Global Travel Metasearch Engine Market

Travel Metasearch Engine Comprehensive Study by Application (Transportation Booking, Hotel Booking, Others), End User (Corporate, Hotel, Event Organiser, Travel agency), Cost Model (Cost Per Click, Pay Per Click, Cost per Impression, Cost Per Action), Mode (Direct Booking, Indirect Booking) Players and Region - Global Market Outlook to 2027

Travel Metasearch Engine Market by XX Submarkets | Forecast Years 2023-2027  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
Travel Metasearch Engine Market Scope
Rising Internet penetration and smartphone, increasing investment in ads, and changing consumer lifestyle are the factors driving the market growth for the travel metasearch engine. Travel metasearch engine is a platform where the individual can aggregate list of available rooms, Flights, and their respective rates Travel businesses see metasearch as a platform to market their brands and bring direct or sales-qualified leads to their website. Therefore, it also works as an acquisition channel.

AttributesDetails
Study Period2017-2027
Base Year2022
UnitValue (USD Million)
Key Companies ProfiledGoogle Hotel Ads (United States), Trip Advisor (United States), Hotels Cobined (Australia), Trivago (Germany), Skyscanner (United Kingdom), Kayak (United States), Wego (Singapore), Home to go (Germany), Distribution Technologies (Germany) and Viajala (United States)
CAGR%


The market for the Travel Metasearch Engine is highly competitive and dominated by few key player such as Google, Trivago, and Trip advisor. The market has a vendor landscape that is extremely competitive. A number of businesses are also taking part in significant mergers and acquisitions as part of crucial plans to increase their market share globally. Research Analyst at AMA estimates that Germany Players will contribute to the maximum growth of Global Travel Metasearch Engine market throughout the predicted period.

Google Hotel Ads (United States), Trip Advisor (United States), Hotels Cobined (Australia), Trivago (Germany), Skyscanner (United Kingdom), Kayak (United States), Wego (Singapore), Home to go (Germany), Distribution Technologies (Germany) and Viajala (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research are Go Euro (Germany), Travex (Israel), Hotels Combined (Australia), Momondo (Denmark) and Vervotech (India).

About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from the total available market.

Segmentation Overview
The study have segmented the market of Global Travel Metasearch Engine market by Type , by Application (Transportation Booking, Hotel Booking and Others) and Region with country level break-up.

On the basis of geography, the market of Travel Metasearch Engine has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). region held largest market share in the year 2022.

Market Leaders and their expansionary development strategies
On September 2021, Rate gain Travel technologies a provider of SaaS solution for the travel and hospitality sector announced the acquisition of myhotelshop a Germany based company. The acquisition is aim to strengthen revenue maximisation and global presence. and On February 2022, Wego a Singapore base company provider of metasearch business in hotel and travel industry announced the acquisition of Cleartrip Middle East operation from the Flipkart Group. The acquisition is aim to strengthen and increase the global presence of the company.
On February 2022, Travel Unicorn Hopper selects RateGain for prime access to global hotel supply inventory and pricing intelligence data


Influencing Trend:
Technological advancement such as AI and Machine Learning is the key trend driving the market growth and Changing consumer lifestyle

Market Growth Drivers:
Rising mobile and smartphone penetration drives the market growth and Increasing internet penetration and 5g infrastructure in emerging economies supports the market growth

Challenges:
Lack of skilled workforce restrict the market growth

Restraints:
Privacy concern and rising cyber threat attacks hampers the market growth

Opportunities:
Increasing investment in ads will create lucrative growth opportunities for the market and Increasing digitalisation in the emerging economies

Key Target Audience
New Entrants and Investors, Hotels, Venture Capitalists, Government Bodies, Corporate Entities, Government and Private Research Organizations and Others

