Monitor customer churn indicators with Bright Data MCP and OpenAI
UnknownWhat this workflow does
This AI workflow has 14 nodes and runs on a schedule (every day at 09:00). Along the way it connects OpenAI Chat Model, OpenAI, Gmail and Mcp (community).
How it runs
Trigger: On a schedule (every day at 09:00).
- Set Admin Dashboard URL (Edit Fields (Set)): sets 1 field: database
- Scrape User Data (AI Agent) (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (Bright Data MCP Client); output parser: Auto-fixing Output Parser
- Format User Login Data (Code): runs custom JavaScript code
- Convert Date to Days Since Login (OpenAI): uses OpenAI
- Convert Days to Integer (Edit Fields (Set)): sets 1 field: message.content
- Check Inactive Threshold (>=30 days) (If): checks a condition and branches into true / false
- Send Re-engagement Email (Gmail): uses Gmail
Services it uses
Before you upgrade to n8n 3.0
We can't fully verify this one: it relies on 1 community package, and n8n 3.0 turns unverified community packages off by default (N8N_UNVERIFIED_PACKAGES_ENABLED=false).
- Check that n8n-nodes-mcp is verified or supports 3.0 (used in Bright Data MCP Client).
Nodes used (12)
- OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - AI Agent
@n8n/n8n-nodes-langchain.agent - Mcp Client Tool
n8n-nodes-mcp.mcpClientTool - Code
n8n-nodes-base.code - OpenAI
@n8n/n8n-nodes-langchain.openAi - If
n8n-nodes-base.if - Gmail
n8n-nodes-base.gmail - No Operation, do nothing
n8n-nodes-base.noOp - Auto-fixing Output Parser
@n8n/n8n-nodes-langchain.outputParserAutofixing - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured
From the author
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors customer churn indicators and early warning signals to help reduce customer attrition and improve retention rates. It…