AI-driven Web Scraping Market Outlook (2023 to 2033)

According to Future Market Insights, the global AI-driven web scraping market size has reached US$ 306.1 million in 2018. Demand for AI-driven web scraping recorded Y-o-Y growth of 12.7% in 2022, and thus, the global market is expected to reach US$ 638.5 million in 2023. Over the projection period 2023-2033, AI-driven web scraping solutions sales in the region are projected to exhibit 17.8% CAGR and total a market size of US$ 3,295.0 million by 2033-end.

AI-driven web scraping refers to the practice of using artificial intelligence (AI) technologies and algorithms to automate and enhance the process of extracting data from websites, forums, and blogs.

AI-driven web scraping takes web scraping a step further by leveraging AI techniques to improve the efficiency, accuracy, and adaptability of the scraping process. AI-driven web scraping involves the application of various AI technologies and methods to address common challenges and limitations in traditional web scraping. The techniques include natural language processing (NLP), computer vision, and machine learning enable AI models to understand the structure and semantics of web content, ensuring precise extraction of relevant data.

Other Drivers Propelling the Demand for AI-driven Web Scraping include:

  • Businesses require vast amounts of data for market research, competitive analysis, pricing intelligence, sentiment analysis so; these needs drive the data extraction process.
  • AI-driven web scraping offers automation and higher efficiency compared to manual data extraction methods.
  • Machine learning algorithms can be trained to identify and extract specific data elements accurately, reducing errors and improving the reliability of the extracted data.
  • AI-driven web scraping enables the data extraction of relevant and valuable data from websites, empowering organizations to gain insights and make informed decisions.

Challenges for Companies /Manufacturers in the AI-driven Web Scraping Market:

  • Websites often undergo changes in their structure, layout, or content, making it challenging AI-driven web scraping solutions to extract data consistently and accurately.
  • The legality and ethics of web scraping raise concerns. Some websites explicitly prohibit scraping in their terms of service, and scraping certain types of data may infringe on copyright or privacy laws.
  • Websites may have inconsistencies, errors, or incomplete information, leading to inaccurate or unreliable data extraction.
  • Staying compliant with these regulations while delivering effective web scraping services can be challenging, requiring ongoing monitoring and adaptation to changing legal frameworks.

Opportunities in the AI-driven Web Scraping Industry:

  • There is an opportunity for companies to develop and offer specialized, customized AI-driven web scraping solutions tailored to specific industries or use cases.
  • AI-driven web scraping can go beyond data extraction and offer advanced data analytics capabilities.
  • As the demand for data-driven insights extends across industries, there is an opportunity for AI-driven web scraping companies to expand their presence into different sectors such as, travel, media, and e-commerce.
  • With increasing concerns about data privacy and compliance, there is an opportunity for AI-driven web scraping providers to focus on developing solutions that adhere to ethical scraping practices and comply with relevant regulations.

Latest Trends in the AI-driven Web Scraping Market:

  • Deep learning techniques, including neural networks, will play a significant role in the advancement of AI-driven web scraping.
  • Extracting information from unstructured data, such as images, charts, or non-textual elements, is a significant trend in AI-driven web scraping.
  • Advancements in image recognition, optical character recognition (OCR), and natural language processing (NLP) will enable AI algorithms to extract meaningful insights from visual content.
  • Cloud platforms will enable businesses to handle large volumes of data, scale their scraping operations efficiently, and benefit from the on-demand resources provided by cloud service providers.
Attributes Details
AI-driven Web Scraping Market Size (2023) US$ 638.5 million
AI-driven Web Scraping Market Projected Size (2033) US$ 3,295.0 million
Value CAGR (2023 to 2033) 17.8%

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2018 to 2022 AI-driven Web Scraping Demand Outlook Compared to 2023 to 2033 Forecast

From 2018 to 2022, the global AI-driven web scraping market experienced a CAGR of 17.8%, reaching a market size of US$ 638.5 million in 2023.

From 2018 to 2022, the global AI-driven web scraping industry witnessed a notable growth due to the businesses increasingly relied on data-driven insights to gain a competitive edge, leading to a surge in the need for web scraping services.

