What is Screen Scraping and How Does it Work: A Complete Guide

We've all heard it before: we live in a data-driven world. Recent years have seen the power of data unleashed to staggering effect. Data has influenced major business decisions, revolutionized user experience, and facilitated transformative innovations. But there's an enormous amount of data out there. Finding, collating, and making sense of it is a challenging task. As such, data collection techniques such as screen scraping have grown increasingly popular. This blog will explore what screen scraping is, the benefits it can provide, and how it differs from other scraping methods.

Screen scraping is a technique used to extract data from websites or web applications. It automates navigating a user interface, interacting with its content, and extracting information from the HTML or other data displayed on the screen. Unlike data or web scraping, screen scraping primarily concerns extracting data visually displayed on a web page or user interface. It often involves emulating user interactions with a website to retrieve information.  

Crucially, screen scraping software simplifies automation and data collection for non-technical users. They offer intuitive interfaces, templates, step-by-step guidance, point-and-click interactions, data export, and cloud-based options. Moreover, users can access community support to use these tools without coding expertise.  

Screen scraping encompasses various techniques or methods used to extract data from the user interface of a website or application. These techniques can range from simple manual approaches to more complex automated processes. Here are the different methods used for screen scraping:  

• Manual Copy-Paste: The simplest screen scraping involves copying and pasting data from a webpage into a local document or application. This approach is suitable for small-scale tasks but is time-consuming and not automated.  

• Screen Capture: In this method, users take screenshots of the data they want to extract and then manually transcribe or use OCR (Optical Character Recognition) software to convert the image into text. It's manual and not suitable for large-scale data extraction.  

• Data Entry: Users may manually input data from webpages into another system or application. This can be tedious and error-prone, making it less efficient for larger scraping tasks.  

• XPath and CSS Selectors: These methods identify and extract specific elements on a webpage. XPath and CSS selectors are often used in web scraping tools and libraries to target HTML elements and extract data from them.  

• Regular Expressions (Regex): Regular expressions are used to find and extract specific patterns in text. While not specific to screen scraping, they can be applied to extract data from text displayed on web pages.  

• Headless Browsing: Headless browsers like Puppeteer (for Chrome) and Playwright enable automated web page interaction. They can navigate web pages, interact with web elements, and extract data from the rendered page. This method is more mechanical and programmable.  

• Web Scraping Tools: Various web scraping tools and software with user-friendly interfaces automate the screen scraping process. These tools often allow users to point and click to identify the data they want to extract and set up scraping tasks without writing code.  

• OCR (Optical Character Recognition): OCR software can convert text in images, such as scanned documents or screenshots, into machine-readable text. This method is useful when the data is available only as images.  

• APIs: Some websites provide APIs (Application Programming Interfaces) that allow developers to access structured data directly. This is a clean and efficient way to extract data when APIs are available.  

• Reverse Engineering: In cases where none of the above methods work, reverse engineering of the website's code or protocols may be used. This is a more complex and often legally questionable method.  

• RPA (Robotic Process Automation): RPA handles rule-based, repetitive tasks. Screen scraping is a subset of RPA where the tool interacts with the UI elements of an application, extracts data from screens, and automates user actions. Most RPA tools come with the OCR and API capabilities mentioned above. In essence, RPA software like Fortra’s Automate can navigate through applications just like a human would but at a faster rate and without errors. Scraped data can also be incorporated into broader automation workflows. 

• Machine Learning: Advanced techniques involving machine learning models can be used to train algorithms to recognize and extract data from images or unstructured text on web pages.  

However, problems may arise when scraping dynamic websites or web applications that use technologies like JavaScript, AJAX, or Single Page Applications. As such, screen scraping software must be capable of capturing the final view of the page or data point. Automate, for example, utilizes Selenium and can interact with elements; it can inject JavaScript to perform executions, read tabular data directly, and download the underlying source code to allow for parsing capabilities.

Screen scraping and web scraping are related techniques used to extract data from online sources, but they differ in scope and methods.  

