Vpon Taiwan Mobile Ad Statistics and Trends Q2 2014

Vpon 行動廣告
2014年第二季台灣行動市場數據報告

Agenda
Taiwan Mobile Market
- Mobile device market share (smartphone, tablet and mobile browser)
User Behavior Analysis
- Location, telecommunication companies, online behavior, App usage analysis
Special Occasions
- Dragon Boat Festival, Taipei metro attack, World cup 2014
Video App User Analysis
- Video App user analysis
Big Data Analysis and Application
- Using mobile data to optimize performance

Vpon in Taiwan
17 Million
Unique users per month
2 Billion
Requests per month
1,000
Renowned advertisers
Source: UU, Q2 2014, Vpon Inc.

Vpon in Asia
Pan Asia
Mainland China, Hong Kong, Macau,
Taiwan, Singapore, Malaysia, Thailand,
Philippines, Indonesia, Japan and Korea.
10 Billion
Impression per month

Vpon SDK
Multi platform
Support iPhone / iPad / Android / Mobile website.
SDK 4
Provide CPM & CPC Ad revenue.
Comply with MRAID standard for international
mobile Ad.
MRAID, Mobile Rich Media Ad Interface Definitions, Source: http://www.iab.net/mraid

Mobile device share
iPhone
Android
iPad
14%
81%
5%
Android : iOS = 8 : 2
l The number of Android devices
grows comparing to previous
quarter.
l With relatively friendly prices and
more new device model choices,
Android devices grow rapidly all
over Asia (South Korea, China,
and Malaysia). Meanwhile, the
global platform ratio is also close
to 8:2.

Android device share
Phone
Phablet
Tablet
46
43 44
46
11
10
Q1
Q2
Phablet: http://en.wikipedia.org/wiki/Phablet, Source: UU, Q2 2014, Vpon Inc.
Phablet rock
l Phablet becomes the main choice
of Android users. 46% users own
5”-6.9” phablet whereas 44%
users with 4.9” phones.
l Android tablet with screen size
larger than 7” get 10% users.
%

Top 10 Android models
Samsung Note 3 & S4
l Phones listed in 2013: HTC One,
Samsung Note 3 & S4, Sony Xperia Z,
Samsung Note 3 & S4 is included in the
Top 10 for the first time.
l Samsung Note 3 took the fifth place
after listing only for 8 months, showing
the strong demand of the big screen
mobile phones. Half phones of Top 10
are all the big screen mobile phones.
l 4.7 "- 5" is most widely used screen.
Samsung Note 2
Samsung S3
HTC One
Samsung S2
Samsung Note 3
HTC Butterfly
Samsung S4
Samsung Tab 2
Sony Xperia Z
HTC One X
5.5”
4.8”
4.7”
4.3”
5.7”
5”
5”
7”
5”
4.7”
2013/3/29
2013/10/29
2013/4/25
2013/3/6

Android OS versions share
Ginger Bread
9.7%
Froyo
0.4%
Honey Comb
0.3%
Ice Cream
Sandwich
11.4%
Jelly Bean
64.2%
Kitkat
13.9%
Most people use
Android 4.3
l 4.3.x Jelly Bean has accounted for
64.2%, is still the mainstream Android
version in Taiwan.
l The proportion of 4.4x Kitkat
increased from 4% of last quarter to
13.9% of this quarter, showed that
the consumers generally pursued to
update the system.
l The proportion of 2.x Froyo and
Ginger Bread dropped sharply, only
for 10.1%.

iOS Device Share
iPhone
iPad
iPad mini
74
64
18
26
8
10
Q1
Q2
Increase of iPad
Share
l More people prefer to use tablets
to connect the Internet. iPad Air
and iPad mini 2 launched in 2013,
lead to a replacement trend for the
iOS tablets. The usage is enhanced
due to the smaller size and easy to
carry.
%

Top 10 iOS models
iPhone 5
iPhone 5s
iPhone 4s
iPad 3
iPhone 4
iPad mini 1
iPad 2
iPad Air
iPad 4
iPad mini 2
Most people use
iPhone 5
l Currently, the iPhone 5 is the most
popular one of iOS mobile phone.
iPhone 5s listed in 2013, took the
second place rapidly, and quickly
replaced iPhone 4s.
l More and more people prefer to
use iPad. There are six models of
iPad and iPad mini on the list,
showing the strong demand of
iPad.

iOS versions share
iOS 5
4%
iOS 6
16%
iOS 7
80%
iOS 7 is the mainstream
l iOS 7 is built in iPhone 5s and 5c. The
share increases due to the growing
penetration of the new phones. Since
becoming available for download in
September 2013, iOS 7 has become the
most popular version taking 80% share.