Companies across various sectors realized the potential of AI-driven techniques in extracting valuable information from websites at scale. The demand for AI-driven web scraping experienced substantial growth. Businesses across various industries recognized the value of extracting data from websites using AI technologies to gain insights and make data-driven decisions.

Future Forecast for AI-driven Web Scraping Industry

Looking ahead, the global AI-driven web scraping industry is expected to rise at a CAGR of 17.8% from 2023 to 2033. During the forecast period, the market size is expected to reach US$ 3,295.0 million.

The AI-driven Web Scraping industry is expected to continue its growth course from 2023 to 2033, driven by increasing demand for data-driven insights, automation, and efficiency in data extraction processes will drive the adoption of AI-driven web scraping solutions across industries. The market is projected to expand as businesses recognize the value of extracting valuable data from websites for competitive analysis, market research, and decision-making.

Sudip Saha
Sudip Saha

Principal Consultant

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Comparative View of the AI-driven Web Scraping Market

AI-driven Web Scraping Market:

Attributes AI-driven Web Scraping Market
CAGR (2023 to 2033) 17.8%
Market Value (2033) US$ 3,295.0 million
Opportunity As the demand for data-driven insights extends across industries, there is an opportunity for AI-driven web scraping companies to expand their presence into different sectors such as, travel, media, and e-commerce.
Key Trends Extracting information from unstructured data, such as images, charts, or non-textual elements, is a significant trend in AI-driven web scraping.

Web Scraping Software Market:

Attributes Web Scraping Software Market
CAGR (2023 to 2033) 15%
Market Value (2033) US$ 1,469 million
Opportunity Businesses can gain deeper insights into their customers, markets, and competition by using this technology, giving them a powerful edge in the marketplace.
Key Trends Many companies make use of web scraping that uses real-time pricing data from competitors to develop pricing strategies that can be based on dynamic pricing in real-time.

Predictive Analytics Market:

Attributes Predictive Analytics Market
CAGR (2023 to 2033) 15.8%
Market Value (2033) US$ 55,500.6 million
Opportunity As big data becomes more prevalent, predictive analysis is projected to be applied in finance and human resources.
Key Trends The e-commerce sector has enhanced customers' usual purchase experiences. The most important aspects for increasing business sales are dedicated social media marketing and consumer perception analysis.

Country-Wise Insights

AI-driven Web Scraping Market to flourish in the United States for Growing Collaborative Initiatives with Prominent Data Providers

Country The United States
Market Size (US$ million) by End of Forecast Period (2033) US$ 375.6 million
CAGR % 2023 to End of Forecast (2033) 26.5%

The AI-driven web scraping in the United States is expected to reach a market share of US$ 375.6 million by 2033, expanding at a CAGR of 26.5%. The AI-driven Web Scraping in the United States is likely to witness notable growth due to collaboration with data providers and technology partners can unlock new opportunities for AI-driven web scraping providers. By collaborating with data providers, such as data aggregators or specialized industry, data sources, web scraping providers can expand their data sources and offer more comprehensive datasets to their customers. Moreover, there are detailed factors expected to drive the growth for AI-driven Web Scraping in the country are:

  • The United States has a robust AI- driven web scraping market due to its highly developed business landscape and technological advancements.
  • The presence of a large number of technology companies, startups, and enterprises contributes to the demand for web scraping services in the country.

Industry Requirements for Timely and Accurate Data Is Propelling the Market for AI-driven Web Scraping

Country The United Kingdom
Market Size (US$ million) by End of Forecast Period (2033) US$ 316.3 million
CAGR % 2023 to End of Forecast (2033) 29.4%

The AI-driven web scraping industry in the United Kingdom is expected to reach a market share of US$ 316.3 million, expanding at a CAGR of 29.4% during the forecast period. The United Kingdom market is projected to experience growth due to companies requiring timely and accurate data to analyze market trends, consumer behavior, and competitor activities. AI-powered web scraping solutions can extract data from various sources, enabling businesses to make informed decisions, identify emerging opportunities, and stay ahead in a competitive market.

