This n8n workflow automates the process of monitoring email campaign performance, analyzing data with AI, and facilitating targeted follow-ups to boost engagement. The workflow starts with a scheduled trigger set to run daily at 9 AM, ensuring consistent performance tracking without manual intervention. It then defines necessary input parameters such as campaign URL and date range. An AI agent scrapes live campaign reports from the ESP using Bright Data MCP, processes the data with GPT-4 to generate summaries, and extracts key metrics like open rates and click-through rates.

Based on these metrics, the workflow makes decisions: if open rates are high (≥30%) but click-through rates are low (<10%), it automatically sends a personalized follow-up email via Gmail to re-engage recipients who opened but did not click. If no action is needed, it gracefully ends. This automation allows marketers to continually optimize their email campaigns by leveraging AI insights and targeted communication, all without manual effort. Ideal use cases include routine campaign monitoring, behavioral re-engagement strategies, and data-driven marketing optimization.

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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, gmail, if, n8n-nodes-mcp.mcpClientTool, noOp, scheduleTrigger, set, stickyNote