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The Better Business Bureau (BBB) maintains a large public directory of business profiles across the United States and Canada, where companies are listed together with ratings, contact information, and customer feedback. These listings provide structured details such as business names, locations, phone numbers, categories, and links to full company profiles that include BBB ratings and additional background information. In this guide, you will learn how to use Web Scraper to collect BBB business listings from search result pages and extract structured company data from both listings and profile pages without writing code. The extracted dataset can then be exported in CSV, Excel, or JSON format and used for business research, lead generation, competitive analysis, or building structured business directories.

Copart is a large online vehicle auction platform where thousands of cars are listed through searchable inventory pages. These pages display structured information such as vehicle titles, lot numbers, auction locations, current bids, sale status, and links to individual vehicle pages. In this guide, you will learn how to scrape Copart vehicle listings using Web Scraper and collect structured vehicle data directly from search result pages without writing code. The extracted data can be exported in CSV, Excel, or JSON formats and used for vehicle market analysis, auction monitoring, inventory research, or integration into other systems.

Trustpilot is one of the largest online review platforms, hosting millions of company profiles where customers share ratings and feedback about businesses across industries. Trustpilot company listings contain structured information such as company names, TrustScore ratings, review counts, categories, and links to company websites. In this guide, you will learn how to scrape Trustpilot company listings using Web Scraper and extract structured company data directly from category and listing pages without writing code. The collected data can be exported in CSV, Excel, or JSON formats for further analysis, reputation monitoring, market research, or integration into other systems.

DIY.com is the online store of the British home improvement retailer B&Q and offers a large catalogue of products across categories such as tools, building materials, kitchens, bathrooms, flooring, and garden equipment. Product listings on DIY.com contain structured information such as product names, prices, ratings, descriptions, images, and category data. In this guide, you will learn how to scrape DIY.com product listings using Web Scraper and extract structured product data directly from category pages and product detail pages without writing code. The extracted data can be exported in CSV, Excel, or JSON formats for further analysis, price monitoring, product research, or integration into other systems.

Amazon product listings can be accessed through both search results and category pages, where products are organised by keyword queries or product categories. These listing pages display structured information such as product titles, prices, ratings, and links to individual product pages. In this guide, you will learn how to scrape Amazon product listings using Web Scraper and extract structured product data from listing pages and product detail pages without writing code. The scraper can start from either an Amazon search results page or a category page and collect product information across multiple listings, with the extracted data exported in CSV, Excel, or JSON formats for further analysis, storage, or integration into other systems.

Amazon Bestsellers pages list the top-selling products within each category and are widely used to monitor product trends, analyse market demand, track competitors, and identify high-performing items. In this guide, you will learn how to scrape Amazon Bestsellers data using Web Scraper and extract structured product information directly from listing and product pages without writing code. The extracted data can be exported in CSV, Excel, or JSON for further analysis, storage, or integration into other systems.

Company directories on G2 list software vendors across a wide range of product categories and provide structured information about companies, ratings, and market presence. This data is often used to analyse software ecosystems, identify competitors, and build datasets of companies operating in specific technology segments. In this guide, you will learn how to scrape G2 company listings using Web Scraper and extract structured company data directly from directory pages without writing code. The extracted data can be exported in CSV, Excel, or JSON for further analysis, storage, or integration into other systems.

Rightmove is one of the largest online real estate platforms in the United Kingdom, used to explore homes for sale, rental properties, and housing market listings across different regions. Property listings on Rightmove contain structured information such as listing prices, property details, locations, images, and real estate agent information. In this guide, you will learn how to scrape Rightmove property listings using Web Scraper and extract structured real estate data directly from search result pages and property detail pages without writing code. The extracted data can be exported in CSV, Excel, or JSON formats for further analysis, real estate market research, price monitoring, or integration into other systems.

Realtor.com is one of the largest online real estate platforms used to explore homes for sale, rental properties, and housing market information across different locations. Property listings on Realtor.com contain structured information such as listing prices, property details, locations, images, and real estate agent information. In this guide, you will learn how to scrape Realtor.com property listings using Web Scraper and extract structured real estate data directly from search result pages and property detail pages without writing code. The extracted data can be exported in CSV, Excel, or JSON formats for further analysis, real estate market research, price monitoring, or integration into other systems.

Yellow Pages is one of the largest online business directories and is widely used to discover companies, local services, and contact information across industries and locations. Yellow Pages listings contain structured data about businesses, including company names, phone numbers, addresses, ratings, and service categories. In this guide, you will learn how to scrape Yellow Pages business listings using Web Scraper and extract structured business data directly from search result pages and business profiles without writing code. The extracted data can be exported in CSV, Excel, or JSON formats for further analysis, lead generation, market research, or integration into other systems.

Bypassing Cloudflare Turnstile captcha is not easy for DIY scrapers. Recently, Cloudflare has been upping its game by releasing innovative bot detection solutions that might feel undefeatable. Most bots are based on Chrome, and one of the best approaches to detect them is to check whether the browser is automated using Chrome Devtools Protocol (CDP). No regular Chrome user would have this protocol enabled, while 99% of bots will be using this to automate Chrome. Cloudflare came up with a new way to detect this by exploiting a bug in the Chrome browser, and Google is fixing it.

We are excited to announce a new version of the Web Scraper extension packed with AI-powered improvements, usability upgrades, and some important changes to how selectors work. This release focuses on making your most common use cases simpler while utilising AI tools for advanced data extraction scenarios.

In the world of web scraping and data collection, efficiency and precision are paramount. That's why we're excited about the new feature that is being added to Web Scraper functionality: Website State Setup. This feature you to execute conditional actions based on specific criteria, ensuring you collect the most relevant data.

New Update: Web Scraper 1.79.3

Web scraping enthusiasts and data aficionados, rejoice! The latest release of Web Scraper, version 1.79.3, brings several enhancements and fixes.

Exciting Updates Alert!

We're thrilled to announce some powerful features and enhancements in our latest Web Scraper update!

Check out what's new: