网路爬虫软体市场 - 全球产业规模、份额、趋势、机会、预测：按类型、部署模式、最终用户、地区和竞争格局划分，2021-2031年

全球网路爬虫软体市场预计将从 2025 年的 1,081,960,000 美元成长到 2031 年的 2,586,030,000 美元，复合年增长率为 15.63%。

该软体包含一系列自动化工具，旨在收集非结构化的网路资料并将其转换为适合分析的结构化格式。该领域的成长主要源于金融投资策略对另类数据日益增长的需求，以及线上零售业对即时竞争价格追踪的需求。企业越来越依赖这些解决方案来收集公开资讯以进行市场情报分析，并建立资料密集型分析平台。这不仅省去了手动资料输入的步骤，还有助于提高营运效率。

然而，由于防御技术的进步和旨在保护用户隐私和防止诈骗的法律法规，该行业面临许多挑战。合法的资料提取工作经常受到恶意活动启动的复杂拦截系统的阻碍。根据全球反诈骗联盟预测，到2024年，全球因诈骗造成的损失将超过1.03兆美元，迫使企业实施严格的数位防御措施。然而，这些措施却无意中阻碍了合法的网路爬虫活动。

市场驱动因素

人工智慧 (AI) 和机器学习 (ML) 模型训练对大量结构化资料的需求日益增长，这是推动市场扩张的主要动力。企业和开发者正在扩大网路爬虫软体的使用范围，以收集改进大规模语言模型 (LLM) 和生成系统所需的各种资料集。高品质公共资讯的匮乏进一步加剧了这种需求，而高品质公共资讯对于开发至关重要。 Epoch AI 在 2024 年 6 月发布的分析报告《数据会枯竭吗？ 》预测，高品质公共语言资料的供应可能在 2026 年至 2032 年间耗尽，这将促使各组织立即加强资料提取力道。因此，网路自动化基础设施得到了显着扩展。根据泰雷兹 (Thales) 2024 年的报告，自动化机器人上年度占所有网路流量的 49.6%，凸显了自动化资料收集在数位经济中的重要性。

此外，电子商务产业的快速成长使得企业越来越依赖网路爬虫工具来收集动态定价资讯和进行市场监测。线上经销商利用这些解决方案即时监控竞争对手的价格、存量基准和消费者情绪，从而能够即时调整策略以维持利润率。数位商务的庞大规模使得及时且准确的数据变得尤为重要。 Adobe 于 2024 年 10 月发布的《2024 年假期购物预测》预测，美国线上销售额将达到 2,408 亿美元，这创造了一个竞争激烈的环境，基于网路爬虫资料的演算法定价策略对于企业的生存至关重要。这种竞争格局确保了网路爬虫软体仍将是商业策略的核心要素，即使目标网站采取了防御措施。

市场挑战

全球网路爬虫软体市场面临的主要障碍是日益猖獗的防御技术和旨在保护数位资产的法律限制。随着网站实施严格的通讯协定来保护使用者隐私和防止资料窃取，合法的爬虫工具常常会受到诸如IP黑名单、验证码机制和行为分析等复杂措施的阻碍。由于这些防御措施通常无法区分合法的抓取活动和恶意机器人，软体供应商被迫不断开发昂贵的规避技术。这种情况显着增加了营运成本，并降低了所收集资料的可靠性，因此潜在客户往往不愿意投资那些无法保证稳定存取关键资讯的爬虫解决方案。

这种监管趋严的趋势是对网路犯罪日益猖獗的直接回应，迫使企业加强其线上防御。根据商家风险委员会 (MRC) 发布的 2024 年报告，超过 60% 的企业正面临诈欺相关滥用行为的增加，因此亟需广泛采用更严格的自动化过滤系统。这种防御措施的激增无意中抑制了网路爬虫市场的成长，因为它将公共数据置于难以取得的屏障之后。随着资料收集过程在技术上变得高成本，软体供应商的利润率正在下降，市场接受度也在放缓。

市场趋势

人工智慧在自适应资料提取领域的应用正在改变市场格局，它能有效降低因网站架构频繁变更而带来的维护负担。与依赖静态程式码选择器的传统爬虫不同，自癒演算法利用机器学习和电脑视觉技术动态分析页面布局，使撷取过程能够自动适应前端变化。这项技术进步显着提升了大规模资料采集计划的资料可靠性和运作效率。正如Zyte在2025年1月发布的《2025年网路爬虫产业报告》中所述，人工智慧驱动的自主撷取技术使结构化电商资料的交付速度比传统的手动脚本方法提高了三倍。这凸显了自适应系统带来的显着效率提升。

