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Source: Trustdata Mobile Big Data Monitoring Platform Analysis Report on the Development of China’s Online Hotel Reservation Industry in the First Half of 2019 This report is produced by Trustdata. All the words, pictures and forms in the report are protected by regulations on intellectual property rights in Chinese laws. No organization or individual may use the information in this report for any other commercial purposes. August 2019

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Page 1: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

Analysis Report on the Development of China’s Online Hotel Reservation Industry

in the First Half of 2019

This report is produced by Trustdata. All the words, pictures and forms in the report are protected by regulations on intellectual property

rights in Chinese laws. No organization or individual may use the information in this report for any other commercial purposes.

August 2019

Page 2: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

Indicators:

• DAU--Daily Active Users

• MAU-- Monthly Active Users

• Monthly coverage -- the percentage of MAU of the app in the total number of mobile Internet users

• Monthly new -- newly added users per month

• Monthly retention rate -- the probability that a new user has used the app for 1 day or more in the following month

• TGI index -- user index/target group’s user feature index

Research Overview

• Object: Chinese mobile Internet users

• Data source: sample set of Android users built by Trustdata with a DAU of over 100 million (and an MAU of over 320 million), according to the

demographic structure and geographical distribution of Chinese mobile Internet users, as well as mobile app iOS

• Calculated by the model built based on various factors including the proportional relationship with Android

• Collection method: data are only collected when the screen is bright to ensure the authenticity and validity of data. Regarding frequency, every

10 seconds for apps without payment function, and every 1 second for apps with payment function

• Time: 2017-2019

Page 3: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

Contents

I. Current Development of Online Hotel Reservation Industry in China

II. User Research for Online Hotel Reservation Industry in China

IV. Trend Forecast for China’s Online Hotel Reservation Industry

III. Competition Landscape of China’s Online Hotel Reservation Industry

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Source: Trustdata Mobile Big Data Monitoring Platform

Current Development of Online Hotel Reservation Industry in China

1. China’s online hotel reservation market continues to grow, with huge potential

in online rate compared with developed markets such as Europe, US and Japan

3. China’s per capita GDP is expected to exceed $10,000 in 2019, accelerating the

increase of new tourists and boosting the demand for hotel reservations

4. In the first half of 2019, local orders have continued to increase, with Q2 orders

accounting for more than 30%

2. The accelerated expansion of supply side resources will lead to the number of

hotel rooms in China exceeding 20 million in 2019

Page 5: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

In the first half of 2019, the number of online hotel reservation users has continued to grow, reaching a scale of 100 million in Q2

11,238

0

3,000

6,000

9,000

12,000

2017 Q1 Q2 Q3 Q4 2018 Q1 Q2 Q3 Q4 2019 Q1 Q2

Online hotel reservation quarterly MAU 2017-2019 (unit: 10,000)

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Note: Trustdata mobile big data monitoring third-party reservation platforms (excluding hotel group’s official websites)

Page 6: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

365

100

180

260

340

420

2017 H1 2017 H2 2018 H1 2018 H2 2019 H1

Room nights reserved via online hotel reservation 2017-2019 H1 (unit: million)

In H1 of 2019, the number of room nights reserved via online hotel reservation increased by 20% year-on-year, reaching the scale of nearly 400 million

+20% YoY

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Source: Trustdata Mobile Big Data Monitoring Platform

0

500

1,000

1,500

2,000

2,500

2015 2016 2017 2018 2019E

Hotel room numbers in China from 2015 to 2019 (unit: 10,000 rooms)

The number of hotel rooms in China is increasing steadily, and will exceed 20 million in 2019

Note: the data on this page are compiled by Trustdata according to the public information of China Hospitality Association

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Page 8: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Japan 58.9%

Germany 55.5%US 47.4%

UK 46.5%

China 35.0%

Penetration rate of online hotels in major economies in 2018

Innovative users

2.5%

Early adopters

13.5%

Early mass users

34%

Late mass users

34%

Late users

16%

0

25%

100%

50%

75%

China’s online hotel reservation market continues to grow, with huge potential in the rise of online rate compared with developed markets such as Europe, US and Japan

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Note: Data of this page is from Euromonitor

Penetration

rate

Growth

rate

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3,468

5,618

8,033

10,000

0

2,000

4,000

6,000

8,000

10,000

2007 2011 2015 2019E

Annual growth of China’s per capita GDP (unit: USD)

China’s per capita GDP is expected to exceed $10,000 in 2019, accelerating the increase of new tourists and boosting the demand for hotel reservations

Note: data on this page refer to data from the National Bureau of Statistics

Mainly sightseeing tours

With the increase of per capita GDP and residents' consumption capacity, the types of tourism have

gradually increased and leisure travel appeared

When per capita GDP exceeds $5,000, long-distance leisure travel and outbound tourism will rise

When per capita GDP is closer to $10,000, ways of leisure travel are more diverse, and long-travel vacation and short-distance leisure travel will grow fast

The proportion of

leisure tourists

Growing number of “new tourists”

As China’s economic development is further accelerated, more provinces and municipalities have lifted their per capital GDP to over USD 10,000, attracting more and more new tourists.Tourists spend more on leisure and vacation, and book significantly increased number of hotel rooms during their personal or family trips.

