Automated Data Scraping from Google Maps Using NITN Workflow: A Practical Demonstration

Data scraping from Google Maps can be streamlined using the right automated workflow. A recent demonstration showcases how NITN (or NITM) can be utilized to efficiently extract location data with minimal manual intervention.

The system demonstrated revolves around a simple yet effective process. It begins with a Google Sheet interface where users can paste a URL from Google Maps. This action triggers a NITN workflow that handles the entire scraping process.

Once activated, the workflow leverages Serp API to collect the data. It intelligently processes the information by identifying and handling errors, removing empty values, and transforming the data into the appropriate format. The final step involves publishing the processed information back to the Google Sheet in a dedicated results tab while updating the status to “success.”

In the demonstration, a search was conducted for parks in Little Rock, Arkansas. After copying the Google Maps URL and pasting it into the designated field in the Google Sheet, the workflow was manually triggered using the “Test Workflow” option (though it’s normally scheduled to run hourly).

The system then executed multiple processing loops – running through cycles approximately 30 times to ensure comprehensive data collection. As the process completed, the workflow merged the collected data and automatically populated the results tab of the Google Sheet.

When comparing the results before and after the operation, what was initially only 77 entries expanded significantly to include comprehensive information about parks in Little Rock. The final data set contained location details organized in a structured format, ready for analysis or further processing.

This automated approach to Google Maps data extraction demonstrates how specialized tools can transform what would otherwise be a tedious manual process into an efficient, systematic workflow with minimal user intervention required.