同时，无程式码/低程式码网路爬虫工具的兴起，使网路情报的取得更加普及，使用者群体也从专业工程团队扩展到了更广泛的使用者群体。这些平台透过提供预先配置的撷取范本和视觉化的点击式介面，降低了技术门槛，使业务分析师和非技术人员能够独立管理资料收集工作流程。这种可近性的提升正在推动各行各业对自动化数据工具的快速采用。根据 Apify 于 2025 年 1 月发布的《2025 年网路爬虫现况报告》，该平台的每月有效用户年增了 142%。这一成长主要源于不断扩大的专业人士群体对易于使用的云端自动化解决方案日益增长的需求。

目录

第一章概述

第二章：调查方法

第三章执行摘要

第四章：客户心声

第五章：全球网路爬虫软体市场展望

• 市场规模及预测
  • 按金额
• 市占率及预测
  • 依类型（通用网路履带、增量网路履带、深度网路履带）
  • 部署方式（云端部署、本机部署）
  • 按最终用户（银行、金融服务和保险、零售/电子商务、房地产、政府、医疗保健、其他）
  • 按地区
  • 按公司（2025 年）
• 市场地图

第六章：北美网路爬虫软体市场展望

• 市场规模及预测
• 市占率及预测
• 北美洲：国别分析
  • 我们
  • 加拿大
  • 墨西哥

第七章：欧洲网路爬虫软体市场展望

• 市场规模及预测
• 市占率及预测
• 欧洲：国别分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太地区网路爬虫软体市场展望

• 市场规模及预测
• 市占率及预测
• 亚太地区：国别分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

第九章：中东和非洲网路爬虫软体市场展望

• 市场规模及预测
• 市占率及预测
• 中东与非洲：国别分析
  • 沙乌地阿拉伯
  • 阿拉伯聯合大公国
  • 南非

第十章：南美洲网路爬虫软体市场展望

• 市场规模及预测
• 市占率及预测
• 南美洲：国别分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第十一章 市场动态

• 促进因素
• 任务

第十二章 市场趋势与发展

• 併购
• 产品发布
• 近期趋势

第十三章：全球网路爬虫软体市场：SWOT分析

第十四章：波特五力分析

• 产业竞争
• 新进入者的潜力
• 供应商的议价能力
• 顾客权力
• 替代品的威胁

第十五章 竞争格局

• Octopus Data Inc.
• Web Spiders Group
• Mozenda, Inc.
• Zyte Group Limited
• Ficstar Software Inc
• QL2 Software, LLC
• Diggernaut, LLC
• UiPath Inc.
• Diffbot Technologies Corp.
• Hashwave Technologies Inc.

第十六章 策略建议

第十七章：关于研究公司及免责声明

The Global Web Scraping Software Market is projected to expand from USD 1081.96 Million in 2025 to USD 2586.03 Million by 2031, registering a 15.63% CAGR. This software includes automated tools engineered to collect unstructured internet data and transform it into structured formats suitable for analysis. Growth in this sector is largely fueled by the rising need for alternative data in financial investment strategies and the requirement for real-time competitive price tracking within the online retail industry. Companies are increasingly depending on these solutions to gather public information for market intelligence and to populate data-heavy analytics platforms, which supports operational efficiency by eliminating the need for manual data entry.

Nevertheless, the industry encounters substantial hurdles due to strengthening defensive technologies and legal regulations designed to safeguard user privacy and deter fraud. Lawful data extraction efforts are frequently obstructed by complex blocking systems activated by widespread malicious activities. As reported by the Global Anti-Scam Alliance, scams resulted in global losses exceeding $1.03 trillion in 2024, prompting businesses to enforce rigorous digital defenses that unintentionally hinder legitimate web scraping activities.

Market Driver

The escalating need for extensive structured data to train Artificial Intelligence and Machine Learning models acts as a major driver for market expansion. Enterprises and developers are increasingly utilizing scraping software to gather the varied datasets necessary for improving Large Language Models and generative systems. This demand is intensified by the limited availability of high-quality public information essential for development. Epoch AI's June 2024 analysis, 'Will we run out of data?', predicts that the supply of high-quality public language data may run out between 2026 and 2032, driving organizations to ramp up their extraction efforts immediately. Consequently, the infrastructure for web automation has grown substantially; Thales reported in 2024 that automated bots represented 49.6% of all internet traffic the previous year, highlighting the vital importance of automated data collection in the digital economy.

