Global Web Content Filtering

Web Content Filtering Comprehensive Study by Type (Client-Side Filters, Content Limited ISPs, Server-Side Filters, Search-Engine Filters), Application (Business Organizations, Schools and Institutions, Federal and Government Agencies, Others) Players and Region - Global Market Outlook to 2026

Web Content Filtering Market by XX Submarkets | Forecast Years 2022-2027  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
What is Web Content Filtering Market?

Web content filtering is a technique that blocks and screens access to inappropriate or unsafe web content that may be deemed offensive, inappropriate, or even dangerous. Web content filtering is primarily used by corporations as part of their firewalls, and also by home computer owners. It helps to keep employees from visiting known spam sites or school systems restricting students from adult content. Web content filters come as either software or hardware and are often part of the firewall. It has multiple benefits for both individual users and organizations such as reduced malware infections, protection against exploit kits, increased staff productivity, network bandwidth efficiency, reduce inappropriate content and minimizes company liability.

The market study is being classified by Type (Client-Side Filters, Content Limited ISPs, Server-Side Filters and Search-Engine Filters), by Application (Business Organizations, Schools and Institutions, Federal and Government Agencies and Others) and major geographies with country level break-up.

Fortinet (United States), Trend Micro (United States), Cisco (United States), Symantec (United States), McAfee (United States), Palo Alto Networks (United States), Zscaler (United States), Trustwave (United States), Forcepoint (United States), Sophos (United Kingdom), Barracuda Networks (United States), iboss (United States), Webroot (United States), Interoute (United Kingdom), TitanHQ (Ireland), Virtela (United States), Netskope (United States), CensorNet (United Kingdom), Clearswift (United Kingdom) and Wavecrest (United States) are some of the key players profiled in the study. Additionally, the Players which are also part of the research are Cyren (United States), GFI Software (Malta), Untangle (United States), ContentKeeper (Australia) and Kaspersky (Russia).

The companies are exploring the market by adopting expansions, investments, new service launches and collaborations as their preferred strategies. The players are exploring new geographies through expansions and acquisitions across the globe to gain a competitive advantage through combined collaborations. Research Analyst at AMA predicts that United States Players will contribute to the maximum growth of Global Web Content Filtering market throughout the predicted period.

Segment Analysis
Analyst at AMA have segmented the market study of Global Web Content Filtering market by Type, Application and Region.

On the basis of geography, the market of Web Content Filtering has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, 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). Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.

Market Drivers
  • Increased Internet Virus and Malicious Internet Activity
  • High Benefits Web Content Filtering Installation such as Improved Productivity, Increased Bandwidth Efficiency and Minimized Company Liability

Market Trend
  • Rise in the Web-based Applications

Restraints
  • High Installation Cost

Opportunities
  • High Demand for Next-Generation Web Filtering Solutions
  • Increased Adoption of Cloud-based Solutions

Challenges
  • Lack of Technical Capabilities and Skills in Handling Complex and Dynamic Environments





Key Target Audience
Web Content Filtering Solution Providers, Emerging Companies, Research Professionals and End-users

