Web & Data Scraping​

Improve Web-Scraping processes with Robotic Process Automation (RPA)

Retrieving relevant information from multiple websites is often used to collate relevant data from various sources. This process is often manual and can lead to several challenges:

  1. Manual Data Extraction: The traditional method of manually extracting data from websites is time-consuming and prone to errors due to laborious processes.
  2. Data Accuracy: With RPA, the risk of manual handling errors in data extraction is significantly reduced, ensuring the reliability and accuracy of the information collected. This assurance of data accuracy is a crucial benefit of implementing RPA for web-scraping.
  3. Data Volume Handling: Dealing with large volumes of data manually can be overwhelming and inefficient, leading to delays and reduced productivity. However, with RPA, this process becomes efficient and simplified, relieving your team from the burden of manual data volume handling.
  4. Timely Data Updates: Manually keeping relevant information up to date requires constant monitoring and updating, which can be challenging to maintain consistently.

By leveraging RPA for web-scraping, businesses have been able to combat the abovementioned issues related to the website data extraction process. In the next section, we will provide real examples of the benefits our customers experienced with implementing RPA for Website Scraping.

Web Scraping is made easy with RPA.

Web Scraping can be time-consuming and open to the many issues described above. 

RPA is a technology that automates repetitive and rule-based tasks. It uses intelligent software robots that mimic human actions to extract data points from defined websites using automated actions. Businesses that utilise web-scraping have observed the following advantages:

Automated Data Extraction

  • Automated Data Extraction
    RPA automates data extraction processes by deploying bots to navigate predefined websites, locate relevant information, and extract data. This ensures that organisations can efficiently and on time collect data from diverse online sources without manual intervention.
  • Scalable Data Collection
    Streamlining data collection at scale is a challenge. RPA addresses this by enabling organisations to deploy bots simultaneously scraping data from multiple websites. Whether it is product information, market trends, or competitor insights, RPA ensures scalability in data collection.
  • Data Accuracy and Consistency
    Manually scraping data can lead to inconsistencies in the retrieved data. RPA bots, with their rule-based precision, ensure accuracy in data extraction. Organisations can rely on consistent and error-free data, which is crucial for making informed business decisions.
  • Real-time Data Monitoring
    RPA contributes to real-time data monitoring by automating live data retrieval from websites. Whether monitoring stock prices, social media trends, or news updates, RPA bots ensure that organisations have access to the latest information for timely decision-making.
  • Structured Data Output
    Raw data from websites can be unstructured and challenging to interpret. RPA processes the scraped data into a pre-designed structured format that meets your needs and specifications. This structured output simplifies data analysis and integration with internal systems.
  • Customized Data Filters
    Organisations often require specific subsets of data. RPA allows the implementation of custom filters, ensuring that only relevant information is extracted. Whether refining data based on keywords, dates, or categories, RPA enhances the precision of data scraping.
  • Secure and Ethical Scraping
    Compliance and ethical data scraping are vital. RPA ensures that data scraping processes adhere to legal and ethical standards. Bots can be programmed to respect website terms of use, privacy policies, and other regulatory requirements.

Case Studies of RPA implementation 

In the Utilities industry, a company encountered difficulties extracting data from websites for analysis. The process involved manually copying and pasting data into spreadsheets, which was time-consuming and prone to errors. RPA was implemented to automate the data extraction process. The RPA bots were programmed to scrape data from websites and enter it into spreadsheets automatically. The bots were also trained to filter and process the data as required. The implementation of RPA resulted in a significant reduction in processing time from hours to minutes. The accuracy of the data also improved, reducing the number of errors and the need for manual intervention. 

In the Aerospace industry, a company whose core business was pilot training realised that its training and exam material was being copied by its competitors. To build their case against these offenders, RPA was used to audit, compare, and extract unique identifiers from the competing databases and provide evidence of the offence.

In essence, RPA assists with optimising Web & Data Scraping by automating the extraction of valuable insights from the web and documents, allowing organisations to stay competitive in the data-driven landscape.

Contact SmartTechNXT for a free consultation to explore how RPA can be tailored to enhance your Data Scraping practices.