How to Scrape Google Maps at Scale: A Practical Data Pipeline Guide
Collecting a few Google Maps listings is easy. The engineering work starts when the same job has to run across dozens of cities, multiple business categories, and a recurring schedule. Take a project covering 30 cities and 10 categories. That already creates 300 search combinations before neighborhoods or alternate keywords are added. If the dataset needs to be refreshed every week, the job quickly moves beyond a one-time export. You have to keep searches consistent, track failures, avoid duplicate records, and make sure each run still looks like the last one.