Report Objectives / Segmentation Covered

By Type
  • Client-Side Filters
  • Content Limited ISPs
  • Server-Side Filters
  • Search-Engine Filters
By Application
  • Business Organizations
  • Schools and Institutions
  • Federal and Government Agencies
  • Others
By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • 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. Increased Internet Virus and Malicious Internet Activity
      • 3.2.2. High Benefits Web Content Filtering Installation such as Improved Productivity, Increased Bandwidth Efficiency and Minimized Company Liability
    • 3.3. Market Challenges
      • 3.3.1. Lack of Technical Capabilities and Skills in Handling Complex and Dynamic Environments
    • 3.4. Market Trends
      • 3.4.1. Rise in the Web-based Applications
  • 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 Web Content Filtering, by Type, Application and Region (value) (2015-2020)
    • 5.1. Introduction
    • 5.2. Global Web Content Filtering (Value)
      • 5.2.1. Global Web Content Filtering by: Type (Value)
        • 5.2.1.1. Client-Side Filters
        • 5.2.1.2. Content Limited ISPs
        • 5.2.1.3. Server-Side Filters
        • 5.2.1.4. Search-Engine Filters
      • 5.2.2. Global Web Content Filtering by: Application (Value)
        • 5.2.2.1. Business Organizations
        • 5.2.2.2. Schools and Institutions
        • 5.2.2.3. Federal and Government Agencies
        • 5.2.2.4. Others
      • 5.2.3. Global Web Content Filtering Region
        • 5.2.3.1. South America
          • 5.2.3.1.1. Brazil
          • 5.2.3.1.2. Argentina
          • 5.2.3.1.3. Rest of South America
        • 5.2.3.2. Asia Pacific
          • 5.2.3.2.1. China
          • 5.2.3.2.2. Japan
          • 5.2.3.2.3. India
          • 5.2.3.2.4. South Korea
          • 5.2.3.2.5. Taiwan
          • 5.2.3.2.6. Australia
          • 5.2.3.2.7. Rest of Asia-Pacific
        • 5.2.3.3. Europe
          • 5.2.3.3.1. Germany
          • 5.2.3.3.2. France
          • 5.2.3.3.3. Italy
          • 5.2.3.3.4. United Kingdom
          • 5.2.3.3.5. Netherlands
          • 5.2.3.3.6. Rest of Europe
        • 5.2.3.4. MEA
          • 5.2.3.4.1. Middle East
          • 5.2.3.4.2. Africa
        • 5.2.3.5. North America
          • 5.2.3.5.1. United States
          • 5.2.3.5.2. Canada
          • 5.2.3.5.3. Mexico
  • 6. Web Content Filtering: 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 (2020)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Fortinet (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. Trend Micro (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. Cisco (United States)
        • 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. Symantec (United States)
        • 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. McAfee (United States)
        • 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. Palo Alto Networks (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. Zscaler (United States)
        • 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. Trustwave (United States)
        • 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. Forcepoint (United States)
        • 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. Sophos (United Kingdom)
        • 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
      • 6.4.11. Barracuda Networks (United States)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Iboss (United States)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
      • 6.4.13. Webroot (United States)
        • 6.4.13.1. Business Overview
        • 6.4.13.2. Products/Services Offerings
        • 6.4.13.3. Financial Analysis
        • 6.4.13.4. SWOT Analysis
      • 6.4.14. Interoute (United Kingdom)
        • 6.4.14.1. Business Overview
        • 6.4.14.2. Products/Services Offerings
        • 6.4.14.3. Financial Analysis
        • 6.4.14.4. SWOT Analysis
      • 6.4.15. TitanHQ (Ireland)
        • 6.4.15.1. Business Overview
        • 6.4.15.2. Products/Services Offerings
        • 6.4.15.3. Financial Analysis
        • 6.4.15.4. SWOT Analysis
      • 6.4.16. Virtela (United States)