Additionally, the rapid growth of the e-commerce industry reinforces the dependence on scraping tools for dynamic pricing intelligence and market surveillance. Online merchants employ these solutions to monitor competitor prices, inventory levels, and consumer sentiment in real-time, facilitating immediate adjustments to preserve profit margins. The importance of timely and accurate data is heightened by the massive scale of digital commerce. In its October 2024 '2024 Holiday Shopping Forecast', Adobe projects U.S. online sales to hit $240.8 billion, establishing a high-pressure environment where algorithmic pricing strategies based on scraped data are crucial for business survival. This competitive landscape ensures that web scraping software remains a core component of commercial strategy, regardless of the defensive barriers erected by target websites.

Market Challenge

A major obstacle obstructing the Global Web Scraping Software Market is the swift increase in aggressive defensive technologies and legal constraints aimed at securing digital assets. Because websites are implementing rigorous protocols to safeguard user privacy and prevent data theft, legitimate scraping tools are often obstructed by advanced countermeasures like IP blacklisting, CAPTCHA mechanisms, and behavioral analysis. Since these defenses frequently cannot differentiate between authorized extraction activities and malicious bots, software vendors are forced to continually create expensive evasion techniques. This situation substantially raises operational costs and compromises the reliability of collected data, causing potential clients to hesitate before investing in scraping solutions that cannot assure consistent access to essential information.

This increasingly restrictive environment is a direct reaction to rising digital crime, compelling businesses to strengthen their online defenses. The Merchant Risk Council reported in 2024 that over 60 percent of merchants experienced a rise in fraud-related misuse, requiring the broad adoption of tighter automated filtering systems. This surge in defensive measures unintentionally curtails the scraping market's growth by placing public data behind inaccessible barriers. As the process of retrieving information becomes more technically challenging and costly, the market encounters reduced profit margins for software providers and slower adoption rates.

Market Trends

The incorporation of AI for Adaptive Data Extraction is transforming the market by reducing the maintenance burden associated with frequent alterations in website architecture. In contrast to traditional scrapers that depend on static code selectors, self-healing algorithms employ machine learning and computer vision to dynamically analyze page layouts, enabling extraction processes to automatically adjust to front-end changes. This technological progression greatly improves data reliability and operational efficiency for large-scale collection initiatives. As stated in Zyte's '2025 Web Scraping Industry Report' from January 2025, the use of AI-powered autonomous extraction technologies facilitated the delivery of structured e-commerce data three times faster than older manual scripting techniques, highlighting the significant efficiency improvements offered by adaptive systems.

Concurrently, the rise of No-Code and Low-Code Scraping Tools is democratizing access to web intelligence, broadening the user base to include those outside of specialized engineering groups. These platforms reduce technical barriers by providing pre-configured extraction templates and visual point-and-click interfaces, allowing business analysts and non-technical personnel to independently manage data collection workflows. This increased accessibility is fueling a swift rise in the adoption of automated data tools across various industries. According to Apify's 'State of Web Scraping Report 2025' from January 2025, the platform experienced a 142% growth in monthly active users over the previous year, a spike driven by the escalating demand for accessible, cloud-based automation solutions among a growing professional audience.

Key Market Players

• Octopus Data Inc.
• Web Spiders Group
• Mozenda, Inc.
• Zyte Group Limited
• Ficstar Software Inc
• QL2 Software, LLC
• Diggernaut, LLC
• UiPath Inc.
• Diffbot Technologies Corp.
• Hashwave Technologies Inc.

Report Scope

In this report, the Global Web Scraping Software Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Web Scraping Software Market, By Type

• General-Purpose Web Crawlers
• Incremental Web Crawlers
• Deep Web Crawlers

Web Scraping Software Market, By Deployment Mode

• Cloud-Based
• On-Premises

Web Scraping Software Market, By End-User

• BFSI
• Retail & E-Commerce
• Real Estate
• Government
• Healthcare
• Others

Web Scraping Software Market, By Region

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
• South America
  • Brazil
  • Argentina
  • Colombia
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Web Scraping Software Market.