First, let’s discuss how screen and web scraping differ in scope. Screen scraping primarily focuses on capturing data from a website or application's user interface or visual representation. It often involves emulating user interactions with the site to extract information as it's displayed on the screen. Web scraping, however, is a broader term that encompasses the extraction of data from the entire web page or website source code. It can include screen scraping but extends to capturing data from the underlying HTML, XML, JSON, or other structured data formats.  

Screen and web scraping also collect different data types. Screen scraping typically focuses on unstructured or semi-structured data visually displayed on the screen, including text, images, and links; web scraping deals with structured and unstructured data, such as tabular data, text, images, links, and more. It's not limited to what is visually presented on the screen.  

The two scraping methods also differ in how they utilize automation. While screen scraping often involves automation, it is more oriented toward capturing data as it's presented on the screen, which may include interaction with web elements and forms. For web scraping, however, automation is crucial. Web scraping can extract data from web pages without rendering them on a screen, making it suitable for large-scale data extraction.  

Screen scraping benefits include data extraction, automation for time-saving tasks, content aggregation, monitoring for alerts, competitive analysis, archiving, market research, data entry, testing, e-commerce tracking, historical analysis, UX testing, and automated reporting.  

Let's look a little deeper at benefits for specific use cases:   

• Data Extraction: Allows users to capture data from legacy systems or applications without APIs easily.  

• Automation: Screen scraping integrates disparate systems by automating UI-based workflows.  

• Testing: Automates UI tests for applications.  

• Competitive Analysis: Monitor competitors' sites for price changes, product additions, and more.  

• Content Aggregation: Compiles content from various sites for research or updates.  

And some general benefits:  

• Error Reduction: Screen scraping can significantly reduce the occurrence of errors compared to manual data entry. Human errors, such as typos, transpositions, and misinterpretation, are common when copying data from one system to another. Screen scraping automates this process, ensuring accuracy and consistency. This can be especially critical in industries where data accuracy is essential, such as finance and healthcare. 

• Time Savings: Screen scraping tools can extract data from web pages or applications at a much faster rate than a human operator. This automation can save a considerable amount of time in data retrieval and data entry tasks. This time can be reallocated to more valuable and strategic tasks, which leads to increased productivity and efficiency within an organization. 

• Productivity: By automating repetitive, manual tasks through screen scraping, employees can focus on more meaningful, strategic, and creative work. This can lead to a boost in overall employee productivity and job satisfaction. Employees can work on tasks that require problem-solving, critical thinking, and innovation, which can contribute to the growth and success of the organization. 

• Business Optimization: Screen scraping is not limited to data retrieval; it can also be used for competitive analysis, market research, and gathering insights from various sources. This information can aid in decision-making, identifying trends, and optimizing business strategies. By streamlining data collection and analysis, businesses can gain a competitive edge and respond quickly to changing market conditions. 

Here are ten specific screen scraping use cases:  

• E-commerce Price Monitoring: Retail businesses can use screen scraping to track product prices, discounts, and availability on competitor websites, enabling them to adjust their pricing strategies.  

• Real Estate Market Analysis: Real estate professionals can scrape property listing websites to gather data on property prices, locations, and market trends for analysis.  

• Social Media Sentiment Analysis: Marketers can scrape social media platforms to analyze user sentiments, reviews, and comments to gauge public opinion about products or brands.  

• Job Market Research: HR departments can scrape job posting websites to analyze market trends, including demand for specific skills and salaries.  

• News Aggregation: Media companies can use screen scraping to aggregate news articles from various sources, providing a comprehensive news feed for readers.  

• Financial Data Analysis: Finance professionals can scrape financial news websites to monitor news and events that may impact stock prices and market movements.  

• Competitive Pricing Analysis: In the hospitality industry, hotels and airlines can scrape competitor websites to compare room rates and ticket prices, adjusting their pricing accordingly.  

• Product Reviews and Ratings: Consumer electronics companies can scrape e-commerce and review websites to gather product reviews and ratings, helping to improve product features and quality.  