        • 6.4.16.1. Business Overview
        • 6.4.16.2. Products/Services Offerings
        • 6.4.16.3. Financial Analysis
        • 6.4.16.4. SWOT Analysis
      • 6.4.17. Netskope (United States)
        • 6.4.17.1. Business Overview
        • 6.4.17.2. Products/Services Offerings
        • 6.4.17.3. Financial Analysis
        • 6.4.17.4. SWOT Analysis
      • 6.4.18. CensorNet (United Kingdom)
        • 6.4.18.1. Business Overview
        • 6.4.18.2. Products/Services Offerings
        • 6.4.18.3. Financial Analysis
        • 6.4.18.4. SWOT Analysis
      • 6.4.19. Clearswift (United Kingdom)
        • 6.4.19.1. Business Overview
        • 6.4.19.2. Products/Services Offerings
        • 6.4.19.3. Financial Analysis
        • 6.4.19.4. SWOT Analysis
      • 6.4.20. Wavecrest (United States)
        • 6.4.20.1. Business Overview
        • 6.4.20.2. Products/Services Offerings
        • 6.4.20.3. Financial Analysis
        • 6.4.20.4. SWOT Analysis
  • 7. Global Web Content Filtering Sale, by Type, Application and Region (value) (2021-2026)
    • 7.1. Introduction
    • 7.2. Global Web Content Filtering (Value)
      • 7.2.1. Global Web Content Filtering by: Type (Value)
        • 7.2.1.1. Client-Side Filters
        • 7.2.1.2. Content Limited ISPs
        • 7.2.1.3. Server-Side Filters
        • 7.2.1.4. Search-Engine Filters
      • 7.2.2. Global Web Content Filtering by: Application (Value)
        • 7.2.2.1. Business Organizations
        • 7.2.2.2. Schools and Institutions
        • 7.2.2.3. Federal and Government Agencies
        • 7.2.2.4. Others
      • 7.2.3. Global Web Content Filtering Region
        • 7.2.3.1. South America
          • 7.2.3.1.1. Brazil
          • 7.2.3.1.2. Argentina
          • 7.2.3.1.3. Rest of South America
        • 7.2.3.2. Asia Pacific
          • 7.2.3.2.1. China
          • 7.2.3.2.2. Japan
          • 7.2.3.2.3. India
          • 7.2.3.2.4. South Korea
          • 7.2.3.2.5. Taiwan
          • 7.2.3.2.6. Australia
          • 7.2.3.2.7. Rest of Asia-Pacific
        • 7.2.3.3. Europe
          • 7.2.3.3.1. Germany
          • 7.2.3.3.2. France
          • 7.2.3.3.3. Italy
          • 7.2.3.3.4. United Kingdom
          • 7.2.3.3.5. Netherlands
          • 7.2.3.3.6. Rest of Europe
        • 7.2.3.4. MEA
          • 7.2.3.4.1. Middle East
          • 7.2.3.4.2. Africa
        • 7.2.3.5. North America
          • 7.2.3.5.1. United States
          • 7.2.3.5.2. Canada
          • 7.2.3.5.3. Mexico
  • 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. Web Content Filtering: by Type(USD Million)
  • Table 2. Web Content Filtering Client-Side Filters , by Region USD Million (2015-2020)
  • Table 3. Web Content Filtering Content Limited ISPs , by Region USD Million (2015-2020)
  • Table 4. Web Content Filtering Server-Side Filters , by Region USD Million (2015-2020)
  • Table 5. Web Content Filtering Search-Engine Filters , by Region USD Million (2015-2020)
  • Table 6. Web Content Filtering: by Application(USD Million)
  • Table 7. Web Content Filtering Business Organizations , by Region USD Million (2015-2020)
  • Table 8. Web Content Filtering Schools and Institutions , by Region USD Million (2015-2020)
  • Table 9. Web Content Filtering Federal and Government Agencies , by Region USD Million (2015-2020)
  • Table 10. Web Content Filtering Others , by Region USD Million (2015-2020)
  • Table 11. South America Web Content Filtering, by Country USD Million (2015-2020)
  • Table 12. South America Web Content Filtering, by Type USD Million (2015-2020)
  • Table 13. South America Web Content Filtering, by Application USD Million (2015-2020)
  • Table 14. Brazil Web Content Filtering, by Type USD Million (2015-2020)
  • Table 15. Brazil Web Content Filtering, by Application USD Million (2015-2020)
  • Table 16. Argentina Web Content Filtering, by Type USD Million (2015-2020)
  • Table 17. Argentina Web Content Filtering, by Application USD Million (2015-2020)
  • Table 18. Rest of South America Web Content Filtering, by Type USD Million (2015-2020)
  • Table 19. Rest of South America Web Content Filtering, by Application USD Million (2015-2020)
