Predict tenant churn and manage retention with GPT-4, Gmail, Slack and your CRM
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 18 nodes and runs on a schedule (every day at 08:00). Along the way it connects OpenAI Chat Model, Gmail and Slack.
How it runs
Trigger: On a schedule (every day at 08:00).
- Workflow Configuration (Edit Fields (Set)): sets 6 fields: tenantApiUrl, serviceRequestApiUrl, feedbackApiUrl…
- Fetch Tenant Data (HTTP Request): calls an HTTP API
- Fetch Service Requests (HTTP Request): calls an HTTP API
- Fetch Feedback Data (HTTP Request): calls an HTTP API
- Merge Tenant Intelligence (Edit Fields (Set)): sets 3 fields: tenantData, serviceRequests, feedbackData
- Tenant Analysis Agent (AI Agent): runs an AI agent, with model: OpenAI GPT-; output parser: Analysis Output Parser
- Check Churn Risk Level (If): checks a condition and branches into true / false
- High Risk Communication Agent (AI Agent): runs an AI agent, with model: OpenAI GPT-4 for Communications; 2 tools (Gmail Tool, Slack Tool)
- Low Risk Engagement (Edit Fields (Set)): sets 2 fields: emailSubject, emailBody
- Update CRM (HTTP Request): calls an HTTP API (POST)
…plus 2 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (10)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - HTTP Request
n8n-nodes-base.httpRequest - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - If
n8n-nodes-base.if - Gmail Tool
n8n-nodes-base.gmailTool - Slack Tool
n8n-nodes-base.slackTool - Gmail
n8n-nodes-base.gmail
From the author
How It Works Automates daily tenant analytics, churn risk evaluation, and proactive retention by unifying tenant data from multiple sources, applying GPT-4–based risk scoring, detecting early churn indicators, routing high-risk tenants to retention…