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Making advertising more targeted, more relevant, more effective
Predictive Analytics
to Target Cross-Border Travelers
OUTLINE
Why cross border travelers
Predictive analytics and
cross-border marketing
Leveraging the new world
01
The possibilities created by data
and technology
02
03
04
Why cross border travelers
According to China Tourism Research Institute,
China had 61.9 million
outbound visitors
in the first half of 2015
an increase of 12.1% compared with the same period in
2014.. Additionally, Boston Consulting Group (BCG)
estimates that by 2030, tourists from China will make up
about 40% of outbound Asian travelers, taking 1.7 billion
trips annually, up from 500 million trips taken in 2012, the
latest year of which data were available .They travel
internationally for leisure (92%) vs 56% Business (CITM
2015), and in H1 2015 64% of those travelers were women.
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
Number of Arrivals by Country in Singapore
from January 2015 – October 2015
Source: Vpon Big Data Group
Accommodation
49%
Shopping
26%
Sightseeing,
Entertainment & Gaming
9%
Food and Beverage
16%
Source: Vpon Big Data Group
Predictive analytics and
cross-border marketing
Low
High
High
Business Value
Complexity
Passive
Descriptive
Predictive
Prescriptive
What happened?
Why did
it happen?
What will
happen?
How to
make it
happen ?
Pre-trip reach
In-trip reach
Post-trip reach
PrescriptiveDescriptivePassive
Target travelers based on the travel related apps on their
phone BEFORE they plan a trip
Target travelers while in Singapore to get them to visit
Specific attractions / retail
1. Target travelers who have been to OTHER locations to suggest
(Singapore) as next destination / market travel product
2. Target travelers who have traveled (to Singapore / on an airline
/ hotel) so that they can share to their friends and families
Pre-trip reach
In-trip reach
Post-trip reach
Target travelers based on the travel related apps on their
phone BEFORE they plan a trip
Target travelers while in destination to get them to visit
specific attractions / retail
PrescriptivePassive
1. Target travelers who have been to OTHER locations to suggest
(Singapore) as next destination / market travel product
2. Target travelers who have traveled (to Singapore / on an airline
/ hotel) so that they can share to their friends and families
Pre-trip reach
In-trip reach
Post-trip reach
Target travelers based on the travel related apps on their
phone BEFORE they plan a trip
Target travelers while in Singapore to get them to visit
Specific attractions / retail
1. Target travelers who have been to OTHER locations to suggest
(Singapore) as next destination / market travel product
2. Target travelers who have traveled (to Singapore / on an airline
/ hotel) so that they can share to their friends and families
PrescriptiveDescriptivePassive
The possibilities created by
data and technology
Researching segments, understanding
responses, optimizing target audiences
• Device ID
• Brand
• Size
• Time
• Location
• GPS
• IP
• Ad Click …
• SDK
• Data
Partnership
• First-hand
Resource
Data Sources Data Analytics Segment
During the 3-day Labor
Day holiday, the volume of
international roaming
increased with the number
of oversea travelers.
High CTR
High Impression
All segment
performance
on Finance
campaign
Pre-trip reach
PrescriptivePredictiveDescriptivePassive
Target travelers based on the travel related apps on their
phone BEFORE they plan a trip
In-trip reach
Target travelers while in destination to get them to visit
specific attractions / retail
Post-trip reach
1. Target travelers who have been to OTHER locations to suggest
(Singapore) as next destination / market travel product
2. Target travelers who have traveled (to Singapore / on an airline
/ hotel) so that they can share to their friends and families
Mainland Chinese
Hongkongers
+35%
+13%
During the 3-day Labor
Day holiday, the volume of
international roaming
increased with the number
of oversea travelers.
28%
20%
17%
11%
10%
5%
3% 3% 3%
Taipei New Taipei City
Taichuang Kaohsiung
Taoyuan Tainan
Hsinchu Pingtung
> 20 %
< 2%
2%~5%
5%~10%
10%~20%
1. Yilan City
2. Zhushan Township
3. Fengshan District
4. Zuoying Distric
5. Puli Township
6. Pingtung City
7. Xingying District
8. Dongshan Township
9. Annan District
10. Budai Township
11. Shuishang Township
12. Hengchun Township
13. Qianzhen District
14. Toucheng Township
15. Qingshui District
GPS
Cell Tower
IP
Sept Oct
Bidding engine uses past data to segment, experiments
with ad variants
Learns from each iteration to further refine segments and
ad variants that produce results
Constantly optimizes effectiveness by extending this
knowledge to additional members of each segment and
further refining the data over time
Understanding the consumer journey is key
Data helps to segment and find high potential scenarios,
then make predictions on likely high response audiences
and scenarios
Making messaging relevant and specific drives response
Leveraging the new world
A
B
C
• Define your consumer segments and important characteristics
• In what situations are they most likely to be responsive?
• What kinds of data can help to focus on your segment and identify the
specific scenarios in which they’re most receptive?
• What do you really need consumers to do?
• Is there a way to make this an online / phone based activity so it flows easier?
• If it’s offline how can you connect the consumer outcome to your advertising input?
• What kind of messaging is most appropriate for each segment?