  • Table 20. Asia Pacific Web Content Filtering, by Country USD Million (2015-2020)
  • Table 21. Asia Pacific Web Content Filtering, by Type USD Million (2015-2020)
  • Table 22. Asia Pacific Web Content Filtering, by Application USD Million (2015-2020)
  • Table 23. China Web Content Filtering, by Type USD Million (2015-2020)
  • Table 24. China Web Content Filtering, by Application USD Million (2015-2020)
  • Table 25. Japan Web Content Filtering, by Type USD Million (2015-2020)
  • Table 26. Japan Web Content Filtering, by Application USD Million (2015-2020)
  • Table 27. India Web Content Filtering, by Type USD Million (2015-2020)
  • Table 28. India Web Content Filtering, by Application USD Million (2015-2020)
  • Table 29. South Korea Web Content Filtering, by Type USD Million (2015-2020)
  • Table 30. South Korea Web Content Filtering, by Application USD Million (2015-2020)
  • Table 31. Taiwan Web Content Filtering, by Type USD Million (2015-2020)
  • Table 32. Taiwan Web Content Filtering, by Application USD Million (2015-2020)
  • Table 33. Australia Web Content Filtering, by Type USD Million (2015-2020)
  • Table 34. Australia Web Content Filtering, by Application USD Million (2015-2020)
  • Table 35. Rest of Asia-Pacific Web Content Filtering, by Type USD Million (2015-2020)
  • Table 36. Rest of Asia-Pacific Web Content Filtering, by Application USD Million (2015-2020)
  • Table 37. Europe Web Content Filtering, by Country USD Million (2015-2020)
  • Table 38. Europe Web Content Filtering, by Type USD Million (2015-2020)
  • Table 39. Europe Web Content Filtering, by Application USD Million (2015-2020)
  • Table 40. Germany Web Content Filtering, by Type USD Million (2015-2020)
  • Table 41. Germany Web Content Filtering, by Application USD Million (2015-2020)
  • Table 42. France Web Content Filtering, by Type USD Million (2015-2020)
  • Table 43. France Web Content Filtering, by Application USD Million (2015-2020)
  • Table 44. Italy Web Content Filtering, by Type USD Million (2015-2020)
  • Table 45. Italy Web Content Filtering, by Application USD Million (2015-2020)
  • Table 46. United Kingdom Web Content Filtering, by Type USD Million (2015-2020)
  • Table 47. United Kingdom Web Content Filtering, by Application USD Million (2015-2020)
  • Table 48. Netherlands Web Content Filtering, by Type USD Million (2015-2020)
  • Table 49. Netherlands Web Content Filtering, by Application USD Million (2015-2020)
  • Table 50. Rest of Europe Web Content Filtering, by Type USD Million (2015-2020)
  • Table 51. Rest of Europe Web Content Filtering, by Application USD Million (2015-2020)
  • Table 52. MEA Web Content Filtering, by Country USD Million (2015-2020)
  • Table 53. MEA Web Content Filtering, by Type USD Million (2015-2020)
  • Table 54. MEA Web Content Filtering, by Application USD Million (2015-2020)
  • Table 55. Middle East Web Content Filtering, by Type USD Million (2015-2020)
  • Table 56. Middle East Web Content Filtering, by Application USD Million (2015-2020)
  • Table 57. Africa Web Content Filtering, by Type USD Million (2015-2020)
  • Table 58. Africa Web Content Filtering, by Application USD Million (2015-2020)
  • Table 59. North America Web Content Filtering, by Country USD Million (2015-2020)
  • Table 60. North America Web Content Filtering, by Type USD Million (2015-2020)
  • Table 61. North America Web Content Filtering, by Application USD Million (2015-2020)
  • Table 62. United States Web Content Filtering, by Type USD Million (2015-2020)
  • Table 63. United States Web Content Filtering, by Application USD Million (2015-2020)
  • Table 64. Canada Web Content Filtering, by Type USD Million (2015-2020)
  • Table 65. Canada Web Content Filtering, by Application USD Million (2015-2020)
  • Table 66. Mexico Web Content Filtering, by Type USD Million (2015-2020)
  • Table 67. Mexico Web Content Filtering, by Application USD Million (2015-2020)
  • Table 68. Company Basic Information, Sales Area and Its Competitors
  • Table 69. Company Basic Information, Sales Area and Its Competitors