Report Objectives / Segmentation Covered

By Application
  • Transportation Booking
  • Hotel Booking
  • Others
By End User
  • Corporate
  • Hotel
  • Event Organiser
  • Travel agency

By Cost Model
  • Cost Per Click
  • Pay Per Click
  • Cost per Impression
  • Cost Per Action

By Mode
  • Direct Booking
  • Indirect Booking

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Rising mobile and smartphone penetration drives the market growth
      • 3.2.2. Increasing internet penetration and 5g infrastructure in emerging economies supports the market growth
    • 3.3. Market Challenges
      • 3.3.1. Lack of skilled workforce restrict the market growth
    • 3.4. Market Trends
      • 3.4.1. Technological advancement such as AI and Machine Learning is the key trend driving the market growth
      • 3.4.2. Changing consumer lifestyle
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Travel Metasearch Engine, by Application, End User , Cost Model , Mode and Region (value and price ) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global Travel Metasearch Engine (Value)
      • 5.2.1. Global Travel Metasearch Engine by: Application (Value)
        • 5.2.1.1. Transportation Booking
        • 5.2.1.2. Hotel Booking
        • 5.2.1.3. Others
      • 5.2.2. Global Travel Metasearch Engine Region
        • 5.2.2.1. South America
          • 5.2.2.1.1. Brazil
          • 5.2.2.1.2. Argentina
          • 5.2.2.1.3. Rest of South America
        • 5.2.2.2. Asia Pacific
          • 5.2.2.2.1. China
          • 5.2.2.2.2. Japan
          • 5.2.2.2.3. India
          • 5.2.2.2.4. South Korea
          • 5.2.2.2.5. Australia
          • 5.2.2.2.6. Rest of Asia-Pacific
        • 5.2.2.3. Europe
          • 5.2.2.3.1. Germany
          • 5.2.2.3.2. France
          • 5.2.2.3.3. Italy
          • 5.2.2.3.4. United Kingdom
          • 5.2.2.3.5. Netherlands
          • 5.2.2.3.6. Rest of Europe
        • 5.2.2.4. MEA
          • 5.2.2.4.1. Middle East
          • 5.2.2.4.2. Africa
        • 5.2.2.5. North America
          • 5.2.2.5.1. United States
          • 5.2.2.5.2. Canada
          • 5.2.2.5.3. Mexico
    • 5.3. Global Travel Metasearch Engine (Price)
  • 6. Travel Metasearch Engine: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Google Hotel Ads (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. Trip Advisor (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Hotels Cobined (Australia)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Trivago (Germany)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Skyscanner (United Kingdom)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Kayak (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Wego (Singapore)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Home to go (Germany)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Distribution Technologies (Germany)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Viajala (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
  • 7. Global Travel Metasearch Engine Sale, by Application, End User , Cost Model , Mode and Region (value and price ) (2022-2027)
    • 7.1. Introduction
    • 7.2. Global Travel Metasearch Engine (Value)
      • 7.2.1. Global Travel Metasearch Engine by: Application (Value)
        • 7.2.1.1. Transportation Booking
        • 7.2.1.2. Hotel Booking
        • 7.2.1.3. Others
      • 7.2.2. Global Travel Metasearch Engine Region
        • 7.2.2.1. South America
          • 7.2.2.1.1. Brazil
          • 7.2.2.1.2. Argentina
          • 7.2.2.1.3. Rest of South America
        • 7.2.2.2. Asia Pacific
          • 7.2.2.2.1. China
          • 7.2.2.2.2. Japan
          • 7.2.2.2.3. India
          • 7.2.2.2.4. South Korea
          • 7.2.2.2.5. Australia
          • 7.2.2.2.6. Rest of Asia-Pacific
        • 7.2.2.3. Europe
          • 7.2.2.3.1. Germany
          • 7.2.2.3.2. France
          • 7.2.2.3.3. Italy
          • 7.2.2.3.4. United Kingdom
          • 7.2.2.3.5. Netherlands
          • 7.2.2.3.6. Rest of Europe
        • 7.2.2.4. MEA
          • 7.2.2.4.1. Middle East
          • 7.2.2.4.2. Africa
        • 7.2.2.5. North America
          • 7.2.2.5.1. United States
          • 7.2.2.5.2. Canada
          • 7.2.2.5.3. Mexico
    • 7.3. Global Travel Metasearch Engine (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Travel Metasearch Engine: by Application(USD Million)
  • Table 2. Travel Metasearch Engine Transportation Booking , by Region USD Million (2017-2022)
  • Table 3. Travel Metasearch Engine Hotel Booking , by Region USD Million (2017-2022)
  • Table 4. Travel Metasearch Engine Others , by Region USD Million (2017-2022)
  • Table 5. South America Travel Metasearch Engine, by Country USD Million (2017-2022)
  • Table 6. South America Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 7. South America Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 8. South America Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 9. South America Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 10. Brazil Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 11. Brazil Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 12. Brazil Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 13. Brazil Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 14. Argentina Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 15. Argentina Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 16. Argentina Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 17. Argentina Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 18. Rest of South America Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 19. Rest of South America Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 20. Rest of South America Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 21. Rest of South America Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 22. Asia Pacific Travel Metasearch Engine, by Country USD Million (2017-2022)