• Weather Data Collection: Meteorologists can scrape weather websites to collect historical weather data for climate and weather pattern analysis.  

• Healthcare Provider Comparisons: Patients and healthcare providers can use screen scraping to compare healthcare provider ratings, patient feedback, and services to make informed choices.  

Is screen scraping legal? 

• Legality can vary. Some websites explicitly prohibit scraping in their terms of service, making it a violation. Violating these terms could result in legal consequences. In some cases, screen scraping can be considered legal when it complies with applicable laws, respects the website's words, and doesn't harm the website or its users.  

How secure is screen scraping?   

• The security of screen scraping depends on factors such as the quality of the scraping tool or code, the frequency of scraping, and the website's defenses.  

• Responsible scraping involves respecting robots.txt files, using appropriate headers, and avoiding excessive or aggressive scraping to minimize security risks.  

• Some websites employ security measures to detect and block scrapers, making it essential to be aware of such defenses. 

How do you handle data storage and management after scraping data from websites?  

• Once the data is scraped, it can be:  

  • Stored in databases or cloud storage.  
  • Processed and transformed into a desired format.  
  • Integrated with other systems using APIs or direct data transfers.  


• Regulatory, source site compliance, copyrights and consent items should always be considered where applicable.  

What’s the difference between screen and API scraping? 

• Screen Scraping: 
  • Involves extracting data from a software application or web page's visual interface. 
  • Doesn't rely on structured data or APIs; it extracts directly from the visual presentation. 
  • Used when data isn't accessible through APIs or with legacy systems. 
  • Vulnerable to changes in UI design, which can make it less robust. 

• API Scraping (API Data Extraction): 
  • Involves interacting with structured data provided through APIs. 
  • Relies on documented, standardized endpoints and requests for data access. 
  • Preferred when dealing with systems that offer APIs offering structured data. 
  • More stable and less affected by UI changes, making it a more reliable approach. 

What’s the difference between screen scraping and OCR? 

• Screen Scraping: 

  • Screen scraping involves extracting data from a software application or web page's user interface (UI). 
  • It captures data from the visual presentation on the screen, including text, images, or other elements, and may involve simulating user interactions. 
  • It doesn't necessarily convert text from images but extracts data as it appears on the screen, whether in text or image form. 
  • Screen scraping is typically used to access data from various sources, such as websites, desktop applications, or virtual machines. 

• OCR (Optical Character Recognition): 

  • OCR is a technology designed to recognize and extract text from images or scanned documents. 
  • It converts printed or handwritten text found in images or scanned pages into machine-readable text. 
  • OCR is primarily used for processing physical documents, such as scanned papers, photographs, or handwritten notes, to extract and make the textual content available for further processing or storage. 
  • OCR is focused explicitly on transforming text within images into a format that can be edited, searched, or analyzed as text. 

In this example, see how Fortra’s Automate completes screen scraping from a desktop application and writes the data to an SQL database—all without any code. In this example, Automate will scrape data from invoices directly from a desktop-based accounting software.  Then you’ll see how Automate compiles the selected invoice data and imports it into an SQL database. 

Fortra’s Automate is an excellent tool for automated screen scraping. Automate is built for employee-driven, enterprise automation and features the right capabilities you need for including screen scraping in your automated workflows. With a user-friendly, no-code approach, everyone from citizen developers to power users can quickly build powerful automation using drag-and-drop capabilities. And a powerful API integration kit connects with the applications and systems that keep your business running, so you can automatically move the data you’re scraping right where it needs to go. Plus, take advantage of over 70 native actions to common applications like Microsoft, OCR, FTP, AWS, and more. 

What really sets it apart from other screen scraping tools is the Automate Recorder, a robust screen recorder that makes capturing real-life processes a breeze. With the recorder, quickly and easily build, accelerate, and distribute automation for both desktop and browser-based applications. Plus, seamlessly integrate programming logic and non-UI actions, like calling an API, for flexible, DIY automation. Pricing for Automate starts at $5,000 annually, with no limit to the amount of data you can scrape.