  • Table 70. Company Basic Information, Sales Area and Its Competitors
  • Table 71. Company Basic Information, Sales Area and Its Competitors
  • Table 72. Company Basic Information, Sales Area and Its Competitors
  • Table 73. Company Basic Information, Sales Area and Its Competitors
  • Table 74. Company Basic Information, Sales Area and Its Competitors
  • Table 75. Company Basic Information, Sales Area and Its Competitors
  • Table 76. Company Basic Information, Sales Area and Its Competitors
  • Table 77. Company Basic Information, Sales Area and Its Competitors
  • Table 78. Company Basic Information, Sales Area and Its Competitors
  • Table 79. Company Basic Information, Sales Area and Its Competitors
  • Table 80. Company Basic Information, Sales Area and Its Competitors
  • Table 81. Company Basic Information, Sales Area and Its Competitors
  • Table 82. Company Basic Information, Sales Area and Its Competitors
  • Table 83. Company Basic Information, Sales Area and Its Competitors
  • Table 84. Company Basic Information, Sales Area and Its Competitors
  • Table 85. Company Basic Information, Sales Area and Its Competitors
  • Table 86. Company Basic Information, Sales Area and Its Competitors
  • Table 87. Company Basic Information, Sales Area and Its Competitors
  • Table 88. Web Content Filtering: by Type(USD Million)
  • Table 89. Web Content Filtering Client-Side Filters , by Region USD Million (2021-2026)
  • Table 90. Web Content Filtering Content Limited ISPs , by Region USD Million (2021-2026)
  • Table 91. Web Content Filtering Server-Side Filters , by Region USD Million (2021-2026)
  • Table 92. Web Content Filtering Search-Engine Filters , by Region USD Million (2021-2026)
  • Table 93. Web Content Filtering: by Application(USD Million)
  • Table 94. Web Content Filtering Business Organizations , by Region USD Million (2021-2026)
  • Table 95. Web Content Filtering Schools and Institutions , by Region USD Million (2021-2026)
  • Table 96. Web Content Filtering Federal and Government Agencies , by Region USD Million (2021-2026)
  • Table 97. Web Content Filtering Others , by Region USD Million (2021-2026)
  • Table 98. South America Web Content Filtering, by Country USD Million (2021-2026)
  • Table 99. South America Web Content Filtering, by Type USD Million (2021-2026)
  • Table 100. South America Web Content Filtering, by Application USD Million (2021-2026)
  • Table 101. Brazil Web Content Filtering, by Type USD Million (2021-2026)
  • Table 102. Brazil Web Content Filtering, by Application USD Million (2021-2026)
  • Table 103. Argentina Web Content Filtering, by Type USD Million (2021-2026)
  • Table 104. Argentina Web Content Filtering, by Application USD Million (2021-2026)
  • Table 105. Rest of South America Web Content Filtering, by Type USD Million (2021-2026)
  • Table 106. Rest of South America Web Content Filtering, by Application USD Million (2021-2026)
  • Table 107. Asia Pacific Web Content Filtering, by Country USD Million (2021-2026)
  • Table 108. Asia Pacific Web Content Filtering, by Type USD Million (2021-2026)
  • Table 109. Asia Pacific Web Content Filtering, by Application USD Million (2021-2026)
  • Table 110. China Web Content Filtering, by Type USD Million (2021-2026)
  • Table 111. China Web Content Filtering, by Application USD Million (2021-2026)
  • Table 112. Japan Web Content Filtering, by Type USD Million (2021-2026)
  • Table 113. Japan Web Content Filtering, by Application USD Million (2021-2026)
  • Table 114. India Web Content Filtering, by Type USD Million (2021-2026)
  • Table 115. India Web Content Filtering, by Application USD Million (2021-2026)
  • Table 116. South Korea Web Content Filtering, by Type USD Million (2021-2026)
  • Table 117. South Korea Web Content Filtering, by Application USD Million (2021-2026)
  • Table 118. Taiwan Web Content Filtering, by Type USD Million (2021-2026)
  • Table 119. Taiwan Web Content Filtering, by Application USD Million (2021-2026)
  • Table 120. Australia Web Content Filtering, by Type USD Million (2021-2026)
  • Table 121. Australia Web Content Filtering, by Application USD Million (2021-2026)