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Early stage

Future

Page 10: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

72.7%

37.6%

27.5% 33.1%

72.5%66.9%

0%

20%

40%

60%

80%

100%

2018 Q1 Q2 Q3 Q4 2019 Q1 Q2

Analysis of quarterly proportion of online reservation of local and non-local hotels from 2018 to 2019

Local Non-local

In the first half of 2019, local orders have continued to grow, with Q2 orders accounting for more than 30%

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Source: Trustdata Mobile Big Data Monitoring Platform

User Research for Online Hotel Reservation Industry in China

1. The age composition of Chinese online hotel reservation users has

changed, with post-90s and post-00s becoming the main consumers

2. Online hotel reservation has continued to penetrate in county-level

markets, with "small town areas" registering multiple growth

3. Young users’ strong willingness to buy, diverse needs and multiple

scenarios for consumption drive the growth of online hotel reservation

4. Young users’ needs and scenarios for online hotel reservation are

becoming increasingly diversified and personalized

Page 12: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

Majority of new online hotel reservation users are small town youths, who have diversified needs and strong willingness to consume online

Younger users

Small town youths

Diversified demands

The number of young users born in the

1990s and 2000s has increased rapidly

The number of users in third-tier and lower-

tier cities has increased significantly

Strong willingness to consume online

The consumption scenarios for online hotel reservation of young users born in the 1990s and 2000s are diversified, covering travel, theme parties, star-chasing and travel list-completing

Young users born in the 1990s and 2000s have no pressure from buying houses & cars and raising kid(s), and they are more willing to consume based on personal interests and hobbies than other users

Unmarried

Love to have fun

Strong personality

Rich

Have a “friends circle”

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Source: Trustdata Mobile Big Data Monitoring Platform

In the first half of 2019, the share of male users was slightly more than female. Young users are increasing, with the share of post-90s exceeding post-80s for the first time.

The potential for the post-2000s is huge

52.7% 47.3%

Proportion of male and female users for online

hotel reservation in H1 2019

male female12% 37% 39% 7% 5%

11%

3%

-20%

-10%

0%

10%

20%

0%

9%

18%

27%

36%

45%

Post-70s Post-80s Post-90s Post-00s Others

Age composition of users and YoY changes in H1 2019

Proportion of age groups Year-on-year growth

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Source: Trustdata Mobile Big Data Monitoring Platform

Online hotel reservation has continued to penetrate in county-level markets in H1 of 2019, with 70% of new users from third and lower tier cities

70.0% 70.7%

January February March April May June

Distribution of new users in H1 2019

First-tier cities Second-tier cities Third-tier cities and below

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Source: Trustdata Mobile Big Data Monitoring Platform

Number of users in some cities in southwest, northwest and central China grew multiple times. “Tourism-resources-led consumption” + “economic-growth-driven consumption” are the dual

drivers of hotel order increase

24.0

5.0

3.5

1.7

5.0

3.5

2.2

1.6 1.6

4.3

2.9 2.7 2.92.5

1.8

SoutheastGuizhou

Dehong SouthwestGuizhou

Wenshan Linxia Jinchang Weinan Ankang Jinzhong Chizhou Huangshan Yiyang Jiaxing Zhangzhou Jiangmen

TOP15 cities for growth of users of online hotel reservation in H1 2019

Southwest Northwest Central China South China

In H1 2019, the TOP15 user growth areas were mainly in the southwest, northwest, Central China and part of South China. There are twomain factors promoting such growth. First, the strong promotion of tourism resources, such as Southeast Guizhou and Dehong in Southwest China. Second, economic development drove consumption growth. The increase of consumption of leisure tourism promoted the release of demand for online hotel reservation. Performance of Linxia, Jinchang, Chizhou, and Jiaxing is outstanding.