Notable Growth Expected in China's AI-driven Web Scraping Market Due to Optimizing E-commerce Platforms with AI-driven Web Scraping

Country China
Market Size (US$ million) by End of Forecast Period (2033) US$ 359.1 million
CAGR % 2023 to End of Forecast (2033) 28.9%

The AI-driven web scraping industry in China is anticipated to reach a market share of US$ 359.1 million, moving at a CAGR of 28.9% during the forecast period. The AI-driven web scraping market in China is likely to grow due to its large e-commerce sector, data-intensive industries, and advanced technology adoption.

AI-driven web scraping is widely used in China for e-commerce, price monitoring, product data aggregation, and sentiment analysis. E-commerce companies heavily rely on web scraping to gather product information, monitor competitor prices, track consumer behavior, and optimize their offerings.

Germany’s Technological Advancement in Web Scraping is driving the Market Growth

Country Germany
Market Size (US$ million) by End of Forecast Period (2033) US$ 329.5 million
CAGR % 2023 to End of Forecast (2033) 28.1%

The AI-driven web scraping market in Germany is estimated to reach a market share of US$ 329.5 million by 2033, thriving at a CAGR of 28.1%. Germany is known for its innovation and technological advancements. Exploring emerging technologies like computer vision, natural language processing, and edge computing can give companies a competitive edge. Leveraging these technologies to extract data from diverse sources, such as images, videos, and social media, can expand the scope and applicability of AI-driven web scraping solutions.

Demand for AI-driven Web Scraping Due to Increasing Demand for Operations and Data Driven Decisions is driving the Market Growth in India

Country India
Market Size (US$ million) by End of Forecast Period (2033) US$ 266.9 million
CAGR % 2023 to End of Forecast (2033) 27.1%

The AI-driven web scraping industry in India is expected to reach a market share of US$ 266.9 million, expanding at a CAGR of 27.1% during the forecast period. The market in India is estimated to witness notable growth due to a significant digital transformation with entrants of AI technology across various industries. This transformation opens up opportunities for AI-driven web scraping to extract valuable data from websites, enabling businesses to gain insights, optimize operations, and make data-driven decisions. Companies in India are leveraging web scraping to monitor competitors, track market growth, gather customer feedback, and enhance their products and services.

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Category-Wise Insights

Dynamic Web Scraping Segment to Dominate AI-driven Web Scraping Industry with 19.4% CAGR through 2033

The dynamic web scraping segment is expected to dominate the AI-driven web scraping market with a CAGR of 19.4% from 2023 to 2033. This segment captures a significant market share in 2023 due to its prominent application of extracting real-time data updates.

The segment of dynamic web scraping in the AI-driven web scraping market is expected to experience rapid growth because many websites today use dynamic content. Which means the content on the web pages changes dynamically based on user interactions, real-time data updates, or other factors. Dynamic web scraping is necessary to extract data from such websites and capture the updated information in real-time. Examples include e-commerce sites with real-time product availability, social media platforms with live feeds, or news websites with constantly updated articles.

How the Static Web Scraping is driving the AI-driven Web Scraping Market?

The static web scraping segment is expected to dominate the AI-driven web scraping market with a market share of 29.8% over the forecast period. This segment captures a significant market share in 2023 due to its simple and time efficient data extraction techniques.

Static web scraping driving factor in the AI-driven web scraping market is automating the web scraping process, static web scraping saves time and effort compared to manual data collection. It enables businesses to retrieve large amounts of data from multiple web pages quickly and accurately. Automation also reduces human errors and ensures consistent data extraction across different sources.

How Key Players Stay Competitive in the AI-driven Web Scraping Industry?

The AI-driven web scraping industry is highly competitive, with numerous players vying for market share. In such a scenario, key players must adopt effective strategies to stay ahead of the competition.

Key Strategies Adopted by the Players

  • Product Innovation

Companies in the AI-driven web scraping market focus on continuous product innovation to enhance their offerings and meet the evolving needs of customers. Companies are investing in advanced web scraping technologies to improve data extraction accuracy, speed, and scalability. These innovations include the use of machine learning algorithms, natural language processing, computer vision, and other AI techniques to extract and analyze data more efficiently and accurately.

  • Strategic Partnerships and Collaborations

Companies in the AI-driven web scraping market form strategic partnerships and collaborations to leverage complementary strengths and expand their market reach. Companies may collaborate with data providers, software vendors, or other technology companies to integrate their web scraping solutions with existing platforms or data sources. These partnerships enable companies to offer comprehensive solutions to customers and access a wider user base.

