What is data scraping?

Data scraping is the process of extracting specific data in a structured form from publicly available websites or online sources. Legitimate use cases of data scraping include collecting business intelligence, making price comparisons, identifying sales leads, or conducting market research.

But data scraping can also be used for malicious purposes. Fraudsters and hackers use data scraping to steal information or disrupt traffic to a certain website. There are numerous ethical concerns surrounding data scraping, and it can contravene laws and regulations relating to privacy rights and copyright infringement.

If your business is considering using data scrapers, or if it already does, then you need to know how to go about the practice in a legal and ethical manner. Even if you’re not interested in data scraping, you still need to protect your online business from black hat data scrapers. In this article, you can find all the information you need about the positive benefits and possible pitfalls of data scraping.

Key Takeaways

• Data scraping is the process of extracting structured data from publicly available websites.
• E-commerce websites use data scraping for marketing or research purposes.
• The act of data scraping is not illegal, but how data is collected and used may violate international laws and regulations.
• Hackers use data scraping to steal sensitive corporate and personal data.
• Chrome extensions and Python libraries like Beautiful Soup and Scrapy can be combined with machine learning algorithms to create sophisticated data scraping pipelines.
• The Data Scraping Tools market was valued at US $2,711 million in 2022 and is projected to be worth US $12,970 million by 2029.

A Quick Explanation of Data Scraping

Data scraping refers to transferring specific structured data output from one digital source to another. More generally, data scraping describes the large-scale extraction of specific structured data from websites, social media platforms, or online databases. Once a user has extracted data, it is saved in a structured format like an Excel sheet or as a JavaScript Object Notation (JSON) or CSV file.

Data scraping is a precisely targeted technique used to collect specific text-based data. Since it is so targeted, data scraping differs from web scraping, which is used to collect unstructured data from the HTML structure of web pages, screen scraping which simulates human activity, and content scraping which is used to collect unstructured or semi-structured content from websites.

Data scraping can be done purely for personal use, such as extracting product information and pricing from e-commerce websites to find the best deal. Academics and researchers scrape news articles from various sources for sentiment analysis and collect public data from government websites for research purposes. Businesses use data scraping for market analysis, customer sentiment analysis, and price comparisons. A company may scrape real estate listings from property websites for market analysis or extract user reviews for product analysis.

What are the business benefits of data scraping?

Online businesses are heavily dependent on leveraging data analytics to stay competitive. Across all industry sectors worldwide there is a huge demand for both raw and processed data. Major companies such as Amazon and Microsoft even facilitate this practice by implementing application programming interfaces (APIs) specifically built for price scraping their websites.

The key advantages of data scraping for businesses include:

Fast, High-Yield Results

Obtaining large amounts of data via traditional methods—like interviews, focus groups, and surveys, or by analyzing published reports or internal documents—is time-consuming and labor-intensive. Businesses are increasingly using automated data scraping techniques to gather valuable information from a wider array of sources. Data scraping is faster and more cost-effective than traditional methods and still yields high-quality, reliable data.

Effective Marketing & Customer Monitoring

Companies collect data about how competitors are performing, customer preferences, and current market trends for use in market research and competitor analysis. Data scraping is an effective way to monitor how marketing campaigns for brands or products are performing on social media or review sites. Scraping reviews and comments is an effective method of customer sentiment analysis.

Accurate Price Comparisons

Price monitoring is another common use of data scraping. Some companies use data scraping to monitor competitor pricing while others scrape data to populate price comparison websites. In the e-commerce sector, data scraping is also sometimes used to transfer product data from e-commerce websites to platforms like Amazon or Google Shopping.

Targeted Lead Generation

Analyzing data scraped from B2B sources like industry-specific websites, directories, or networks can be a highly useful way of generating new leads. Companies can filter results through an automated analytical model to find prospects that most closely match their intended target markets.

Easier Content Generation

In some cases, a business may use scraped data to aggregate content from multiple sources to create content-rich websites. This practice must be done ethically and with care not to violate terms of service, breach privacy laws, or infringe copyright.

Is data scraping a legal activity?

Data scraping is not illegal in and of itself, and there are no laws that specifically prohibit data scraping. However, that doesn’t mean that scraping data from a website is a completely legitimate act. There are numerous legal and ethical aspects to consider when it comes to data scraping. The legality of data scraping depends on the method used to scrape the data, what data is scraped, and how the scraped data is used.

In some cases, data scraping activities can contravene international data safety and privacy laws. For instance, collecting data from a website that specifically prohibits such an activity in its Terms of Service (TOS) is illegal, as is the unauthorized collection and use of copyrighted or proprietary content and personal data or sensitive information without explicit consent from the data holder. Using scraped content without permission can infringe on the intellectual property rights of the content creators or copyright holders.

It is illegal to use scraped data for malicious purposes. This includes practices like overwhelming a server with data scrapers or using email scraping to create spam and phishing lists.

It’s worth noting that price scraping can be seen as highly unethical. When a business uses price scraping to undercut their competitors and distort the market it can be viewed as participating in unfair business practices.