Available Customizations:

Global Web Scraping Software Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Web Scraping Software Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Type (General-Purpose Web Crawlers, Incremental Web Crawlers, Deep Web Crawlers)
  • 5.2.2. By Deployment Mode (Cloud-Based, On-Premises)
  • 5.2.3. By End-User (BFSI, Retail & E-Commerce, Real Estate, Government, Healthcare, Others)
  • 5.2.4. By Region
  • 5.2.5. By Company (2025)
• 5.3. Market Map

6. North America Web Scraping Software Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Type
  • 6.2.2. By Deployment Mode
  • 6.2.3. By End-User
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Web Scraping Software Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Type
      • 6.3.1.2.2. By Deployment Mode
      • 6.3.1.2.3. By End-User
  • 6.3.2. Canada Web Scraping Software Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Type
      • 6.3.2.2.2. By Deployment Mode
      • 6.3.2.2.3. By End-User
  • 6.3.3. Mexico Web Scraping Software Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Type
      • 6.3.3.2.2. By Deployment Mode
      • 6.3.3.2.3. By End-User

7. Europe Web Scraping Software Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Type
  • 7.2.2. By Deployment Mode
  • 7.2.3. By End-User
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Web Scraping Software Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Type
      • 7.3.1.2.2. By Deployment Mode
      • 7.3.1.2.3. By End-User
  • 7.3.2. France Web Scraping Software Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Type
      • 7.3.2.2.2. By Deployment Mode
      • 7.3.2.2.3. By End-User
  • 7.3.3. United Kingdom Web Scraping Software Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Type
      • 7.3.3.2.2. By Deployment Mode
      • 7.3.3.2.3. By End-User
  • 7.3.4. Italy Web Scraping Software Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Type
      • 7.3.4.2.2. By Deployment Mode
      • 7.3.4.2.3. By End-User
  • 7.3.5. Spain Web Scraping Software Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Type
      • 7.3.5.2.2. By Deployment Mode
      • 7.3.5.2.3. By End-User

8. Asia Pacific Web Scraping Software Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Type
  • 8.2.2. By Deployment Mode
  • 8.2.3. By End-User
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Web Scraping Software Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Type
      • 8.3.1.2.2. By Deployment Mode
      • 8.3.1.2.3. By End-User
  • 8.3.2. India Web Scraping Software Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Type
      • 8.3.2.2.2. By Deployment Mode
      • 8.3.2.2.3. By End-User
  • 8.3.3. Japan Web Scraping Software Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Type
      • 8.3.3.2.2. By Deployment Mode
      • 8.3.3.2.3. By End-User
  • 8.3.4. South Korea Web Scraping Software Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Type
      • 8.3.4.2.2. By Deployment Mode
      • 8.3.4.2.3. By End-User
  • 8.3.5. Australia Web Scraping Software Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Type
      • 8.3.5.2.2. By Deployment Mode
      • 8.3.5.2.3. By End-User

9. Middle East & Africa Web Scraping Software Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Type
  • 9.2.2. By Deployment Mode
  • 9.2.3. By End-User
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Web Scraping Software Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Type
      • 9.3.1.2.2. By Deployment Mode
      • 9.3.1.2.3. By End-User
  • 9.3.2. UAE Web Scraping Software Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Type
      • 9.3.2.2.2. By Deployment Mode
      • 9.3.2.2.3. By End-User
  • 9.3.3. South Africa Web Scraping Software Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Type
      • 9.3.3.2.2. By Deployment Mode
      • 9.3.3.2.3. By End-User

10. South America Web Scraping Software Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Type
  • 10.2.2. By Deployment Mode
  • 10.2.3. By End-User
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Web Scraping Software Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Type
      • 10.3.1.2.2. By Deployment Mode
      • 10.3.1.2.3. By End-User
  • 10.3.2. Colombia Web Scraping Software Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Type
      • 10.3.2.2.2. By Deployment Mode
      • 10.3.2.2.3. By End-User
  • 10.3.3. Argentina Web Scraping Software Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Type
      • 10.3.3.2.2. By Deployment Mode
      • 10.3.3.2.3. By End-User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Global Web Scraping Software Market: SWOT Analysis

14. Porter's Five Forces Analysis

• 14.1. Competition in the Industry
• 14.2. Potential of New Entrants
• 14.3. Power of Suppliers
• 14.4. Power of Customers
• 14.5. Threat of Substitute Products

15. Competitive Landscape

• 15.1. Octopus Data Inc.
  • 15.1.1. Business Overview
  • 15.1.2. Products & Services
  • 15.1.3. Recent Developments
  • 15.1.4. Key Personnel
  • 15.1.5. SWOT Analysis
• 15.2. Web Spiders Group
• 15.3. Mozenda, Inc.
• 15.4. Zyte Group Limited
• 15.5. Ficstar Software Inc
• 15.6. QL2 Software, LLC
• 15.7. Diggernaut, LLC
• 15.8. UiPath Inc.
• 15.9. Diffbot Technologies Corp.
• 15.10. Hashwave Technologies Inc.

16. Strategic Recommendations

17. About Us & Disclaimer