  • Expansion into Emerging Markets

To capitalize on the growing demand for AI-driven web scraping solutions, companies are expanding into emerging markets. They identify regions with significant potential for market growth and establish a local presence through partnerships, acquisitions, or setting up subsidiaries. By entering emerging markets, companies can tap into new customer segments and gain a competitive advantage over their rivals.

  • Mergers and Acquisitions

Mergers and acquisitions play a crucial role in the AI-driven web scraping market, allowing companies to consolidate their market position, acquire new capabilities, and gain access to a broader customer base. Companies may acquire smaller competitors to eliminate competition or acquire complementary technologies to enhance their product offerings. Mergers and acquisitions also enable companies to enter new geographic markets or expand their existing market presence.

Key Players in the AI-driven Web Scraping Industry

  • Import.io
  • Diffbot
  • Zyte
  • Mozenda
  • Octoparse

Key Developments in the AI-driven Web Scraping Market:

  • Scaleworks, a venture equity firm specializing in B2B SaaS, has recently revealed its acquisition of Import.io, a prominent enterprise web data extraction provider. Import.io excels in facilitating the collection of data by leveraging cutting-edge technology and industry expertise, enabling the efficient delivery of web data on a large scale. With an extensive network of website feeds that gather an impressive volume of over half a trillion data points each month, Import.io empowers renowned brands worldwide with robust analytics capabilities.
  • Zyte has recently unveiled its latest offering in the form of Zyte API, a web data extraction solution. The company claims that this self-service API integrates a wide range of web scraping technologies and techniques into a user-friendly yet robust API, allowing for seamless and efficient collection of web data on a large scale.
  • Mozenda has recently announced its merger with Dexi, a digital commerce intelligence suite. Under this merger, both Mozenda and Dexi will be maintained as separate products and brands. The combined operations have already commenced, and the headquarters of Dexi.io and Mozenda will remain in London, United Kingdom, and Pleasant Grove, Utah, respectively. Additionally, they will be supported by offices located in Tirana, Albania, and Copenhagen, Denmark.

Segmentation Analysis of the AI-driven Web Scraping Market

By Scraping Type:

  • Static Web Scraping
  • Dynamic Web Scraping
  • API Scraping
  • Image and Text Recognition

By Subscription Model:

  • Paid Services
  • Free Services

By Industry:

  • IT & Telecommunication
  • BFSI
  • E-commerce
  • Healthcare
  • Retail & Consumer Goods
  • Energy & Utilities
  • Others

By Region:

  • North America
  • Latin America
  • Europe
  • East Asia
  • South Asia Pacific
  • Middle East & Africa

Frequently Asked Questions

What is the Expected Net Worth of AI-driven Web Scraping Market?

The net worth of the market is expected to be US$ 3,295.0 million by 2033.

What is the Calculated CAGR for the Market Forecast?

The market is calculated to expand at a CAGR of 17.8% through 2033.

Which Trends are Dictating the Market Growth?

Extraction of information from unstructured data like charts, images, or non-textual elements.

Which Opportunities are Appearing in the Market?

Emerging opportunity to extend their footprint in media, travel and e-commerce, etc., is making the market attractive.

Which Country has the Robust Market CAGR?

China is expected to expand at a robust CAGR of 28.9% through 2033.

