What is Web Scraping? How to Scrape Data from a Website?

Web scraping is the automated process of extracting data from websites, transforming unstructured or semi-structured web data into structured formats such as CSV or JSON.

This technique has gained significant attention due to the growing reliance on data for decision-making in various industries, including e-commerce, finance, marketing, and research.

Utilizing a reliable web scraping service can further increase the efficiency of the data extraction process. This is especially important for conducting market research, boosting lead generation for sales and marketing teams, and providing price monitoring for competitive retail and travel businesses.

What is web scraping and how to scrape a website seamlessly?

Get the detailed guide in this article!

What is Web Scraping?

Web scraping involves the use of software or scripts to collect and process information from websites. Unlike manual data collection, web scraping automates the extraction process, making it more efficient and scalable. The primary goal is to gather actionable insights or large datasets for analysis, research, or integration into applications.

Web scraping plays a key role in providing data for machine learning models, further advancing the advancement of artificial intelligence technology. By automating the data collection process and expanding the data to collect information from a variety of sources, web scraping helps create powerful, accurate, and well-trained artificial intelligence models.

Web scraping is particularly useful if the public website you want to obtain data from does not have an API, or only provides limited access to web data!

In this case, traditional methods cannot meet the needs, and leveraging external web scraping services such as Scrapeless may be a strategic approach. These services provide more efficient and scalable solutions. In addition, for those who are looking for advanced features, tools such as Scrapeless's API and Scraping Browser provide comprehensive solutions, providing features such as handling blocking, automatic browser operations, session and cookie management, and efficient data extraction.

And compared to other similar products, Scrapeless also provides cheaper prices while ensuring high stability. It relieves the cost burden for those companies with limited budgets but strong needs.

Learn more about how to keep stable web crawling!

How Does Web Scraping Work?

Web scraping is the process of automating the collection of unstructured and structured data. It is also widely known as web data extraction or web data scraping.

Some of the major use cases for web scraping include price monitoring, price intelligence, news monitoring, lead generation, and market research, among others.

Generally speaking, it is used by individuals and businesses who want to leverage publicly available web data to generate valuable insights and make smarter decisions.

Web scraping manually

If you have ever copied and pasted information from a website, you performed the same function as any web scraping tool, except that you performed the data scraping process manually:

1. Identify the target website
2. Collect the URLs of the target pages
3. Make requests to those URLs to get the HTML of the page
4. Use locators to find information in the HTML
5. Save the data as a JSON or CSV file or other structured format

It seems to be enough for daily web scraping. Unfortunately, if you need to extract data on a large scale, you need to deal with quite a few challenges.

For example, if the website layout changes, maintain data extraction tools and web crawlers, manage proxies, execute javascript, or bypass anti-bots. These are technical issues that consume internal resources.

At this time, we need to use more powerful automation tools - Web Scraper

Web scraper

Unlike the tedious process of extracting data yourself, web scraping uses machine learning and intelligent automation to retrieve millions or even billions of extracted data points from the internet.

1. Web scraping works by sending HTTP requests to a website and fetching its HTML content.
2. The script then parses the HTML structure to locate and extract specific data points using tags, attributes, or patterns.
3. Advanced methods can handle dynamic content rendered via JavaScript by simulating browser behavior using tools like Puppeteer or Selenium.

Whether you write a web scraper yourself or use a powerful web data extraction tool, you need to know more about the basics of web scraping or web data extraction!

Differences between Web Scraping and Web Crawling

Features	Web Scraping	Web Crawling
Goal	Extract specific data	Crawl web links and build content index
Scope	Focus on a small number of web pages and specific content	Crawl a large number of web pages
Technical complexity	Medium, mainly used for data analysis	High, need to manage link tracking and deduplication
Common tools	BeautifulSoup, Puppeteer, Scrapy	Scrapy, Apache Nutch, Selenium
Main applications	Data analysis, e-commerce price monitoring	Search engine indexing, SEO analysis

The web scraping

Web scraping is a focused process used to extract specific data from a web page and convert it into a structured format, such as CSV or JSON. The goal is to retrieve precise information, such as prices, reviews, or product details, for analysis or further use. Scrapers use tools like XPath, CSS selectors, or regex to locate and extract the desired data efficiently.

The web crawling

Web crawling, often referred to as "spidering," is an automated process of browsing the internet to index and collect web pages by following links. Crawlers are typically used to build large datasets or indexes, like those for search engines. In some projects, web crawling is a preliminary step to gather URLs, which are then processed by a web scraper to extract specific data.

2 Popular Web Scraping Methods to Scrape a Site

In order to give you a clearer understanding of how to scrape a website, we will now use 2 popular and powerful crawling tools: Scraping API and Scraping Browser to scrape Google Trends.

Scraping API

With the advanced Scraping API, you can easily access and scrape Google Trends data without writing or maintaining complex scraping scripts. Simply call the API we provide to quickly get all the information you need.

