Lead Data Scraper

Checkout My Build 009/500

I started building this lead data scraper because I wanted a less repetitive way to find businesses that could be a good fit for outreach. Manually searching through maps, opening websites, copying company names, and trying to find useful information about each business gets tiring very quickly.

I wanted to see if I could turn that entire process into one small system. The idea was simple: give it a list of business keywords, let it search a chosen location, collect the useful details, clean everything up, and return a spreadsheet that is ready for the next step.

The current version searches Google Maps using Playwright and collects the business name and website whenever they are available. It removes duplicate results before saving an untouched copy of the original data. After that, it visits each website and looks for extra signals such as the company’s LinkedIn page and an estimated team-size range.

Google Maps does not always return what I expect, so I added OpenStreetMap as a fallback. The automation also saves results in smaller batches while it runs, which means a long session does not have to become completely useless if something interrupts it halfway through.

It is still an early build. The location is currently configured for De Pijp in Amsterdam, and there are parts of the enrichment process I still want to improve. But it already turns a slow manual research process into a repeatable workflow that produces raw, batched, and consolidated CSV files.

This is exactly the kind of automation I want to document here: not something presented as magically finished, but a useful system that gets better every time I test it.