Google Business Data Scraper

Budget 1k
No partial payments will be made. Payment will be made on project completion.

I need a reliable scraper that pulls business-level data directly from Google and drops it into a clean, csv file. The fields I must see in each row are: business name, full street address (including city, state, and postcode), primary contact information (phone and, when available, email or website), and the business category exactly as it appears on Google.

The script should accept a keyword category and a location, iterate through all returned listings—including those beyond the first page—and collect the data without tripping Google’s limits. Rotating proxies, user-agent switching, or any other anti-block techniques you prefer are fine as long as they keep the run stable, sessions are maintained for proper logging, and proper error handling.

Deliverables
• Python script or application tool
• Source code (Python preferred)
• Instructions to use document

Acceptance criteria
• Every search term tested returns all the listings with no duplicate rows
• proper error handling
• automate the scraping
• All required fields populate consistently; blanks appear only when Google genuinely omits the info
• Runtime finishes within a reasonable window for a 500-listing pull (roughly 5–10 minutes on a standard connection)
• optional ( check if the number is present on whatsapp or not )

If you already have a working Google Maps or Places scraping solution, feel free to adapt it—as long as it meets the field and reliability specs above.