Note: In the chart, means regions driven by tourist resources, while means regions driven by economic growth

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Source: Trustdata Mobile Big Data Monitoring Platform

Young users born in the 1990s and 2000s have less pressure of parenting, mortgage and car expenses. They have strong willingness to spend online,

with higher demand for online hotel reservation

0

100

200

300

400

Overseas onlineshopping

Brand e-commerce

content payment leisure &entertainment

hotel reservation parenting car expenses housing mortgage

TGI index of online hotel reservation users for H1 2019 (by generations)

Post-70s Post-80s Post-90s Post-00s

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Source: Trustdata Mobile Big Data Monitoring Platform

Young users’ leisure and entertainment are rich and colorful. Multi-scene interaction drives the growth of demand for online hotel reservation

Self-drivingfor leisure

Theme parties &entertainment

Graduate/gap year travel

Travel list-completionFood & Consumption

Cartoon exhibition/lectures/music/star-chasing

Overseas study

Young users

Average number of APP starts in H1 2019 Monthly average number of reservations in H1 2019

7.1 times

1.5 times higher than other users

2.6 times

1.6 times higher than other users

Young users’ leisure and entertainment are rich and colorful

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Source: Trustdata Mobile Big Data Monitoring Platform

Competitive Landscape of China’s Online Hotel Reservation Industry

1. Competition in the industry continues to rise, and Meituan gains at higher speed

2. Meituan and Fliggy users are younger, with 50% post-90s and post-00s

3. User stickiness of mainstream platforms are above 20%, Ctrip has the best

performance of 24.3%

Page 19: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

50.6%

21.3%

10.3%

9.8%5.4%

2.6%

Proportion of orders of different platforms in the online hotel reservation industry in

China in H1 2019

Meituan Hotel Ctrip

Qunar Tongcheng-Elong

Fliggy Others

Meituan tops the online hotel reservation industry in H1 2019, gaining over 50% of orders in the industry

Note: data on this page are statistics of users in the Chinese mainland, excluding Hong Kong, Macao, Taiwan. Number of orders here refers

to number of paid orders.

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0

60

120

180

Meituan Hotel Ctrip Qunar Tongcheng-Elong Fliggy

Accumulated orders of online hotel reservation

platforms in China in H1 2019 (unit: million)

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Source: Trustdata Mobile Big Data Monitoring Platform

47.3%

23.9%

10.4%

10.3%

5.4%2.7%

Market share of China's platforms in terms of room nights reserved in H1 2019

Meituan Hotel Ctrip

Qunar Tongcheng-eLong

Fliggy Others

In H1 2019, Meituan led the industry in terms of room nights reserved, accounting for 47.3% of the market, more than the total share of Ctrip, Qunar and eLong combined

Note: data on this page are statistics of users in China’s mainland, excluding Hong Kong, Macao, Taiwan and overseas

0

50

100

150

200

Meituan Hotel Ctrip Qunar Tongcheng-Elong Fliggy

Ranking of China's platforms in terms of room nights reserved in H1 2019(unit: million)

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Source: Trustdata Mobile Big Data Monitoring Platform

0.88

1.04 1.02

1.12

0

0.4

0.8

1.2

0

30

60

90

2018 Q1 2018 Q2 2019 Q1 2019 Q2

Meituan’s room nights reserved (million)

Ctrip’s room nights reserved (million)

Meituan/Ctrip-related’s room nights reserved

Meituan’s room nights reserved increased rapidly, surpassing the Ctrip-related platforms in a steady manner

Note: Ctrip-related refers to OTA platforms such as Ctrip, Qunar, Tongcheng-Elong

Meituan vs. Ctrip-related OTA platforms regarding room nights reserved during 2018-2019

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Source: Trustdata Mobile Big Data Monitoring Platform

51.2%

17.3%

15.2%

11.3%

2.6%2.4%

Market share of platforms in terms of new users in H1 2019

Meituan Hotel Qunar Ctrip

Fliggy Tongcheng-Elong Others

In H1 2019, users of China's online reservation platforms have continued to grow, adding up to 5 million per month. Meituan accounts for half of the new user market, while Qunar and

Ctrip rank second and third

513.2

250

310

370

430

490

550

January February March April May June

Growth trend of new users for online reservation platforms in China in H1 2019 (unit: 10,000)

Spring

Festival

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Source: Trustdata Mobile Big Data Monitoring Platform

Meituan & Fliggy led the industry regarding number of young users, with post-90s and post-00s accounting for more than 50%

6.3%

6.8%

6.5%

6.9%

7.0%

38.0%

40.1%

41.0%

43.5%

44.3%

36.5%

38.7%

37.5%

34.0%

34.4%

14.8%

10.8%

11.2%

11.6%

10.6%

4.4%

3.6%

3.8%

4.0%

3.7%

Ctrip

Tongcheng-Elong

Qunar

Fliggy

MeituanHotel

Age composition of users of major platforms in H1 2019

post-00s post-90s post-80s post-70s Others

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Source: Trustdata Mobile Big Data Monitoring Platform

