The Problem
Every sales team needs local business leads, but manually searching Google Maps and copying data is painfully slow. I needed a way to extract hundreds of leads in seconds.
What I Built
I built GMapsScraper AI — a tool thatuses AI to extract business data from Google Maps at scale.
Tech stack:
- Next.js 14 (frontend)
- Cloudflare Workers (deployment)
- Supabase (auth + database)
- Go-based scraper (backend on Google Cloud Run)
How It Works
- User enters a keyword + location (e.g. "dentist, New York")
- Backend spins up a headless browser to crawl Google Maps
- AI processes and structures the raw data
- Returns clean results: name, phone, email, website, rating, reviews
- One-click CSV export for CRM import
Key Technical Challenges
Rate limiting — Google Maps aggressively blocks automated requests. Solution: rotating proxies + randomized delays + browser fingerprint rotation.
Data accuracy — Raw scraped data is messy. Used AI to normalize phone formats, validate addresses, and deduplicate results.
Speed — Users expect results in seconds. Implemented parallel scraping with a job queue system to handle concurrent requests.
Results
- 200+ leads extracted per search
- Average response time under 30 seconds
- Supporting 18 languages and global locations
Try It
If you're building outreach tools or need local business data, check it out: gmapsscraper.io
Free trial available — no credit card required.
Top comments (11)
The part that stands out is how quickly these tools stop being “just a scraper” and become a full infrastructure problem.
One thing I’d keep in mind is where your app is doing repeated heavy work. If you’re generating previews, thumbnails, map screenshots, or other media assets as part of the workflow, it’s usually better to normalize and deliver those through a dedicated pipeline instead of making the app redo that work on every request.
That doesn’t solve Google’s rate limits, obviously, but it does keep the non-scraping parts of the system from becoming a second bottleneck. In these products, the boring delivery layer can end up being as important as the scraper itself.
Would be cool to have a Zapier integration so I can auto-trigger outreach sequences when new leads are exported. Any plans for that?
Good idea! We're considering Zapier and Make integrations. For now the CSV → HubSpot import workflow works well but direct API integration is on the roadmap.
Nice write-up! Curious about the proxy rotation strategy — are you using residential proxies or datacenter? I've been hitting rate limits with datacenter IPs when scraping at scale.
Started with datacenter but switched to a mix of residential + mobile proxies. The key is randomizing request intervals between 2-5 seconds and rotating user agents. Haven't been blocked since.
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