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Predict Customer Churn with AI Analysis of HubSpot and Google Sheets Data

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Created by: PollupAI || zeerobug

PollupAI

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Last update 11 hours ago

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Who it’s for

Built for Customer Success and Account Management teams focused on proactive retention. This workflow helps you automatically identify at-risk customers – before they churn – by combining CRM, usage, and sentiment data into one actionable alert.

What it does

This end-to-end workflow continuously monitors customer health by consolidating data from HubSpot and Google Sheets.
Here’s how it works:

  • Fetch deals from HubSpot.
  • Collect context — linked support tickets and feature usage from a Google Sheet.
  • Run sentiment analysis on the tickets to generate a customer health score.
  • Evaluate risk — an AI agent reviews deal age, sentiment score, and usage trends against predefined thresholds.
  • Send alerts — if churn risk is detected, it automatically sends a clear, data-driven email to the responsible team member with next-step recommendations.

How to set it up

To get started, configure your credentials and parameters in the following nodes:

  1. Credentials:
    • HubSpot: Connect your account (HubSpot: Get All Deals).
    • LLM Model: Add credentials for your preferred provider (Config: Set LLM for Agent & Chains).
    • Google Sheets: Connect your account (Tool: Get Feature Usage from Sheets).
    • Email: Set up your SMTP credentials (Email: Send Churn Alert).
  2. Tool URLs:
    • In Tool: Calculate Sentiment Score, enter the Webhook URL from the Trigger: Receive Tickets for Scoring node within this same workflow.
    • In Tool: Get HubSpot Data, enter the Endpoint URL for your MCP HubSpot data workflow. (Note: This tool does call an external workflow).
  3. Google Sheet:
    • In Tool: Get Feature Usage from Sheets, enter the Document ID for your own Google Sheet.
  4. Email Details:
    • In Email: Send Churn Alert, change the From and To email addresses.

Requirements

  • HubSpot account with Deals API access
  • LLM provider account (e.g. OpenAI)
  • Google Sheets tracking customer feature usage
  • n8n with LangChain community nodes enabled
  • A separate n8n workflow set up to act as an MCP endpoint for fetching HubSpot data (called by Tool: Get HubSpot Data).

How to customize it

Tailor this workflow to match your business logic:

  • Scoring logic: Adjust the JavaScript in the Code: Convert Sentiment to Score node to redefine how customer scores are calculated.
  • Alert thresholds: Update the prompt in the AI Chain: Analyze for Churn Risk node to fine-tune when alerts trigger (e.g. deal age, score cutoff, or usage drop).
  • Data sources: Swap HubSpot or Google Sheets for your CRM or database of choice — like Salesforce or Airtable.

Outcome: A proactive customer health monitoring system that surfaces risks before it’s too late — keeping your team focused on prevention, not firefighting.