  • Table 122. Rest of Asia-Pacific Web Content Filtering, by Type USD Million (2021-2026)
  • Table 123. Rest of Asia-Pacific Web Content Filtering, by Application USD Million (2021-2026)
  • Table 124. Europe Web Content Filtering, by Country USD Million (2021-2026)
  • Table 125. Europe Web Content Filtering, by Type USD Million (2021-2026)
  • Table 126. Europe Web Content Filtering, by Application USD Million (2021-2026)
  • Table 127. Germany Web Content Filtering, by Type USD Million (2021-2026)
  • Table 128. Germany Web Content Filtering, by Application USD Million (2021-2026)
  • Table 129. France Web Content Filtering, by Type USD Million (2021-2026)
  • Table 130. France Web Content Filtering, by Application USD Million (2021-2026)
  • Table 131. Italy Web Content Filtering, by Type USD Million (2021-2026)
  • Table 132. Italy Web Content Filtering, by Application USD Million (2021-2026)
  • Table 133. United Kingdom Web Content Filtering, by Type USD Million (2021-2026)
  • Table 134. United Kingdom Web Content Filtering, by Application USD Million (2021-2026)
  • Table 135. Netherlands Web Content Filtering, by Type USD Million (2021-2026)
  • Table 136. Netherlands Web Content Filtering, by Application USD Million (2021-2026)
  • Table 137. Rest of Europe Web Content Filtering, by Type USD Million (2021-2026)
  • Table 138. Rest of Europe Web Content Filtering, by Application USD Million (2021-2026)
  • Table 139. MEA Web Content Filtering, by Country USD Million (2021-2026)
  • Table 140. MEA Web Content Filtering, by Type USD Million (2021-2026)
  • Table 141. MEA Web Content Filtering, by Application USD Million (2021-2026)
  • Table 142. Middle East Web Content Filtering, by Type USD Million (2021-2026)
  • Table 143. Middle East Web Content Filtering, by Application USD Million (2021-2026)
  • Table 144. Africa Web Content Filtering, by Type USD Million (2021-2026)
  • Table 145. Africa Web Content Filtering, by Application USD Million (2021-2026)
  • Table 146. North America Web Content Filtering, by Country USD Million (2021-2026)
  • Table 147. North America Web Content Filtering, by Type USD Million (2021-2026)
  • Table 148. North America Web Content Filtering, by Application USD Million (2021-2026)
  • Table 149. United States Web Content Filtering, by Type USD Million (2021-2026)
  • Table 150. United States Web Content Filtering, by Application USD Million (2021-2026)
  • Table 151. Canada Web Content Filtering, by Type USD Million (2021-2026)
  • Table 152. Canada Web Content Filtering, by Application USD Million (2021-2026)
  • Table 153. Mexico Web Content Filtering, by Type USD Million (2021-2026)
  • Table 154. Mexico Web Content Filtering, by Application USD Million (2021-2026)
  • Table 155. Research Programs/Design for This Report
  • Table 156. Key Data Information from Secondary Sources
  • Table 157. 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 Web Content Filtering: by Type USD Million (2015-2020)
  • Figure 5. Global Web Content Filtering: by Application USD Million (2015-2020)
  • Figure 6. South America Web Content Filtering Share (%), by Country
  • Figure 7. Asia Pacific Web Content Filtering Share (%), by Country
  • Figure 8. Europe Web Content Filtering Share (%), by Country
  • Figure 9. MEA Web Content Filtering Share (%), by Country
  • Figure 10. North America Web Content Filtering Share (%), by Country
  • Figure 11. Global Web Content Filtering share by Players 2020 (%)
  • Figure 12. Global Web Content Filtering share by Players (Top 3) 2020(%)
  • Figure 13. Global Web Content Filtering share by Players (Top 5) 2020(%)
  • Figure 14. BCG Matrix for key Companies
  • Figure 15. Fortinet (United States) Revenue, Net Income and Gross profit
  • Figure 16. Fortinet (United States) Revenue: by Geography 2020
  • Figure 17. Trend Micro (United States) Revenue, Net Income and Gross profit
  • Figure 18. Trend Micro (United States) Revenue: by Geography 2020
  • Figure 19. Cisco (United States) Revenue, Net Income and Gross profit
  • Figure 20. Cisco (United States) Revenue: by Geography 2020
