This n8n workflow automates the process of monitoring competitor product launches through scraping, analysis, and alerting. Scheduled to run every morning at 7AM, it targets review pages like The Verge, leveraging Bright Data’s web scraping services combined with AI-powered extraction via OpenAI models. The workflow begins with setting the target URL for reviews, then uses Bright Data’s MCP (Managed Cloud Proxy) to scrape product details such as titles, release dates, and summaries, bypassing anti-bot measures.

The AI agent processes the scraped content to generate structured data, which is then split into individual review items. For each product review, personalized emails are sent to the R&D team with the product details, and the review entries are logged into a Google Sheet for record-keeping and future analysis. This automation is ideal for competitive intelligence teams tracking new product launches efficiently without manual effort, ensuring timely alerts and organized data collection.

The workflow includes detailed annotation notes for setup and customization, making it accessible for users to adapt to different competitor sites or data points. It combines web scraping, AI data processing, email notifications, and data logging into a seamless automation pipeline.

Node Count	11 – 20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserAutofixing, @n8n/n8n-nodes-langchain.outputParserStructured, code, gmail, googleSheets, n8n-nodes-mcp.mcpClientTool, scheduleTrigger, set, stickyNote