  • Table 23. Asia Pacific Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 24. Asia Pacific Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 25. Asia Pacific Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 26. Asia Pacific Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 27. China Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 28. China Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 29. China Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 30. China Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 31. Japan Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 32. Japan Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 33. Japan Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 34. Japan Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 35. India Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 36. India Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 37. India Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 38. India Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 39. South Korea Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 40. South Korea Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 41. South Korea Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 42. South Korea Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 43. Australia Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 44. Australia Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 45. Australia Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 46. Australia Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 47. Rest of Asia-Pacific Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 48. Rest of Asia-Pacific Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 49. Rest of Asia-Pacific Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 50. Rest of Asia-Pacific Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 51. Europe Travel Metasearch Engine, by Country USD Million (2017-2022)
  • Table 52. Europe Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 53. Europe Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 54. Europe Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 55. Europe Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 56. Germany Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 57. Germany Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 58. Germany Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 59. Germany Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 60. France Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 61. France Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 62. France Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 63. France Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 64. Italy Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 65. Italy Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 66. Italy Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 67. Italy Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 68. United Kingdom Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 69. United Kingdom Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 70. United Kingdom Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 71. United Kingdom Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 72. Netherlands Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 73. Netherlands Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 74. Netherlands Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 75. Netherlands Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 76. Rest of Europe Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 77. Rest of Europe Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 78. Rest of Europe Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 79. Rest of Europe Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 80. MEA Travel Metasearch Engine, by Country USD Million (2017-2022)
  • Table 81. MEA Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 82. MEA Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 83. MEA Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 84. MEA Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 85. Middle East Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 86. Middle East Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 87. Middle East Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 88. Middle East Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 89. Africa Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 90. Africa Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 91. Africa Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 92. Africa Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 93. North America Travel Metasearch Engine, by Country USD Million (2017-2022)
  • Table 94. North America Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 95. North America Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 96. North America Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 97. North America Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 98. United States Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 99. United States Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 100. United States Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 101. United States Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 102. Canada Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 103. Canada Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 104. Canada Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 105. Canada Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 106. Mexico Travel Metasearch Engine, by Application USD Million (2017-2022)
  • Table 107. Mexico Travel Metasearch Engine, by End User USD Million (2017-2022)
  • Table 108. Mexico Travel Metasearch Engine, by Cost Model USD Million (2017-2022)
  • Table 109. Mexico Travel Metasearch Engine, by Mode USD Million (2017-2022)
  • Table 110. Company Basic Information, Sales Area and Its Competitors
  • Table 111. Company Basic Information, Sales Area and Its Competitors
  • Table 112. Company Basic Information, Sales Area and Its Competitors
  • Table 113. Company Basic Information, Sales Area and Its Competitors
