How to Extract Data from Websites to Excel Automatically (Tutorial)

Posted on November 30, 2023
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Tired of your staff wasting countless hours pulling critical information from the internet–like contact information, shipping tracking, competitor pricing, data from portals, and more? While these tasks might seem simple, searching websites and portals and copying and pasting the information into Excel can quickly take up a lot of your team’s precious time. Plus, manually entering data into a spreadsheet is highly prone to human error. But with robotic process automation (RPA), you can streamline these repetitive tasks with automated data scraping from websites.

Automated data scraping collects data across many sources and pulls it into one spot—like an Excel spreadsheet—to eliminate errors and give you time back to work on more critical projects. Here are just some of the ways real companies are using automated data scraping:

  • Gathering contact information from an online portal
  • Price comparisons for competitive analysis
  • Monitoring real estate prices from MLS
  • Testing data for machine learning projects
  • Tracking shipments from UPS, FedEx, etc.
  • And many more!

How Web Scraping to Excel Works

automated data scraping to excel

Traditionally, web data extraction involves creating custom processing and filtering algorithms to grab structured data from a website or portal. Structured data is easy to search and group together and is easily stored in an Excel file. And once you have your data, you’ll need additional scripts–or an additional tool–to transport that data to Excel or other applications in your environment.

RPA simplifies Excel automation by providing one tool to scrape, extract, and write data directly into Excel, documents, reports, or other critical business applications. Using one tool, like Fortra’s Automate, eliminates the need for custom scripts and bloating your tech stack with more tools. Plus, bringing data extraction and transformation together in one tool practically eliminates errors by moving the information you need directly to where you need it.

Other Ways to Automate Excel

The most common way organizations automate Excel processes is through the use of VBA code. This is Microsoft’s programming language and is most commonly known as macros. Using Excel macros can increase efficiency and save time, but there are also several setbacks to be aware of. For starters, macros aren’t user friendly and require a fair amount of coding knowledge to set up automations. 

They are also increasingly complicated, and the more you share a spreadsheet, the more chances your business logic will be altered, rendering your macros useless. Plus, macros can be susceptible to viruses and can be a security risk to your business. Using an RPA tool eliminates these issues by providing a user-friendly, centralized, and secure way to automate Excel processes. 

7 Easy Steps for Data Scraping from Website to Excel

There are several ways to scrape data from a web page that involve creating custom processing and filtering algorithms for each site. These require you to write additional scripts or create a separate tool to integrate the scraped data with the rest of your IT infrastructure. But with the web scraping tool from Automate, you can easily take information from webpages and put it directly into an Excel sheet to analyze—all without writing any code.

In the video below, you’ll see an Automate bot running a task that enters UPS tracking numbers into the UPS website, performs automated data scraping to get delivery tracking information, and enters it into an Excel file. After the task runs, it goes on to show how that task was built. Watch and then try it yourself with this helpful, step-by-step tutorial.

 

In the video above, you’ll see an Automate bot running a task that enters UPS tracking numbers into the UPS website, performs automated data scraping to get delivery tracking information, and enters it into an Excel file. After the task runs, it goes on to show how that task was built. All but step 1 are shown in the video.

Step 1: Download an Automate trial

Step 2: Build the task by starting with variables. (If you need a basic primer on how to build Automate tasks, Automate Academy is a great place to learn.)  In this task, you’ll add variables for file names, rows, etc. Notice that this task builder is drag and drop, with no coding required!

automated_web_scraping_variables

Step 3: Open Excel workbook to get tracking numbers. You’ll store this as a dataset to use later on.

automated_web_scraping_excel_workbook

Step 4: Add a step to create a report workbook to write the dataset to.

automated_web_scraping_report_workbook

Step 5: Use the report workbook with tracking numbers and column headings in a web browser activity.

automated_web_scraping_workbook_tracking

Step 6: Identify which pieces of information you need. This will include telling the Automate bot where to find the data you want scraped. Put this on a loop to go through all the tracking numbers to do automated data scraping from the UPS website into Excel.

automated_web_scraping_data

Step 7: For each piece of data you want scraped from the website, write the variable value to a cell in the workbook.

automated_web_scraping_variable_value

 

This is just one example of Excel automation. There are so many other ways Automate and Excel can work together to take manual work off your plate.