Table of Content

1. Executive Summary

    1.1. Global Market Outlook

    1.2. Demand Side Trends

    1.3. Supply Side Trends

    1.4. Analysis and Recommendations

2. Market Overview

    2.1. Market Coverage / Taxonomy

    2.2. Market Definition / Scope / Limitations

3. Key Market Trends

    3.1. Key Trends Impacting the Market

    3.2. Product Innovation / Development Trends

4. Pricing Analysis

    4.1. Pricing Analysis, By Subscription

        4.1.1. Subscription Pricing Model

        4.1.2. Perpetual Licensing

    4.2. Average Pricing Analysis Benchmark

5. Global Market Demand (Value in US$ Million) Analysis 2018 to 2022 and forecast, 2023 to 2033

    5.1. Historical Market Value (US$ Million) Analysis, 2018 to 2022

    5.2. Current and Future Market Value (US$ Million) Projections, 2023 to 2033

        5.2.1. Y-o-Y Growth Trend Analysis

        5.2.2. Absolute $ Opportunity Analysis

6. Market Background

    6.1. Macro-Economic Factors

    6.2. Forecast Factors - Relevance & Impact

    6.3. Value Chain

    6.4. COVID-19 Crisis – Impact Assessment

        6.4.1. Current Statistics

        6.4.2. Short-Mid-Long Term Outlook

        6.4.3. Likely Rebound

    6.5. Market Dynamics

        6.5.1. Drivers

        6.5.2. Restraints

        6.5.3. Opportunities

7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Scraping Type

    7.1. Introduction / Key Findings

    7.2. Historical Market Size (US$ Million) Analysis By Scraping Type, 2018 to 2022

    7.3. Current and Future Market Size (US$ Million) Analysis and Forecast By Scraping Type, 2023 - 2033

        7.3.1. Static Web Scraping

        7.3.2. Dynamic Web Scraping

        7.3.3. API Scraping

        7.3.4. Image and Text Recognition

    7.4. Market Attractiveness Analysis By Scraping Type

8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Subscription Model

    8.1. Introduction / Key Findings

    8.2. Historical Market Size (US$ Million) Analysis By Subscription Model, 2018 to 2022

    8.3. Current and Future Market Size (US$ Million) Analysis and Forecast By Subscription Model, 2023 - 2033

        8.3.1. Paid Services

        8.3.2. Free Services

    8.4. Market Attractiveness Analysis By Subscription Model

9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Industry

    9.1. Introduction / Key Findings

    9.2. Historical Market Size (US$ Million) Analysis By Industry, 2018 – 2022

    9.3. Current and Future Market Size (US$ Million) Analysis and Forecast By Industry, 2023 – 2033

        9.3.1. IT & Telecommunication

        9.3.2. BFSI

        9.3.3. E-commerce

        9.3.4. Healthcare

        9.3.5. Retail & Consumer Goods

        9.3.6. Energy & Utilities

        9.3.7. Others

    9.4. Market Attractiveness Analysis By Industry

10. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region

    10.1. Introduction / Key Findings

    10.2. Historical Market Size (US$ Million) Analysis By Region, 2018 to 2022

    10.3. Current and Future Market Size (US$ Million) Analysis and Forecast By Region, 2023 - 2033

        10.3.1. North America

        10.3.2. Latin America

        10.3.3. Europe

        10.3.4. East Asia

        10.3.5. South Asia Pacific

        10.3.6. Middle East and Africa

    10.4. Market Attractiveness Analysis By Region

11. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    11.1. Introduction

    11.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    11.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        11.3.1. By Scraping Type

        11.3.2. By Subscription Model

        11.3.3. By Industry

        11.3.4. By Country

            11.3.4.1. U.S.

            11.3.4.2. Canada

    11.4. Market Attractiveness Analysis

        11.4.1. By Scraping Type

        11.4.2. By Subscription Model

        11.4.3. By Industry

        11.4.4. By Country

    11.5. Market Trends

        11.5.1. Key Market Participants - Intensity Mapping

12. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    12.1. Introduction

    12.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    12.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        12.3.1. By Scraping Type

        12.3.2. By Subscription Model

        12.3.3. By Industry

        12.3.4. By Country

            12.3.4.1. Brazil

            12.3.4.2. Mexico

            12.3.4.3. Rest of Latin America

    12.4. Market Attractiveness Analysis

        12.4.1. By Scraping Type

        12.4.2. By Subscription Model

        12.4.3. By Industry

        12.4.4. By Country

13. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    13.1. Introduction

    13.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    13.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        13.3.1. By Scraping Type

        13.3.2. By Subscription Model

        13.3.3. By Industry

        13.3.4. By Country

            13.3.4.1. Germany

            13.3.4.2. Italy

            13.3.4.3. France

            13.3.4.4. U.K.

            13.3.4.5. Spain

            13.3.4.6. BENELUX

            13.3.4.7. Russia

            13.3.4.8. Rest of Europe

    13.4. Market Attractiveness Analysis

        13.4.1. By Scraping Type

        13.4.2. By Subscription Model

        13.4.3. By Industry

        13.4.4. By Country

14. South Asia & Pacific Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    14.1. Introduction

    14.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    14.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        14.3.1. By Scraping Type