  • Table 114. Company Basic Information, Sales Area and Its Competitors
  • Table 115. Company Basic Information, Sales Area and Its Competitors
  • Table 116. Company Basic Information, Sales Area and Its Competitors
  • Table 117. Company Basic Information, Sales Area and Its Competitors
  • Table 118. Company Basic Information, Sales Area and Its Competitors
  • Table 119. Company Basic Information, Sales Area and Its Competitors
  • Table 120. Travel Metasearch Engine: by Application(USD Million)
  • Table 121. Travel Metasearch Engine Transportation Booking , by Region USD Million (2022-2027)
  • Table 122. Travel Metasearch Engine Hotel Booking , by Region USD Million (2022-2027)
  • Table 123. Travel Metasearch Engine Others , by Region USD Million (2022-2027)
  • Table 124. South America Travel Metasearch Engine, by Country USD Million (2022-2027)
  • Table 125. South America Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 126. South America Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 127. South America Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 128. South America Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 129. Brazil Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 130. Brazil Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 131. Brazil Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 132. Brazil Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 133. Argentina Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 134. Argentina Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 135. Argentina Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 136. Argentina Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 137. Rest of South America Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 138. Rest of South America Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 139. Rest of South America Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 140. Rest of South America Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 141. Asia Pacific Travel Metasearch Engine, by Country USD Million (2022-2027)
  • Table 142. Asia Pacific Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 143. Asia Pacific Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 144. Asia Pacific Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 145. Asia Pacific Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 146. China Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 147. China Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 148. China Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 149. China Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 150. Japan Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 151. Japan Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 152. Japan Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 153. Japan Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 154. India Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 155. India Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 156. India Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 157. India Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 158. South Korea Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 159. South Korea Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 160. South Korea Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 161. South Korea Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 162. Australia Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 163. Australia Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 164. Australia Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 165. Australia Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 166. Rest of Asia-Pacific Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 167. Rest of Asia-Pacific Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 168. Rest of Asia-Pacific Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 169. Rest of Asia-Pacific Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 170. Europe Travel Metasearch Engine, by Country USD Million (2022-2027)
  • Table 171. Europe Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 172. Europe Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 173. Europe Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 174. Europe Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 175. Germany Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 176. Germany Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 177. Germany Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 178. Germany Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 179. France Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 180. France Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 181. France Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 182. France Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 183. Italy Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 184. Italy Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 185. Italy Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 186. Italy Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 187. United Kingdom Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 188. United Kingdom Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 189. United Kingdom Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 190. United Kingdom Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 191. Netherlands Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 192. Netherlands Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 193. Netherlands Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 194. Netherlands Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 195. Rest of Europe Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 196. Rest of Europe Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 197. Rest of Europe Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 198. Rest of Europe Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 199. MEA Travel Metasearch Engine, by Country USD Million (2022-2027)
