How to Build a Scalable B2B Lead Scraping Pipeline Using Node.js and n8n

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A software engineer at SpaceAI360 has outlined an architecture for building production-grade web scraping pipelines aimed at B2B lead generation. The approach uses a dual-layer extraction strategy, routing simpler static pages through direct HTTP requests and dynamic JavaScript-heavy pages through headless browser automation to reduce unnecessary overhead. Responsible scraping practices are emphasized, including rate limiting, realistic request headers, adaptive delays, and reviewing robots.txt before targeting any site. Extracted data is then passed to n8n for normalization, optional LLM-assisted cleanup using models like Claude or Gemini Flash, and deduplication before being stored in a central database. The author argues that production resilience — handling timeouts, selector changes, and rate limits — matters far more than raw scraping speed.

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