        14.3.2. By Subscription Model

        14.3.3. By Industry

        14.3.4. By Country

            14.3.4.1. India

            14.3.4.2. Indonesia

            14.3.4.3. Malaysia

            14.3.4.4. Singapore

            14.3.4.5. Australia & New Zealand

            14.3.4.6. Rest of South Asia and Pacific

    14.4. Market Attractiveness Analysis

        14.4.1. By Scraping Type

        14.4.2. By Subscription Model

        14.4.3. By Industry

        14.4.4. By Country

15. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    15.1. Introduction

    15.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    15.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        15.3.1. By Scraping Type

        15.3.2. By Subscription Model

        15.3.3. By Industry

        15.3.4. By Country

            15.3.4.1. China

            15.3.4.2. Japan

            15.3.4.3. South Korea

    15.4. Market Attractiveness Analysis

        15.4.1. By Scraping Type

        15.4.2. By Subscription Model

        15.4.3. By Industry

        15.4.4. By Country

16. Middle East and Africa Market Analysis 2018 to 2022 and Forecast 2023 to 2033

    16.1. Introduction

    16.2. Historical Market Size (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022

    16.3. Current and Future Market Size (US$ Million) Forecast By Market Taxonomy, 2023 - 2033

        16.3.1. By Scraping Type

        16.3.2. By Subscription Model

        16.3.3. By Industry

        16.3.4. By Country

            16.3.4.1. GCC Countries

            16.3.4.2. Turkey

            16.3.4.3. South Africa

            16.3.4.4. Rest of Middle East and Africa

    16.4. Market Attractiveness Analysis

        16.4.1. By Scraping Type

        16.4.2. By Subscription Model

        16.4.3. By Industry

        16.4.4. By Country

17. Key Countries Analysis- Market

    17.1. U.S. Market Analysis

        17.1.1. By Scraping Type

        17.1.2. By Subscription Model

        17.1.3. By Industry

    17.2. Canada Market Analysis

        17.2.1. By Scraping Type

        17.2.2. By Subscription Model

        17.2.3. By Industry

    17.3. Mexico Market Analysis

        17.3.1. By Scraping Type

        17.3.2. By Subscription Model

        17.3.3. By Industry

    17.4. Brazil Market Analysis

        17.4.1. By Scraping Type

        17.4.2. By Subscription Model

        17.4.3. By Industry

    17.5. Germany Market Analysis

        17.5.1. By Scraping Type

        17.5.2. By Subscription Model

        17.5.3. By Industry

    17.6. Italy Market Analysis

        17.6.1. By Scraping Type

        17.6.2. By Subscription Model

        17.6.3. By Industry

    17.7. France Market Analysis

        17.7.1. By Scraping Type

        17.7.2. By Subscription Model

        17.7.3. By Industry

    17.8. U.K. Market Analysis

        17.8.1. By Scraping Type

        17.8.2. By Subscription Model

        17.8.3. By Industry

    17.9. Spain Market Analysis

        17.9.1. By Scraping Type

        17.9.2. By Subscription Model

        17.9.3. By Industry

    17.10. BENELUX Market Analysis

        17.10.1. By Scraping Type

        17.10.2. By Subscription Model

        17.10.3. By Industry

    17.11. Russia Market Analysis

        17.11.1. By Scraping Type

        17.11.2. By Subscription Model

        17.11.3. By Industry

    17.12. Rest of Europe Market Analysis

        17.12.1. By Scraping Type

        17.12.2. By Subscription Model

        17.12.3. By Industry

    17.13. China Market Analysis

        17.13.1. By Scraping Type

        17.13.2. By Subscription Model

        17.13.3. By Industry

    17.14. Japan Market Analysis

        17.14.1. By Scraping Type

        17.14.2. By Subscription Model

        17.14.3. By Industry

    17.15. South Korea Market Analysis

        17.15.1. By Scraping Type

        17.15.2. By Subscription Model

        17.15.3. By Industry

    17.16. India Market Analysis

        17.16.1. By Scraping Type

        17.16.2. By Subscription Model

        17.16.3. By Industry

