System
23
• ARPU（Monthly）
• ARPPU（Avg. Revenue per Paying
User
• LTV （lifetime value）
• Virtual currency purchased/spent
By level/By date
By types purchased
• Paying users（%）
• New paying users
• Time/level of first charge
• Whale
Revenue Refer
REV = F(Charge trap,whale, Conv%)
• K-factor
• Invites
Per DAU
Per who send invite
• Invite accept（%）
• Times By type
Massages
E-mail
• Cohort by invitee
Revenue
ARPU
REF = F(Excitation,UX)
Monetization Viral

24. TalkingData White Paper For Mobile Game Data Analysis
24
• Standard and unified definitions
of all the Key metrics based on
AARRR model system
• Benchmarking enabled to help
generate valuable insight of your
data

25. Key Metrics
New Player Acquisition & Tutorial
Activation & Retention
Engagement & Behavior
IAP Drill-down
Player Segmentation
Right Tool to Power up
Real- time

26. Best
Practices
Retention is KING!
A Data-driven
F2P Card Battle Game

27. Red Infinity was established in 2010 and
has rich experience in product
development and publishing. The
company has become one of the industry
leaders in just one year.
MAU 4,000,000
Data-driven Workflow

28. Description
★ TouchArcade.com HOT
NEW GAME ★
Versions
Initial release：Sep 14, 2012
Enhanced version：Nov 1, 2012
F2P
Puzzle + Battle + Collection

30.  DAU/MAU
 Day 1 retention
 Day 7 retention
 Conversions(%)
 Virtual Expense
Behavior
KPIs
Tracking
Measure &
Analysis
Solution
Optimize
Testify

31. The key metric to track during initial stage
First time experience and impression
Acceptance of the theme, content, visual quality, arts…
Day 1 Retention
18.6% VSAvg.
Day 1 Retention for card games
~30%
Benchmark:

32. Bad Day1 retention rate, but steady for Day2 and subsequence.
Something must be wrong with the
new player initialization stage!

33. 34
Load
Sign up
Create
Character
Start
Tutorial
Finish
Tutorial
Conversion Funnel for initial stage

34. Frequent Connectivity FailureTutorial
suddenly lost

35. Step 1 – Enhancement
Move to more stable IDC
Dedicated server for domestic players
Simplify and enhance tutorial
Polish UI to gain more visual attraction
Solutions
Step 2 – Optimization
Localize to fulfill local players’ preference
Theme Core UX Art

36. Testify & Ongoing Optimization

37. Result of daily incentive boost, e.g. Login bonus
How are core players growing in game
Acceptance of difficulty settings for gaming
The key metric to reflect gameplay acceptance and performance of
player engaging operations

38. Plenty of incentive activities
Mission complete bonus
Daily login bonus
Free cards offer
Friends alliance
⋯⋯
But
Day 7 Retention
9.2% VSAvg.
Day 7 Retention for card games
~15%
Benchmark:

39. Significant player Drop off at the growing levels(16-30)
Something wrong with the
gameplay design at these levels
Analysis by Churning Level Distribution

40. Option1: Players Power-up
Higher winning rate of powerful card lottery
Stronger friend alliance for early stage players
More chance to get enhancing virtual items
Solutions
Option2: Weaken Challenges
Lower monster’s numbers to bring down
mission completion difficulty
Easier player advancing at growing stages
Day 7 Retention
13.6%Avg.
A/B Analysis &
Ongoing Optimization

41. Test in App store，Without Marketing.

42. Thanks
www.TalkingGame.com
A
A
RR
R