Top 10 mobile device
No.1
No.2
No.3
No.4
No.5
iPhone 5
No.6
No.7
No.8
No.9
No.10
Samsung
Galaxy S2
iPhone 4S
Samsung
Note II
HTC Butterfly iPhone 4
iPhone 5S
Samsung
Galaxy S3
HTC One
Samsung
Note 3
l Although the iPhone 5 is the most popular one, there are 4 Samsung mobile
phones listed in Top 10. Samsung remains the most popular brand.

Mobile browser share
Safari
23%
Chrome
Mobile
5%
Android
Browser
72%
Built-in browser has
the highest usage
l The users prefer to use Android or
iOS built-in browsers to access to the
Internet.
l About 5% of users download
Chrome, as a commonly used mobile
phone browser.

Regional analysis of mobile devices
Northern
52.2%
Middle
23.0%
Southern
21.1%
Outling
Island
0.3%
Eastern
3.4%
Mobile devices become
more popular
l In this quarter, there is no obvious
regional distribution change. Mobile
devices penetration continues to grow
in Taiwan. According to the latest
survey of Institute for Information
Industry, the market share of mobile
devices has reached 58.7%. (2014/6)

Operators analysis
CHT
37.3%
Far
Eastone
28.6%
Taiwan
Mobile
27.5%
Vibo
4.1%
Asia Pacific
2.5%
The market share of
operators might change
l Top 3 operators cover 93.4% share,
Chunghwa is the top one, but the market
share has declined slightly over the
previous quarter, followed by Far Eastone
Telecom.
l Asia Pacific telecom provides EVOD
Internet service, Vibo telecom provides
WCDMA Internet service, the penetration
rate of both is 6.6%, has increased
slightly.
l Due to the emergence of 4G, the market
share of operators may change in the
future.

Mobile internet access
50.5
3G
Wi-Fi
44.7
49.5
55.3
Q1
Q2
Special occasions
affect the approach to
connect
l Compared with the last quarter, the
penetration of Wi-Fi increased, similar
to the end of last year. With the
influence of the holidays and recent
events, the penetration of 3G or Wi-Fi
changed slightly. (ex. Chinese New
Year & Sunflower Event result in more
often outdoor activities. So 3G was
more than Wifi in Q1)
l Along with growth of the video
demand, the Wi-Fi penetration
increased. Will see what happen after
the launch of 4G.
%

Weekday usage pattern
Wi-Fi
3G
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Use 3G during the day, Wi-Fi after 8PM
l 3G was adopted more often than Wi-Fi during the office and school hours. It
generally begins to increase at 7AM in the morning, reaches the peak at noon.
l Wi-Fi usage begins to increase after 8PM, 1 hour ahead compared to last quarter.
Generally reaches the peak at 10PM, showing that the online behavior is closely
related to the consumer's lifestyle.

Weekend usage pattern
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Usage at night increases, obviously begins to
increase after 9PM
l Mobile Internet usage begins to increase after 9pm. due to days off during the
weekends. No big difference between 3G and Wi-Fi usage during the day time.
l Usage of Wi-Fi is more than 3G in the evening. And both of them increased at
night, showing that people often sleep late during weekends.
Wi-Fi
3G

Mobile devices usage patterns
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
00
11
22
33
44
55
66
77
88
99
1100
1111
1122
1133
1144
1155
1166
1177
1188
1199
2200
2211
2222
222333
iPad usage at night is higher
l iPad usage begins to increase after 9PM and continue to 1AM of the next day,
showing that the tablet usage when users at home is higher.
l Compared with the Android systems, iPhone usage reached the peak around
7PM. Due to the smaller screen of iPhone, tablet usage increases from 6PM.
However, Android does not have this issue due to the larger screens.
Android iPhone iPad

Android most popular apps
Education
0.2%
Entertain
ment
35.4%
Finance
0.9%
Life
15.3%
News
3.1%
Social
4.6%
Tech
Travel 4.1%
7.2%
Videos
29.1%
Android users prefer to
use the entertainment
Apps
l Android users mostly use the
entertainment Apps covering 35.4%.
Followed by the audio, 29.1%. This
may be related to the bigger screen
of Android phone.
l 15.3% of Android users often use
food, lottery, bus, beauty makeup,
clothing and other life Apps.

iPhone most popular apps
Education
0.1%
Entertain
ment
28.7%
Finance
0.2%
Life
29.5%
News
Social 5.2%
8.1%
Tech
0.2%
Travel
0.8%
Videos
27.1%
iPhone users prefer to
use the life Apps
l iPhone users mostly use the life and
other Entertainment Apps, including
life, food, beauty makeup and clothing
Apps.
l Less users go for video Apps due to
the smaller screen size.

iPad most popular apps
Education
0.2%
Entertainm
ent
20.6%
Finance
0.2%
Life
5.0%
News
3.2%
Social
9.0%
Videos
61.3%
Tech
0.2%
Travel
0.4%
iPad users prefer to see
the videos
l More than 60% of iPad users
download video related Apps,
including Taiwanese, Korean, Mainland
and Japanese dramas. Followed by the
entertainment, games and other
Entertainment Apps.
l Unlike the mobile phone use behavior,
iPad users prefer to use video related
Apps compared with the iPhone and
Android.

