Predictive Analytics Covering definitions, usage in a cross border travel context Examples of LBS and other tools to explain how it works

1. Making advertising more targeted, more relevant, more effective
Predictive Analytics
to Target Cross-Border Travelers

2. OUTLINE
Why cross border travelers
Explaining predictive analytics and
the relevance of different analytics
to a cross border marketing scenario
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

6. Accommodation
49%
Shopping
26%
Sightseeing,
Entertainment & Gaming
9%
Food and Beverage
16%
Source: Vpon Big Data Group

7. Explaining predictive analytics and
the relevance of different analytics
to a cross border marketing scenario

8. Low
High
High
Business Value
Complexity
Passive
Descriptive
Predictive
Prescriptive
What happened?
Why did
it happen?
What will
happen?
How to
make it
happen ?

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
2.Target travelers who have traveled to Singapore so that
they can share to their friends and families too

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
1.Target travelers who have been to OTHER locations to
suggest Singapore as next destination
2.Target travelers who have traveled to Singapore so that
they can share to their friends and families too
PrescriptivePassive

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

17. Mainland Chinese
Hongkongers
+35%
+13%
During the 3-day Labor
Day holiday, the volume of
international roaming
increased with the number
of oversea travelers.

18. 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%

19. 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

24. 陽明山
National Highway
MRT Routes
Yangmingshan

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. Leveraging the new world

29. 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

30. Thank You!
www.vpon.com