    17.17. Malaysia Market Analysis

        17.17.1. By Scraping Type

        17.17.2. By Subscription Model

        17.17.3. By Industry

    17.18. Indonesia Market Analysis

        17.18.1. By Scraping Type

        17.18.2. By Subscription Model

        17.18.3. By Industry

    17.19. Singapore Market Analysis

        17.19.1. By Scraping Type

        17.19.2. By Subscription Model

        17.19.3. By Industry

    17.20. Australia and New Zealand Market Analysis

        17.20.1. By Scraping Type

        17.20.2. By Subscription Model

        17.20.3. By Industry

    17.21. GCC Countries Market Analysis

        17.21.1. By Scraping Type

        17.21.2. By Subscription Model

        17.21.3. By Industry

    17.22. Turkey Market Analysis

        17.22.1. By Scraping Type

        17.22.2. By Subscription Model

        17.22.3. By Industry

    17.23. South Africa Market Analysis

        17.23.1. By Scraping Type

        17.23.2. By Subscription Model

        17.23.3. By Industry

    17.24. Rest of Middle East and Africa Market Analysis

        17.24.1. By Scraping Type

        17.24.2. By Subscription Model

        17.24.3. By Industry

18. Market Structure Analysis

    18.1. Market Analysis by Tier of Companies

    18.2. Market Share Analysis of Top Players

    18.3. Market Presence Analysis

19. Competition Analysis

    19.1. Competition Dashboard

    19.2. Competition Benchmarking

    19.3. Competition Deep Dive

        19.3.1. Import.io

            19.3.1.1. Business Overview

            19.3.1.2. Scraping Type Portfolio

            19.3.1.3. Profitability by Market Segments (Business Segments/Region)

            19.3.1.4. Key Strategy & Developments

        19.3.2. Diffbot

            19.3.2.1. Business Overview

            19.3.2.2. Scraping Type Portfolio

            19.3.2.3. Profitability by Market Segments (Business Segments/Region)

            19.3.2.4. Key Strategy & Developments

        19.3.3. Zyte

            19.3.3.1. Business Overview

            19.3.3.2. Scraping Type Portfolio

            19.3.3.3. Profitability by Market Segments (Business Segments/Region)

            19.3.3.4. Key Strategy & Developments

        19.3.4. Mozenda

            19.3.4.1. Business Overview

            19.3.4.2. Scraping Type Portfolio

            19.3.4.3. Profitability by Market Segments (Business Segments/Region)

            19.3.4.4. Key Strategy & Developments

        19.3.5. Octoparse

            19.3.5.1. Business Overview

            19.3.5.2. Scraping Type Portfolio

            19.3.5.3. Profitability by Market Segments (Business Segments/Region)

            19.3.5.4. Key Strategy & Developments

        19.3.6. ScrapeStorm

            19.3.6.1. Business Overview

            19.3.6.2. Scraping Type Portfolio

            19.3.6.3. Profitability by Market Segments (Business Segments/Region)

            19.3.6.4. Key Strategy & Developments

        19.3.7. Kadoa

            19.3.7.1. Business Overview

            19.3.7.2. Scraping Type Portfolio

            19.3.7.3. Profitability by Market Segments (Business Segments/Region)

            19.3.7.4. Key Strategy & Developments

        19.3.8. Nimbleway

            19.3.8.1. Business Overview

            19.3.8.2. Scraping Type Portfolio

            19.3.8.3. Profitability by Market Segments (Business Segments/Region)

            19.3.8.4. Key Strategy & Developments

        19.3.9. Browse.ai

            19.3.9.1. Business Overview

            19.3.9.2. Scraping Type Portfolio

            19.3.9.3. Profitability by Market Segments (Business Segments/Region)

            19.3.9.4. Key Strategy & Developments

        19.3.10. Apiscrapy

            19.3.10.1. Business Overview

            19.3.10.2. Scraping Type Portfolio

            19.3.10.3. Profitability by Market Segments (Business Segments/Region)

            19.3.10.4. Key Strategy & Developments

20. Assumptions and Acronyms Used

21. Research Methodology

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