Mobile traffic in Dragon Boat Festival
Dragon
Boat
Festival
5/22-5/27
5/29-6/3
Thu
Fri
Sat
Sun
Mon
Tue
Consecutive holidays brings traffic up
l As usual of consecutive holidays, mobile traffic goes up. The dragon boat
festival of this year has only three holidays, while comparing to the same
period of the week before, traffic grows 1.2 times.

Mobile traffic during metro attack
5/13-5/19
5/20-5/26
Metro
Attack
Tue Wed Thu Fri Sat Sun Mon
News affect mobile traffic
l By studying the mobile traffic around Banqiao and Nangang line, it is found
that the traffics is relatively smaller(-11%) than the week before. It may
implies that relatively fewer people take Metro and use mobile on Metro that
week than the week before.
(the mobile traffic around Banqiao and Nangang line)

Mobile traffic during FIFA
5/29-6/10　
6/29-7/2(Ro16), 7/5-7/6 (Ro8), 7/9-7/10 (Ro4)
6/29
6/30
7/1
7/2
7/5
7/6
7/9
7/10
FIFA inflates mobile traffic by 1.15 time
l Comparing the traffic of the week before, the mobile traffic during the World Cup has
significantly increased. Especially for the first day round of 16, users have higher
attention to the game. Moreover, for the games involving Argentina(7/2 & 7/6), the
same upward trend is observed. The games started earlier at 12AM shed some light to
the reason why and it also reflects that Taiwanese’s preference to Argentina and the
famous player Messi. The traffic grow in apps of video, social and news categories.
l While comparing to the traffic to rounds of 4, the traffic increase was minimal. The
reason can be the timing of the games which only started at 4AM and it logically
follows that users using mobile when watching the games is correct.

Mobile traffic of FIFA quarter final
6/8(日)
7/13(日) Brazil vs. Holland
0
1
2
3
4
5
6
7
8
9
10
11
12
Lower attention to quarter final
l By comparing the mobile traffic of the week before and that of quarter
quarter final, it shows users did not pay extraordinary attention to the
quarter final. The traffic is comparable to normal days.
Game
Starts

Mobile traffic of FIFA final
6/9(一)
7/14(一) Germany vs. Argentina
0
1
2
3
4
5
6
7
8
9
10
11
12
FIFA inflates 1.2 times in 3 hours
l Mobile traffic surges significantly during the 3 hours around the games and
reach 1.2 times to the traffic of normal days. The closer to the end of the
game, this higher the traffic, it shows users highly cared about the results.
The average traffic remains high until 6AM and back to normal

Video App User Analysis
Sponsored by

Mobile video, man VS women
34%
35%
16%
15%
31%
52%
4%
13%
Taiwanese
Korean
Japanese
Chinese
Men
Women
Source: iOS, UU, Q2 2014, Vpon & CHOCOLABS
Women fall for Korean
drama
l Most user watch the Korean drama
and women prefers the Korean drama
to 52%
l Taiwanese drama are popular
l Men prefers work related Japanese
drama series

Mobile video top 10
Rank
Drama
Men’ Top 10
1
KR
來自星星的你
2
KR
奇皇后
3
TW
世間情
4
TW
女人30情定水舞間
5
TW
我的自由年代
6
KR
繼承者們
7
CN
步步驚情
8
TW
愛上兩個我
9
TW
雨後驕陽
10
TW
廉政英雄
Rank
Drama
Women’ Top 10
1
KR
奇皇后
2
KR
來自星星的你
3
TW
世間情
4
TW
女人30情定水舞間
5
CN
步步驚情
6
KR
繼承者們
7
TW
我的自由年代
8
KR
百年新娘
9
TW
愛上兩個我
10
KR
急診男女

Mobile video, age defines
Taiwanese
Korean
Japanese
Chinese
Aged 13-17
Aged 18-24
Aged 25-34
Aged 35-44
Aged 45-54
Aged 35+ like Korean drama
l Aged 13-24 prefers to using mobile for Taiwanese and Korean drama.
l Aged 35+ watch Korean drama on mobile the most

