How to verify lead domains and scrape metadata without paying SaaS credit markups (Python + n8n)

Описание и применение

Пайплайн без затрат, использующий Python и n8n, отфильтровывает неактивные домены, извлекает метаданные и генерирует открывающие фразы с помощью gpt‑4o‑mini, снижая расходы на 1 000 лидов до ~2 $.

Задача

Domain decay wastes 15–30% of scraped domains, burning paid enrichment credits on dead or parked domains.

Результат

The pipeline eliminates wasteful credit usage, reduces enrichment cost from ~$180/1k leads to ~$2, and provides contextual openers with minimal overhead.

Рабочий процесс

• Query Google DNS‑over‑HTTPS for MX records to validate domains.
• Drop domains with NXDOMAIN or no mail servers.
• For valid domains, fetch homepage title and meta description using Python’s urllib and regex.
• Feed the extracted metadata to gpt‑4o‑mini to generate contextual openers.
• Integrate steps into a self‑hosted n8n workflow for automation.

Доказательства

Between 15% and 30% of scraped domains are dead, parked, or expired.

Источник

Query Google’s public DNS-over-HTTPS API directly over standard port 443

Источник

For verified live domains, extract the homepage <title> and meta description in ~200ms using the pure Python standard library

Источник

Because the input payload is minimal, this drops enrichment costs from ~$180/1k leads down to just ~$2 in raw API tokens while generating contextual openers

Источник