Ctrip ranked first in user stickiness, while Tongcheng-eLong and Meituan ranked second and third

24.3%

23.1%

22.0%

21.5%

20.4%

Ctrip Tongcheng-Elong Meituan Hotel Fliggy Qunar

User stickiness of mainstream platforms in H1 2019 (user stickiness = monthly DAU/MAU)

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Source: Trustdata Mobile Big Data Monitoring Platform

Qunar ranked first in terms of daily opens, followed by Tongcheng-eLong and Meituan

3.4 3.3

3.0

2.72.5

Qunar Tongcheng-Elong Meituan Hotel Ctrip Fliggy

Daily open times of platform users in H1 2019 (times)

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Source: Trustdata Mobile Big Data Monitoring Platform

Trend Forecast for China’s Online Hotel Reservation Industry

1. Online hotel reservation is deeply interlinked with scenarios of leisure

and entertainment, and gradually upgraded to one-stop consumption model

featured by diversification and high frequency

2. Super platforms with huge customer traffic drive the upgrade of competition which focuses more on integrated strength of players

3. OTA players around the world form a four-pole competitive landscape, and

leisure travel is the key area battled for

Page 27: Analysis Report on the Development of China’s Online Hotel …report.itrustdata.com/report/pdf/Report+of+China’s+Online+Hotel... · Analysis of quarterly proportion of online

Source: Trustdata Mobile Big Data Monitoring Platform

Deeply interlinked with life, leisure and entertainment scenes, online hotel reservation is gradually upgrading to the one-stop consumption model

Rise of young users

Young users growing up together with the mobile Internet are largely different from traditional users in terms of

consumption mindset, ways and demand. Under the scenario of tourism, young users are stronger than traditional ones

regarding frequency of local and non-local travels, and most of such travels, dominated by free travels, are with close friends

or freely formed groups. In addition to tourism, other scenarios such as leisure and entertainment, star-chasing, exhibition,

games and parties, also tap the potential of online hotel reservation.

Diversified and one-stop consumption

Chinese users are getting more diversified. From business travelers in early days to people with “business + leisure and

entertainment needs” today, the rapid change of user mix leads to the upgrading of consumption characteristics to one-

stop consumption. Super APP platforms integrating ecosystems such as online hotel reservation, travel, leisure and

entertainment are popular among users.

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Source: Trustdata Mobile Big Data Monitoring Platform

Key factors of tourist consumption: from “air ticket & hotel” to “food, hotel, travel, tourism, shopping & entertainment”

The changing user needs lead to changes in tourist consuming behaviors. With the rise of recreational vacation and users' growing consuming ability, “air ticket + hotel” are no longer the most critical factors in tourist consumption decisions. After determining the destination, people prefer more in-depth local travel experience integrating food, hotel, ticket to scenic spots, travel, shopping and entertainment.

Online travel reservation

Itinerary VisaAir

ticket

Local travel

Food

Hotel

Ticket to scenic spots

Entertainment

Integration of “food, hotel, travel, tourism, shopping &

entertainment”

“Air ticket + hotel”

Shopping

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Source: Trustdata Mobile Big Data Monitoring Platform

OTA players around the world form a four-pole competitive landscape, and leisure travel is the key area battled for

0.2

0.4

0.7

1.1

1.5

1.7

2.1

2.2

0.0

0.7

1.4

2.1

2.8

0

200

400

600

800

2004 2006 2008 2010 2012 2014 2016 2018

Booking Expedia Booking/Expedia

Both Booking and Expedia have been developing for more than 20 years. The former’s market is

mainly Europe, which is dominated by leisure demand and the supply of which is relatively scattered,

while the latter’s major market is the US, which focuses on business travel and boasts higher share

of chain hotels. In early days of competition, Expedia had obvious advantages over its rival. But in

2010, the room nights reserved of Booking exceeded Expedia, and then Booking developed rapidly,

widening the gap and maintaining the champion position.

Globally, Meituan and Ctrip have rapidly grown to form a four-pole pattern with Booking and

Expedia in terms of scale. Similar to Expedia, Ctrip has been developing for 20 years and focusing

on business travel. Meituan, though young, is similar to Booking in nature. Meituan mainly focuses

on the leisure and vacation market, and expands in regions with little chain hotels and with rapid

growth. At the same time, Meituan, as a comprehensive platform of life services, has access to

different ecosystems and is able to drive the growth of low-frequency scenarios with high-frequency

ones, forming its unique competitiveness

Note: the data are from Booking and Expedia’s financial reports.

Comparison of room nights reserved

between Booking and Expedia from

2004 to 2018

Independent hotel + leisure market

Chain hotel + business travel

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Source: Trustdata Mobile Big Data Monitoring Platform

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