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Churn Risk Detector

Example prompt: "Every Monday, pull last week's support tickets from our tracking sheet. Use AI to identify customers who had multiple tickets, negative sentiment, or unresolved issues. Email me a summary of at-risk accounts."

The Problem

Customers rarely announce they are about to leave. Instead, the warning signs are scattered across support tickets — repeated contacts about the same issue, increasingly frustrated language, tickets that were closed but never truly resolved. Support teams see individual tickets but miss the pattern, and by the time account managers hear about the problem, the customer is already shopping for alternatives.

How GloriaMundo Solves It

We build a weekly workflow that pulls recent support ticket data and analyses it for churn signals. A code step groups tickets by customer and calculates frequency and resolution rates. An LLM step then reviews the grouped data, assessing sentiment from ticket descriptions and identifying patterns like repeat contacts, escalations, or long resolution times. Customers flagged as at-risk are compiled into a summary report and emailed to the account management team. Glass Box preview shows you the full analysis before any emails go out, so you can verify the risk assessments make sense.

Example Workflow Steps

  1. Trigger (schedule): Runs every Monday morning.
  2. Step 1 (integration): Read the past week's support tickets from Google Sheets, including customer name, ticket subject, status, and resolution notes.
  3. Step 2 (code): Group tickets by customer. Calculate per-customer metrics: ticket count, percentage unresolved, average time to resolution.
  4. Step 3 (LLM): Analyse each customer's ticket history for churn indicators — negative sentiment, repeated complaints, unresolved issues. Assign a risk level (low, medium, high) with a brief explanation.
  5. Step 4 (conditional): If any customers are rated medium or high risk, proceed to notification.
  6. Step 5 (LLM): Draft a concise summary email listing at-risk customers, their risk level, key issues, and suggested follow-up actions.
  7. Step 6 (integration): Send the summary email via Gmail to the account management team.

Integrations Used

  • Google Sheets — source of support ticket data
  • Gmail — delivers the weekly churn risk report

Who This Is For

Account managers, customer success leads, and support directors at SaaS or subscription businesses who want early warning when a customer relationship is deteriorating, before it shows up as a cancellation.

Time & Cost Saved

Manually reviewing ticket histories across customers to spot churn patterns could take 2-3 hours per week, and most teams simply do not do it at all. This workflow surfaces at-risk accounts automatically, giving account managers a head start on retention conversations. Even catching one at-risk customer early can justify months of running this workflow.