Maps Lead Extractor.

Local lead research is manual, repetitive, and slow.

Every sales team pulling local business data from Google Maps hits the same wall — a day per geography, a week per region, a month per country. The data is public; the friction is time.

The extractor automates the friction layer so the operator only has to think about the strategy: which geographies, which keywords, what depth.

A small CLI. A SerpAPI call. A clean CSV.

The tool is a small Python CLI. The operator supplies a geography and keyword; the tool paginates through SerpAPI results and writes an enriched CSV with everything the sales team needs — business name, address, phone, website, category, rating, review count.

Configurable depth (10 to 500+ results per query) and environment-based credentials mean it drops cleanly into any sales workflow without touching a UI.

Non-obvious decisions.

• Rate-aware pagination — the tool knows SerpAPI quotas and never blows the budget on a single run.
• Resume logic — if interrupted, it resumes from the last successful page rather than re-fetching the whole set.
• Deterministic output — same geography + keyword = same CSV, so downstream processes can diff reliably between runs.

Why this one matters.

A sales team that used to spend a week on local lead research runs this tool in ten minutes. The product is the embodiment of my philosophy: find the repeatable bottleneck in your client's workflow, then write a small, sharp tool that removes it.