Big Data Analysis and
Application

Vpon big data
Vpon has more than 380 million unique users, by collecting user behavior on advertisment,
we are handling more than 10TB data each month. With multi-dimensional data mining,
we find the specific prospective customers for advertisers. Vpon has not settled for
accurate targeting by optimization, sending the ad to the right audience. We lower the
cost and promote higher CTR at the same time and hence improve the effectiveness of
the mobile advertisement.
• Click Preference
• Mobile Device
• APP Category
• Ad Personality
• Timing
• Location
• Social Pattern
• Categories
• Grouping
• Recommendation
• Retargeting
• Audience
Targeting
• Personalize
Marketing
• Cross Media
Platform
Integrate to other
data base. ie.
Customer’s existing
CRM data base、
social fans page
(facebook fans)…
Collect User Pattern
information
Link to Advertiser
data base
Big Data Analysis
Optimize Targeting
Second-Party Data
First-Party Data

Successful case: optimized Ad
Click Through Rate
+3.6 times
TA reach
rate
81%
Target Reach
85%
TOTAL
Impression
- 5 times
Normal Optimized Normal Optimized
l Vpon leverages big data to assist
advertisers to preform dependence
analysis, through click pattern, we
can spot out the prospective
customers, such optimized CTR
outperforms the normal one 3.6
times.
l Using recommendation algorithm to
locate the target segment, it
effectively reduce excess impression
and lower advertising cost. In
optimized case, even the total
impression shrinks 5 times than
before, the actual reach to target
segment has only a tiny change.

CTR(Click Through Rate) +3.6 times
CVR(Conversion rate)
CVR
l Use of analytic algorithm allocates ads to
precise target customers, thought only a
minor lift on the CTR while Vpon achieves
to 3.6 times conversion rate.
+4.9 times
+1.8 times
l Through accumulation of data as time goes
by, Vpon will be able to perform continuous
optimization. After multiple algorithm
calculation, Vpon is able to achieve 4.9 time
conversion upon the first optimization and
another 1.8 times upon the second run.
Optimized conversion
Normal Optimized Normal Optimized Further Optimized

Big data critical 3R
Looking at big data at economic perspective, in classical theory, rich and richness is a
trade off to each other; while in nowadays digital times, with the advancement of
technology, it is possible that we can break through the compromise to create bigger
value for all. Regarding big data, apart from Reach and Richness, another critical
information of mobile data is Range which is the variety of mobile usage scenario.
Digital Economics
Reach High
High
Richness
Low
Classical-> Digital Economics
Big Data Economics
The power source of
behavioral forecasting
Reach
Richness
High
High
Low
Reach of unique users
Range
High
The customer affiliate of whole context
Classical Economics

Range affects the accuracy of big data
Cross use of multiple mobile device has become the trend, for every ad campaigns,
the effectiveness and achievement of itself is closely related to the interaction and
synchronization of other media.
TV campaign
Reach
View
Rating
Brand Awareness
Mobile Campaign
Request
Click
Impression
Conversions
Range
Offline Campaign
Reach
Traffic
Buzz
Actions
Reach
Richness

3R for best performance
16.00%
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
40000
35000
30000
25000
20000
15000
10000
5000
0
APP下載率
優化轉換率
App Download Rate Optimized Conversion Rate
TV Ad
Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun
Resonance of integrated media advertisement
l By studying the app download and conversion rate through big data optimization, we find
resonance of TV and mobile advertisement and effectively improve the ad performance
as a whole. By synchronizing the campaign and ad material, executing TV and mobile
campaign at the same time, the conversion rate of mobile advertisement is even better
than normal app download rate and it vividly depicts that in the time customers cross-use
of multiple mobile devices, the consideration of range becomes the critical factor.

Embrace big data
n Big Date is not just quantitative analysis
l Big data analyzes various external factors
l Consumers’s cross-use of multiple mobile devices affects the accuracy of
analysis
n Reach, Richness, Range
l Reach：Base of analysis, the larger the sample size, the more accurate the
analysis
l Richness：The richer the source information, the better we understand user
behavior and the higher precision of targeting.
l Range：The variety of usage context affect the accuracy of big data analysis
ü Total strategy of cross media: matching and integration
ü Synchronization of creatives
n Vitalize advertisers’ data base(i.e: member info) to
combine with big data analysis
l M-CRM
l Personalized Marketing
l Audience Targeting

About the report
All analytic data comes from Vpon Inc.
For the most updated reports, please go to
http://www.vpon.com/
Contact us
Website：http://www.vpon.com/
For publishers：bd@vpon.com
For advertisers: ad@vpon.com

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