  • Figure 21. Symantec (United States) Revenue, Net Income and Gross profit
  • Figure 22. Symantec (United States) Revenue: by Geography 2020
  • Figure 23. McAfee (United States) Revenue, Net Income and Gross profit
  • Figure 24. McAfee (United States) Revenue: by Geography 2020
  • Figure 25. Palo Alto Networks (United States) Revenue, Net Income and Gross profit
  • Figure 26. Palo Alto Networks (United States) Revenue: by Geography 2020
  • Figure 27. Zscaler (United States) Revenue, Net Income and Gross profit
  • Figure 28. Zscaler (United States) Revenue: by Geography 2020
  • Figure 29. Trustwave (United States) Revenue, Net Income and Gross profit
  • Figure 30. Trustwave (United States) Revenue: by Geography 2020
  • Figure 31. Forcepoint (United States) Revenue, Net Income and Gross profit
  • Figure 32. Forcepoint (United States) Revenue: by Geography 2020
  • Figure 33. Sophos (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 34. Sophos (United Kingdom) Revenue: by Geography 2020
  • Figure 35. Barracuda Networks (United States) Revenue, Net Income and Gross profit
  • Figure 36. Barracuda Networks (United States) Revenue: by Geography 2020
  • Figure 37. Iboss (United States) Revenue, Net Income and Gross profit
  • Figure 38. Iboss (United States) Revenue: by Geography 2020
  • Figure 39. Webroot (United States) Revenue, Net Income and Gross profit
  • Figure 40. Webroot (United States) Revenue: by Geography 2020
  • Figure 41. Interoute (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 42. Interoute (United Kingdom) Revenue: by Geography 2020
  • Figure 43. TitanHQ (Ireland) Revenue, Net Income and Gross profit
  • Figure 44. TitanHQ (Ireland) Revenue: by Geography 2020
  • Figure 45. Virtela (United States) Revenue, Net Income and Gross profit
  • Figure 46. Virtela (United States) Revenue: by Geography 2020
  • Figure 47. Netskope (United States) Revenue, Net Income and Gross profit
  • Figure 48. Netskope (United States) Revenue: by Geography 2020
  • Figure 49. CensorNet (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 50. CensorNet (United Kingdom) Revenue: by Geography 2020
  • Figure 51. Clearswift (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 52. Clearswift (United Kingdom) Revenue: by Geography 2020
  • Figure 53. Wavecrest (United States) Revenue, Net Income and Gross profit
  • Figure 54. Wavecrest (United States) Revenue: by Geography 2020
  • Figure 55. Global Web Content Filtering: by Type USD Million (2021-2026)
  • Figure 56. Global Web Content Filtering: by Application USD Million (2021-2026)
  • Figure 57. South America Web Content Filtering Share (%), by Country
  • Figure 58. Asia Pacific Web Content Filtering Share (%), by Country
  • Figure 59. Europe Web Content Filtering Share (%), by Country
  • Figure 60. MEA Web Content Filtering Share (%), by Country
  • Figure 61. North America Web Content Filtering Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Fortinet (United States)
  • Trend Micro (United States)
  • Cisco (United States)
  • Symantec (United States)
  • McAfee (United States)
  • Palo Alto Networks (United States)
  • Zscaler (United States)
  • Trustwave (United States)
  • Forcepoint (United States)
  • Sophos (United Kingdom)
  • Barracuda Networks (United States)
  • iboss (United States)
  • Webroot (United States)
  • Interoute (United Kingdom)
  • TitanHQ (Ireland)
  • Virtela (United States)
  • Netskope (United States)
  • CensorNet (United Kingdom)
  • Clearswift (United Kingdom)
  • Wavecrest (United States)
Additional players considered in the study are as follows:
Cyren (United States) , GFI Software (Malta) , Untangle (United States) , ContentKeeper (Australia) , Kaspersky (Russia)
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Key Highlights of Report


Mar 2021 221 Pages 69 Tables Base Year: 2021 Coverage: 15+ Companies; 18 Countries

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Global Web Content Filtering Quantitative research analysis
Global Web Content Filtering Qualitative Industry Analysis
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