You can easily scrape Google Trends data categories like:

1. Interest over time
2. Compared breakdown by region
3. Interest by subregion
4. Related queries
5. Related topics

Let's see the detailed steps:

• Step 1. Log in to Scrapeless
• Step 2. Click the "Scraping API"

• Step 3. Find our "Google Trends" Panel and enter it:

• Step 4. Configure your data in the left operation panel:

• Step 5. Click the "Start Scraping" button and then you can get the result:

Or you can deploy our API to your own project like:

• Python

import http.client
import json

conn = http.client.HTTPSConnection("api.scrapeless.com")
payload = json.dumps({
   "actor": "scraper.google.trends",
   "input": {
      "keywords": "Mercedes-Benz,BMW X5",
      "geo": "",
      "time": "today 1-m",
      "category": "0",
      "property": ""
   },
   "proxy": {
      "country": "US"
   }
})
headers = {
   'Content-Type': 'application/json'
}
conn.request("POST", "/api/v1/scraper/request", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))

• Golang

package main

import (
   "fmt"
   "strings"
   "net/http"
   "io/ioutil"
)

func main() {

   url := "https://api.scrapeless.com/api/v1/scraper/request"
   method := "POST"

   payload := strings.NewReader(`{
    "actor": "scraper.google.trends",
    "input": {
        "data_type": "autocomplete",
        "q": "Mercedes-Benz"
    }
}`)

   client := &http.Client {
   }
   req, err := http.NewRequest(method, url, payload)

   if err != nil {
      fmt.Println(err)
      return
   }
   req.Header.Add("Content-Type", "application/json")

   res, err := client.Do(req)
   if err != nil {
      fmt.Println(err)
      return
   }
   defer res.Body.Close()

   body, err := ioutil.ReadAll(res.Body)
   if err != nil {
      fmt.Println(err)
      return
   }
   fmt.Println(string(body))
}

Scraping Browser

Requirements:

• Node.js: Ensure version 14 or above is installed.
• npm: Node package manager for handling dependencies.
• Scrapeless Browserless Service: Use the browser service provided by Scrapeless.

Then, please access the Scraping Browser dashboard, navigate to the "Settings" tab, and retrieve your API key.

Then, please follow our steps:

1. Install the necessary dependencies using:

npm install

1. Set Up Environment Variables

Create a .env file in the project root directory and add your API key as follows:

API_KEY=your_scrapeless_api_key

1. Customize Script Parameters

The script is pre-configured to fetch trends for "youtube" and "twitter" in the United States over the last 7 days. You can adjust the following settings:

• Keywords: Modify the q parameter in the QUERY_PARAMS variable to change the search terms.
• Geolocation: Update the geo parameter to set the desired location.
• Date Range: Adjust the date parameter based on the time period you want to analyze.

1. Set Cookies

To stabilize data related to changing interests over time, configure cookies using Puppeteer before visiting the website:

const cookies = JSON.parse(fs.readFileSync('./data/cookies.json', 'utf-8'));  
await browser.setCookie(...cookies);

To generate the cookies.json file, log in to Google Trends via your browser and export the cookies in JSON format. If you're unsure how to do this, consider using a browser extension designed for cookie export.

1. Execute the script using Node.js:

node index.js

What Can Web Scraping Used for?

Price Intelligence

Yes, price intelligence is the biggest use case for web scraping.

Extracting product and pricing information from e-commerce websites and then turning it into intelligence is a vital component of modern e-commerce companies looking to make better pricing/marketing decisions based on data.

Benefits of web pricing data and price intelligence:

• Dynamic pricing
• Revenue optimization
• Competitor monitoring
• Product trend monitoring
• Brand and MAP compliance

Market research

Market research is critical and should be driven by the most accurate information. With data scraping, you get access to high-quality, high-volume, high-insight web scraped data in all shapes and sizes that is driving market analysis and business intelligence around the world.

• Market trend analysis
• Market pricing
• Optimizing entry points
• Research and development
• Competitor monitoring

Financial alternative data

Uncover alpha and create value from the ground up with web data tailored for investors.

Decision making has never been smarter and data has never been more insightful - web scraped data is increasingly used by the world's leading companies given its incredible strategic value.

• Extract insights from SEC filings
• Assess company fundamentals
• Public sentiment integration
• News monitoring

Real Estate

The digital transformation of real estate over the past two decades has the potential to disrupt traditional businesses and give rise to powerful new players in the industry.

By incorporating real estate data scraped from the web into daily operations, agents and brokerages can fend off top-down online competition and make smart decisions in the market.

• Assess property values
• Monitor vacancy rates
• Estimated rental yields
• Understand market direction

News and content monitoring

Modern media can create outstanding value or an existential threat to your business in a single news cycle.

If your company relies on timely news analysis, or is a company that is frequently in the news, then web scraping news data is the ultimate solution to monitor, aggregate, and parse the most important news in your industry.

• Investment decisions
• Online public opinion analysis
• Competitor monitoring
• Political campaigns
• Sentiment analysis

Lead generation

Lead generation is a critical marketing/sales activity for all businesses.

In a 2024 Hubspot report, 65% of inbound marketers said that generating traffic and leads is their biggest challenge. Fortunately, web data extraction can be used to get structured lists of leads from the web.

Brand Monitoring

In today's competitive market, protecting your online reputation is a top priority.

Whether you sell products online and need to enforce a strict pricing policy, or you just want to know how people view your products online, brand monitoring using web scraping can provide you with that information.

Business Automation

In some cases, accessing data can be cumbersome. Maybe you need to extract data from your own or your partners' websites in a structured way.

But there's no easy way to do this in-house, so it's a smart move to create a scraping tool and scrape the data directly. Rather than trying to figure it out with complex internal systems.

MAP Monitoring

Minimum Advertised Price (MAP) monitoring is a standard practice to ensure that a brand's online prices are consistent with its pricing policy.

Manually monitoring prices is impossible due to the large number of dealers and distributors.

That's why web scraping is so convenient because you can easily keep an eye on the prices of your products.

How to Scrape a Website for Free?

There are a variety of free web scraping solutions available for automatically scraping content and extracting data from the web. These solutions range from simple point-and-click scraping solutions for non-professionals to more powerful, developer-centric applications with extensive configuration and management options.

Scraping API and Scraping Browser will become the most powerful tools that are in line with the development of the Internet society. They have built-in web unlocker, proxy and CAPTCHA .etc, making your web scraping more convenient and faster.

Only simple configuration operations are required to get the most accurate data immediately.