FAQs about Automating Data Scraping from Websites and Putting the Data into Excel 

After identifying the data source (website and webpages), an RPA tool would be used to launch the website and inspect and select elements containing the desired data points, these could be table rows, divs, or specific classes/ids. Once the elements are identified, you would configure your RPA application to extract the relevant data from those elements.  

You may need to set up loops or conditions to scrape multiple data points or handle dynamic web content. As the data is scraped, store it in variables or datasets within the automation process, you may also need to manipulate the data after it has been successfully extracted.  

After all the required data is collected, use the RPA or automation tool’s Excel automation capabilities to create a new file or open an existing one and then write the scraped data into the Excel file in the appropriate cells and columns. Using specialized RPA tools will simplify this process. Fortra's Automate for example has a recorder specifically designed for UI automation that will automatically identify elements and pull in the underlying attributes by using Selenium to traverse the underlying HTML. Fortra's Automate also has both Excel and Open Document Spreadsheet capabilities to easily write scraped data into new or existing Excel documents even if Excel isn’t installed on the host machine the automation is executing from. 

It's essential to clarify that Excel Macros are a specific feature within Microsoft Excel, and they are not inherently designed for web scraping tasks. Instead, Excel Macros, also known as VBA (Visual Basic for Applications) macros, allow users to automate repetitive tasks within Excel itself. 

While Excel Macros can be used to scrape data from websites via VBA scraping, they are not the most suitable or efficient tool for web scraping tasks. VBA scrapers are highly dependent on MS Office tools and third-party useful scraping tools, like selenium for example, are hard to integrate with it and there is a steep learning curve as VBA programming language is less beginner-friendly and a bit harder than other modern programming languages. Excel Macros primarily focus on automating actions within Excel, such as formatting, calculations, and data manipulation, rather than web interactions and data extraction. 

If someone wishes to automate web scraping, it is more appropriate to use dedicated web scraping tools or RPA (Robotic Process Automation) tools. These tools are specifically designed for web automation and data extraction, and they offer better capabilities for navigating websites, locating specific elements, and extracting data in a structured manner. 

Yes, Excel can automatically update data from a website using various methods like: Web Queries (Web Queries in Excel), Power Query (Get & Transform Data), External Data connections, VBA (Visual Basic for Applications) Macros, and by using Add-ins and Third-party tools.  

Using RPA or automation tools instead of Excel for automatically updating data from a website offers several advantages, especially when dealing with complex or repetitive web scraping tasks: 

  • Advanced Web Automation: RPA tools are specifically designed for web automation tasks, making them more versatile and robust for web scraping. They can interact with web pages, navigate through dynamic content, and handle various user interactions like clicking buttons or filling forms. 

  • Multiple Data Sources: RPA can handle data extraction from multiple websites and various data sources simultaneously, allowing you to consolidate data from different websites into one centralized location. 

  • Data Transformation and Validation: RPA tools offer powerful data manipulation and validation capabilities. You can clean and transform the scraped data before updating it in Excel, ensuring data accuracy and consistency. 

  • Error Handling and Recovery: RPA tools come with built-in error handling mechanisms to deal with various issues that might arise during web scraping, such as website changes, connection errors, or timeouts. They can automatically retry or handle errors gracefully, ensuring a smoother data update process. 

  • Task Scheduling and Triggers: RPA tools provide scheduling features, allowing you to set up automatic data updates at specific intervals or based on predefined triggers. This enables you to keep the data in Excel up-to-date without any manual intervention. 

  • Scalability and Performance: For large-scale web scraping projects or scenarios with frequent data updates, RPA tools are better equipped to handle the load and deliver better performance compared to Excel macros. 

  • Security and Compliance: RPA tools often come with security features, such as encrypted credentials and secure data handling, ensuring that sensitive information is protected during the web scraping process. 

  • Integration with Other Systems: RPA tools can integrate with various applications and systems, making it easier to incorporate the scraped data into other processes or databases. 

  • Ease of Maintenance: RPA provides a visual, low-code or no-code approach to building automations, making it more accessible to business users and easier to maintain compared to complex VBA macros in Excel. 

  • Logging and Reporting: RPA tools typically offer extensive logging and reporting features, allowing you to monitor the web scraping process, track updates, and identify any issues that might arise. 