Even if this type of information is gathered unintentionally, it could still be in violation of international laws and regulations such as:

• The Computer Fraud and Abuse Act (CFAA)
• The California Consumer Privacy Act (CCPA)
• The General Data Protection Regulation (GDPR)
• The UK Data Protection Act (UK GDPR)

Always be cautious when data scraping. Best practices are only to scrape publicly available information, don’t overload a site with automated requests, always follow a site’s TOS, and be sure to only scrape data from unrestricted site areas.

Common Data Scraping Techniques

Data scraping can be performed manually, but it’s difficult and time-consuming. The process is usually done by dedicated automated software or scripts known as data scrapers.

There are three steps involved in a data scraping workflow:

1. A scraper bot issues an HTTP GET request to the target website.
2. When the bot receives a response, it parses the requested HTML document for the specific data patterns it is looking for.
3. The data is extracted and converted into the desired format.

Although this seems simple, implementing data scraping and web crawling algorithms can be complex. Common data scraping techniques include:

• HTML Parsing: Software tools or libraries like Beautiful Soup or Scrapy built with languages such as Python read and interpret a website’s HTML code to extract data from specific HTML tags.
• Document Object Model (DOM) Parsing: Data scrapers use a DOM parser to view the hierarchy of a target website and identify what elements to scrape data from.
• XPath: XPath is an acronym for XML Path Language. It is a query language that data scrapers use to navigate and select nodes or elements from XML or HTML documents. XPath is often used in conjunction with Beautiful Soup and DOM parsing.
• API Access: APIs provide controlled and authorized access to a website’s data. API parsing is seen as a more ethical and regulated method of data scraping.
• Vertical Aggregation: A company with sufficient processing power can use the vertical aggregation method to scrape data. Vertical aggregation platforms are cloud-based data harvesting platforms that generate bots to scrape data from targeted verticals. Vertical aggregation can repeatedly scrape large amounts of data over a specific period from multiple sources.
• Google Sheets: A popular way of simply scraping data, Google Sheets has an IMPORTXML function that can be used to extract data. This function can also verify if a website has been scraped or has sufficient protection from data scrapers.

Can data scraping harm a business website?

A data scraping attack can be used to steal sensitive corporate or personal information, which can then be used in spam attacks or for phishing campaigns. Hackers can also use scraped data to create a fake website that steals payment information from potential customers or sells inferior goods. This is known as ‘website spoofing’. Website spoofing and duplicated content can negatively impact rankings on search engines.

Repeated requests from data scrapers put huge pressure on a website’s servers. Legitimate users may experience slower response times from the site. The site may even experience a distributed denial of service (DDoS) attack due to data scraping requests and go offline. Scraping attacks can uncover security weaknesses that leave the target site vulnerable to data breaches or other cyber threats.

A business may experience loss of credibility and damage to its reputation because of data scraping. Customers may view the site as untrustworthy, unsafe, or poorly managed.

But you don’t have to put your business at the mercy of hackers and fraudsters. There are numerous ways you can protect your website from malicious data scrapers.

How to Protect Your Website from Malicious Data Scrapers

The first step to protecting yourself from a web scraper is to limit the amount of transferable data on your website. You can do this by restricting the number of requests an IP address can make to your website. An API with set rate limits and usage policies can control access to your data and ensure it is only used for legitimate purposes. Implementing CAPTCHAs and dynamic web content on your site can also stop or slow down bot attacks.

Have a TOS document visible on the site that specifically limits rate requests and prohibits data extraction. The site’s robots.txt file should also contain specific information about data collection.

DataDome can protect your site from web scraping bots. DataDome’s advanced AI-driven detection system evaluates each incoming request within 2 milliseconds and accurately analyzes client-side and server-side signals. Our industry-leading technology has a false positive rate of less than 0.01%. Threats are blocked in real-time before any data can be scraped from data sources.

DataDome has been used to ward off scraping attacks and web crawlers by respected IT companies such as Softvoyage and SuperTravel, and major retailers like Kurt Geiger. We were also instrumental in uncovering a major attack against Facebook.

FAQS

Is data scraping a common activity for businesses?

Yes. Companies use data scraping to gather information on competitor pricing, market insights, customer reviews, and contact information for lead generation. Data scraping is also used for market research, price monitoring, and data analysis.

Is data scraping always done for legitimate purposes?

No. Malicious fraudsters and hackers use sophisticated web scraping tools, automation, browser extensions, machine learning, and proxies to access data sets without authorization. This can include scraping personal information without consent, stealing copyrighted content, or extracting data from websites in violation of their terms of service.

How can I protect my website from data scrapers?

Update your website’s terms of service to prohibit or limit data scraping. Use CAPTCHA or other verification methods to deter bots. Implement IP blocking or user agent blocking. Deploy specialized software solutions like DataDome to protect against web scraping.

Can I use software to detect and prevent data scrapers?

Yes. DataDome is a highly effective solution for detecting and preventing scraping efforts. With a false positive rate of less than 0.01%, DataDome is one of the most accurate, reliable, and powerful bot and online fraud protection tools currently available.