• How can we refine the message to make it even more relevant in different
scenarios – what elements work with DCO?
Segments, Scenarios
KPI / Outcome
Creative matching
www.vpon.com
sales.global@vpon.comAdvertisers
Publishers bd.global@vpon.com
Contact Us
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Unlocking the revenue opportunity from cross-border travelers - presented by Vpon

  • 1. Making advertising more targeted, more relevant, more effective Predictive Analytics to Target Cross-Border Travelers
  • 2. OUTLINE Why cross border travelers Predictive analytics and cross-border marketing Leveraging the new world 01 The possibilities created by data and technology 02 03 04
  • 3. Why cross border travelers
  • 4. According to China Tourism Research Institute, China had 61.9 million outbound visitors in the first half of 2015 an increase of 12.1% compared with the same period in 2014.. Additionally, Boston Consulting Group (BCG) estimates that by 2030, tourists from China will make up about 40% of outbound Asian travelers, taking 1.7 billion trips annually, up from 500 million trips taken in 2012, the latest year of which data were available .They travel internationally for leisure (92%) vs 56% Business (CITM 2015), and in H1 2015 64% of those travelers were women.
  • 5. 0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 Number of Arrivals by Country in Singapore from January 2015 – October 2015 Source: Vpon Big Data Group
  • 9. Pre-trip reach In-trip reach Post-trip reach PrescriptiveDescriptivePassive Target travelers based on the travel related apps on their phone BEFORE they plan a trip Target travelers while in Singapore to get them to visit Specific attractions / retail 1. Target travelers who have been to OTHER locations to suggest (Singapore) as next destination / market travel product 2. Target travelers who have traveled (to Singapore / on an airline / hotel) so that they can share to their friends and families
  • 10. Pre-trip reach In-trip reach Post-trip reach Target travelers based on the travel related apps on their phone BEFORE they plan a trip Target travelers while in destination to get them to visit specific attractions / retail PrescriptivePassive 1. Target travelers who have been to OTHER locations to suggest (Singapore) as next destination / market travel product 2. Target travelers who have traveled (to Singapore / on an airline / hotel) so that they can share to their friends and families
  • 11. Pre-trip reach In-trip reach Post-trip reach Target travelers based on the travel related apps on their phone BEFORE they plan a trip Target travelers while in Singapore to get them to visit Specific attractions / retail 1. Target travelers who have been to OTHER locations to suggest (Singapore) as next destination / market travel product 2. Target travelers who have traveled (to Singapore / on an airline / hotel) so that they can share to their friends and families PrescriptiveDescriptivePassive
  • 12. The possibilities created by data and technology
  • 13. Researching segments, understanding responses, optimizing target audiences • Device ID • Brand • Size • Time • Location • GPS • IP • Ad Click … • SDK • Data Partnership • First-hand Resource Data Sources Data Analytics Segment
  • 14. During the 3-day Labor Day holiday, the volume of international roaming increased with the number of oversea travelers.
  • 15. High CTR High Impression All segment performance on Finance campaign
  • 16. Pre-trip reach PrescriptivePredictiveDescriptivePassive Target travelers based on the travel related apps on their phone BEFORE they plan a trip In-trip reach Target travelers while in destination to get them to visit specific attractions / retail Post-trip reach 1. Target travelers who have been to OTHER locations to suggest (Singapore) as next destination / market travel product 2. Target travelers who have traveled (to Singapore / on an airline / hotel) so that they can share to their friends and families
  • 17.
  • 18. Mainland Chinese Hongkongers +35% +13% During the 3-day Labor Day holiday, the volume of international roaming increased with the number of oversea travelers.
  • 19. 28% 20% 17% 11% 10% 5% 3% 3% 3% Taipei New Taipei City Taichuang Kaohsiung Taoyuan Tainan Hsinchu Pingtung > 20 % < 2% 2%~5% 5%~10% 10%~20%
  • 20. 1. Yilan City 2. Zhushan Township 3. Fengshan District 4. Zuoying Distric 5. Puli Township 6. Pingtung City 7. Xingying District 8. Dongshan Township 9. Annan District 10. Budai Township 11. Shuishang Township 12. Hengchun Township 13. Qianzhen District 14. Toucheng Township 15. Qingshui District
  • 21.
  • 23.
  • 24.
  • 25. Bidding engine uses past data to segment, experiments with ad variants Learns from each iteration to further refine segments and ad variants that produce results Constantly optimizes effectiveness by extending this knowledge to additional members of each segment and further refining the data over time
  • 26. Understanding the consumer journey is key Data helps to segment and find high potential scenarios, then make predictions on likely high response audiences and scenarios Making messaging relevant and specific drives response
  • 28. A B C • Define your consumer segments and important characteristics • In what situations are they most likely to be responsive? • What kinds of data can help to focus on your segment and identify the specific scenarios in which they’re most receptive? • What do you really need consumers to do? • Is there a way to make this an online / phone based activity so it flows easier? • If it’s offline how can you connect the consumer outcome to your advertising input? • What kind of messaging is most appropriate for each segment? • How can we refine the message to make it even more relevant in different scenarios – what elements work with DCO? Segments, Scenarios KPI / Outcome Creative matching