predictive analytics & cross border marketing
TRANSCRIPT
Making advertising more targeted, more relevant, more effective
Predictive Analytics to Target Cross-Border Travelers
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 dataand technology
02
0304
Why cross border travelers
Chinese Overseas Travellers
According to China Tourism Research Institute, China had 61.9 million outbound visitors in the first half of 2015an 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.
Traveller Arrivals by Countries
Indon
esia
China
Malays
iaInd
iaJa
pan
Philipp
ines
Hong K
ong S
AR
South
Korea
Thaila
nd
Vietna
m
Taiwan
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
Chinese Travelers contributing 15% of total Tourism Receipts, with 49% spent on Shopping
Explaining predictive analytics and
the relevance of different analytics
to a cross border marketing scenario
Traveller Arrivals by Countries
Valu
e
InnovationLow
High
High
Business Value
Com
plex
ity
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
Prescriptive Predictive DescriptivePassive
Target travelers based on the travel related apps on theirphone 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 destination2.Target travelers who have traveled to Singapore so that they can share to their friends and families too
Pre-trip reach
In-trip reach
Post-trip reach
Target travelers based on the travel related apps on theirphone 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 destination2.Target travelers who have traveled to Singapore so that they can share to their friends and families too
Prescriptive Predictive DescriptivePassive
Pre-trip reach
In-trip reach
Post-trip reach
Target travelers based on the travel related apps on theirphone 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 product2.Target travelers who have traveled (to Singapore / on an airline / hotel) so that they can share to their friends and families
Prescriptive Predictive DescriptivePassive
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.
Identifying relevant, high reach segments
High CTR
High Impression
All Segment Performanceon Finance campaign
LBS for Descriptive & Predictive Analytics
Mainland Chinese
Hongkongers
+35%
+13%
During the 3-day Labor Day holiday, the volume of international roaming increased with the number of oversea travelers.
Where do they come from ?
28%
20%16%
11%
10%
5%
3% 3% 3%
Taipei New Taipei CityTaichuang KaohsiungTaoyuan TainanHsinchu Pingtung
Where do they go ?
> 20 %
< 2%
2%~5%
5%~10%
10%~20%
1. Yilan City2. Zhushan
Township3. Fengshan District4. Zuoying Distric5. Puli Township6. Pingtung City7. Xingying District8. Dongshan
Township9. Annan District10.Budai Township11.Shuishang
Township12.Hengchun
Township13.Qianzhen District14.Toucheng
Township15.Qingshui District
Tracking Travel over CNY
Where do people go ?
Where do people go ?
And where do they stop moving ?
And where do they stop moving ?
陽明山
National Highway
MRT Routes
Yangmingshan
Tracking traveler movement along MRT routes
Not just a marketing gimmick
What comes after the data?
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
Xaxis Chairman on DCO and it’s magical powers
Leveraging the new world
AB
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
Unlocking the possibilitiesfor your business
Thank You!
www.vpon.com