While Excel can be useful for simple web queries and basic data updates, RPA excels when dealing with more sophisticated web scraping scenarios that involve multiple websites, complex interactions, and automated data processing. It provides a comprehensive solution for automating the end-to-end process of web data extraction and integration into Excel or other systems, making it a preferred choice for many businesses and organizations. 

  1. Identify the HTML source containing the data you want to extract. This can be a webpage, an HTML file, or an element from a webpage. 

  1. Inspect the HTML structure of the data you want to extract. Identify the HTML tags, classes, or IDs that encompass the data you need. 

  1. Use automation or web scraping tools to extract the data programmatically. 

  1. Once you’ve extracted the data, store it in object such as variables or datasets. 

  1. From the created objects, export the data to Excel. 

Always respect the website's terms of service and avoid scraping personal or sensitive data without consent. It's also advisable not to overload a website with too many requests in a short time, which could cause it to slow down or crash. 

For web scraping, having a basic understanding of HTML is beneficial, but you don't need to be an expert. Knowing some essential HTML elements and their structure will help you identify the data you want to extract. Key HTML elements you should be familiar with include tags and attributes. Tags define the structure of the webpage and help you locate the data you want to scrape, and attributes provide additional information about the elements. These attributes are commonly used to pinpoint data for scraping. 

While some knowledge of HTML is helpful, using RPA for web scraping significantly reduces the technical debt associated with traditional programming. Here's why: 

  • No Low-level Coding: RPA tools often provide visual interfaces or low-code/no-code capabilities, allowing users with minimal programming experience to create web scraping workflows. This eliminates the need for in-depth knowledge of HTML or traditional programming languages. 

  • Built-in Web Scraping Features: RPA tools come with pre-built activities or actions specifically designed for web scraping. These activities handle the complexities of interacting with websites, extracting data, and handling dynamic content, reducing the need for manual coding. 

  • Ease of Maintenance: RPA workflows are typically easier to maintain than custom-coded solutions. If a website's structure changes, updating the web scraping process in an RPA tool can be done through visual adjustments rather than rewriting code. 

  • Rapid Development: RPA allows for rapid prototyping and quick deployment of web scraping automation. The development time is significantly reduced compared to traditional programming, which often requires more extensive planning and coding efforts. 

  • Reusability and Modularity: RPA workflows are designed to be modular and reusable. Once you create a web scraping automation workflow, you can easily use it for similar tasks on other websites, reducing duplication of efforts. 

  • Error Handling and Logging: RPA tools often include built-in error handling mechanisms and comprehensive logging capabilities, making it easier to monitor and troubleshoot web scraping processes. 

Potential Additional Items (if needed) 

Data scraping, or web scraping, is the process of extracting data from websites. It's useful in various scenarios, such as market research, sentiment analysis, data aggregation, and more. It automates the gathering of information that would be time-consuming and tedious to collect manually.

RPA is a technology that allows a software robot to mimic human actions to automate repetitive tasks. In data scraping, RPA can be used to automate the process of navigating websites, selecting, and copying data, then pasting it into an Excel sheet.

Fortra's Automate is an RPA solution that can be programmed to automate data scraping tasks. It allows users to create workflows where a bot navigates to specified websites, extracts relevant data, and places it into Excel, among other functionalities. 

Accuracy is ensured by correctly specifying what data to extract during the task creation. Periodically checking and validating a sample of the scraped data can also help ensure reliability.

Yes, Fortra's Automate is designed to handle tasks of various scales. It can automate data scraping from multiple websites or pages. Its performance will depend on the capabilities of the hardware it's running on and the complexity of the tasks.

Websites may block IP addresses if they detect unusual activity such as high frequency scraping. You can reduce the frequency of your requests, use a rotating proxy service, or contact the website's administrators to request permission for your activities.

Some common challenges include handling dynamic websites that use JavaScript or AJAX, dealing with websites that have anti-scraping measures in place, maintaining the accuracy of the extracted data, multi-factor authentication, and adhering to ethical and legal considerations around data privacy.

If RPA is not feasible, data scraping can be done manually, though this can be very time-consuming. There are also specific web scraping tools and libraries available in various programming languages. Finally, API access, if provided by the website owner, is a preferable method for extracting data from a site.

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