What is Web Scraping? — SimpleCrawl Glossary

Definition

Web scraping is the automated extraction of data from websites. Instead of manually copying information from web pages, scraping software sends HTTP requests to target URLs, downloads the HTML response, and parses it to extract specific data points. The extracted data is then stored in a structured format like JSON, CSV, or a database for further analysis.

Web scraping is sometimes called web harvesting, web data extraction, or screen scraping. While the term is often used interchangeably with web crawling, scraping specifically refers to the data extraction step, whereas crawling refers to the broader process of discovering and navigating pages.

How Web Scraping Works

A typical web scraping workflow follows these steps:

1. Send a request — The scraper sends an HTTP GET request to a target URL, just like a browser would when you visit a page.
2. Receive the response — The server returns HTML, which contains the page content, styles, and structure.
3. Parse the HTML — The scraper uses an HTML parser to build a document tree from the raw markup.
4. Extract data — Using CSS selectors, XPath expressions, or regular expressions, the scraper locates and pulls out specific data points like prices, titles, or contact information.
5. Store the results — Extracted data is saved in a structured format for analysis, reporting, or feeding into other systems.

Modern scraping often requires handling JavaScript-rendered content using headless browsers, managing rate limits, rotating proxies, and respecting robots.txt directives.

Web Scraping in Web Scraping

Web scraping is foundational to virtually every data extraction workflow on the internet. Common use cases include:

• Price monitoring — E-commerce companies track competitor pricing across thousands of product pages.
• Lead generation — Sales teams extract business contact information from directories and social platforms.
• Market research — Analysts gather data from review sites, forums, and news outlets to spot trends.
• AI training data — Machine learning teams collect large text datasets to train language models.
• RAG pipelines — Developers scrape documentation and knowledge bases to build retrieval-augmented generation systems.
• SEO monitoring — Marketers track search rankings, meta tags, and backlinks across competing sites.

The rise of large language models (LLMs) has made web scraping more important than ever. LLMs need vast amounts of clean, structured text data, and web scraping is the primary way to collect it at scale.

How SimpleCrawl Handles Web Scraping

SimpleCrawl turns web scraping into a single API call. Instead of building and maintaining scraping infrastructure, you send a URL to our API and receive clean, structured data back in seconds.

Here's what SimpleCrawl handles for you:

• JavaScript rendering — Pages that rely on client-side rendering are fully loaded in headless browsers before extraction.
• Proxy management — Automatic proxy rotation prevents IP blocks and ensures reliable access.
• Output formats — Get results as clean markdown (ideal for LLMs), structured JSON, or raw HTML.
• Rate limit compliance — Built-in throttling respects target site limits and keeps your scraping ethical.
• Robots.txt awareness — SimpleCrawl checks and respects robots.txt by default, with options to configure behavior.

Whether you're building a RAG pipeline, monitoring prices, or extracting leads, SimpleCrawl abstracts away the complexity so you can focus on using the data.

Related Terms

• Web Crawling — The process of discovering and navigating web pages
• HTML Parsing — Transforming raw HTML into a structured document tree
• Headless Browser — A browser without a GUI used for rendering JavaScript
• CSS Selectors — Patterns used to target specific HTML elements