Building Lead Scraper in Public: Week 1 Update

What we're building and why

Every B2B salesperson knows the pain of list building. You need qualified leads — specific companies, specific location, verified contacts. The current workflow: search Google Maps manually, find a business, hunt for an email, copy it to a spreadsheet, repeat 200 times. Hours to build a list you'll use once.

We're building Lead Scraper — a no-code engine that does this automatically. Define your search criteria, it pulls leads, verifies emails, de-duplicates against previous exports, and produces a clean CSV in minutes.

The technical approach

Google Maps is our primary source — the most structured public directory of local businesses on the planet. Every listing has a name, location, category, phone, and often a website URL. From the URL, we extract email addresses using our scraping layer, then pass every email through verification to check deliverability.

Stack: Python for scraping, Playwright for JS-heavy pages, PostgreSQL for storage and de-duplication, Next.js for the UI.

What we've built so far

The Google Maps scraper works. Tested against 500 searches across 12 business categories and 8 cities. Data quality is high — clean names, addresses, phones, and website URLs in about 94% of results.

Email verification is live and integrated. Of emails extracted, roughly 68% verify as deliverable — a good ratio for raw web data. The rest are catch-all addresses or defunct domains. We mark them separately rather than dropping them.

What's still being built

LinkedIn integration is the next milestone. The data is harder to pull cleanly due to rate limiting. We're working through the right approach — sustainable and within platform terms.

After LinkedIn, we build the dashboard UI. Right now the engine runs from the command line. The UI makes it accessible to non-technical users, which is 90% of our target market.

When can you get access?

Q3 2026 beta. The waitlist is open. Early access gets a discounted rate locked in for life.