  • Table 200. MEA Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 201. MEA Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 202. MEA Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 203. MEA Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 204. Middle East Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 205. Middle East Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 206. Middle East Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 207. Middle East Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 208. Africa Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 209. Africa Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 210. Africa Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 211. Africa Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 212. North America Travel Metasearch Engine, by Country USD Million (2022-2027)
  • Table 213. North America Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 214. North America Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 215. North America Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 216. North America Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 217. United States Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 218. United States Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 219. United States Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 220. United States Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 221. Canada Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 222. Canada Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 223. Canada Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 224. Canada Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 225. Mexico Travel Metasearch Engine, by Application USD Million (2022-2027)
  • Table 226. Mexico Travel Metasearch Engine, by End User USD Million (2022-2027)
  • Table 227. Mexico Travel Metasearch Engine, by Cost Model USD Million (2022-2027)
  • Table 228. Mexico Travel Metasearch Engine, by Mode USD Million (2022-2027)
  • Table 229. Research Programs/Design for This Report
  • Table 230. Key Data Information from Secondary Sources
  • Table 231. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Travel Metasearch Engine: by Application USD Million (2017-2022)
  • Figure 5. South America Travel Metasearch Engine Share (%), by Country
  • Figure 6. Asia Pacific Travel Metasearch Engine Share (%), by Country
  • Figure 7. Europe Travel Metasearch Engine Share (%), by Country
  • Figure 8. MEA Travel Metasearch Engine Share (%), by Country
  • Figure 9. North America Travel Metasearch Engine Share (%), by Country
  • Figure 10. Global Travel Metasearch Engine share by Players 2022 (%)
  • Figure 11. Global Travel Metasearch Engine share by Players (Top 3) 2022(%)
  • Figure 12. Global Travel Metasearch Engine share by Players (Top 5) 2022(%)
  • Figure 13. BCG Matrix for key Companies
  • Figure 14. Google Hotel Ads (United States) Revenue, Net Income and Gross profit
  • Figure 15. Google Hotel Ads (United States) Revenue: by Geography 2022
  • Figure 16. Trip Advisor (United States) Revenue, Net Income and Gross profit
  • Figure 17. Trip Advisor (United States) Revenue: by Geography 2022
  • Figure 18. Hotels Cobined (Australia) Revenue, Net Income and Gross profit
  • Figure 19. Hotels Cobined (Australia) Revenue: by Geography 2022
  • Figure 20. Trivago (Germany) Revenue, Net Income and Gross profit
  • Figure 21. Trivago (Germany) Revenue: by Geography 2022
  • Figure 22. Skyscanner (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 23. Skyscanner (United Kingdom) Revenue: by Geography 2022
  • Figure 24. Kayak (United States) Revenue, Net Income and Gross profit
  • Figure 25. Kayak (United States) Revenue: by Geography 2022
  • Figure 26. Wego (Singapore) Revenue, Net Income and Gross profit
  • Figure 27. Wego (Singapore) Revenue: by Geography 2022
  • Figure 28. Home to go (Germany) Revenue, Net Income and Gross profit
  • Figure 29. Home to go (Germany) Revenue: by Geography 2022
  • Figure 30. Distribution Technologies (Germany) Revenue, Net Income and Gross profit
  • Figure 31. Distribution Technologies (Germany) Revenue: by Geography 2022
  • Figure 32. Viajala (United States) Revenue, Net Income and Gross profit
  • Figure 33. Viajala (United States) Revenue: by Geography 2022
  • Figure 34. Global Travel Metasearch Engine: by Application USD Million (2022-2027)
  • Figure 35. South America Travel Metasearch Engine Share (%), by Country
  • Figure 36. Asia Pacific Travel Metasearch Engine Share (%), by Country
  • Figure 37. Europe Travel Metasearch Engine Share (%), by Country
  • Figure 38. MEA Travel Metasearch Engine Share (%), by Country
  • Figure 39. North America Travel Metasearch Engine Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Google Hotel Ads (United States)
  • Trip Advisor (United States)
  • Hotels Cobined (Australia)
  • Trivago (Germany)
  • Skyscanner (United Kingdom)
  • Kayak (United States)
  • Wego (Singapore)
  • Home to go (Germany)
  • Distribution Technologies (Germany)
  • Viajala (United States)
Additional players considered in the study are as follows:
Go Euro (Germany) , Travex (Israel) , Hotels Combined (Australia) , Momondo (Denmark) , Vervotech (India)
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Key Highlights of Report


Sep 2022 239 Pages 53 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Global Travel Metasearch Engine Market Quantitative research analysis
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Frequently Asked Questions (FAQ):

The key segments that are playing vital role in Travel Metasearch Engine Market are by end use application [Transportation Booking, Hotel Booking and Others].
The Travel Metasearch Engine Market is gaining popularity and expected to see strong valuation by 2027.
  • Rising mobile and smartphone penetration drives the market growth
  • Increasing internet penetration and 5g infrastructure in emerging economies supports the market growth

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