Auto-Detect Customers Who Are About to Cancel Using Stripe + AI

Churn is the silent killer of subscription businesses.

Most founders find out a customer is unhappy only after they receive the cancellation notice. By then, it's usually too late to save them.

But customers rarely cancel on a whim. They leave "breadcrumbs" of dissatisfaction weeks or months in advance:

* Their usage drops.

* They stop logging in.

* Their credit card fails and they don't update it immediately.

* They visit your "Cancel Subscription" page (if you track that).

What if you could detect these signals automatically?

This guide shows you how to build a "Churn Early Warning System" using Stripe, Make.com, and AI.

The Logic: Defining "At Risk"

Before we automate, we need to define what a "Churn Risk" looks like for your specific business.

Common signals include:

Usage Drop: Login count dropped by 50% compared to last month.

Payment Hiccups: A failed payment that hasn't been retried.

Support Silence: A previously active user goes completely dark.

For this tutorial, we'll focus on a combination of Stripe Payment Failures and (optionally) Usage Data.

Step 1: Watching for Stripe Events

We'll use Make.com to listen to Stripe.

Module: Stripe > Watch Events.

Webhook: Set up a webhook in your Stripe dashboard to send data to Make.

Events to Watch:

* invoice.payment_failed: The most obvious sign.

* customer.subscription.updated: Watch for downgrades or cancellations scheduled for the future.

Seeing this in action makes a huge difference. Once configured, the interface provides a clear visual confirmation that your automation is running smoothly, giving you peace of mind that the system is working as intended.

Step 2: Analyzing the Customer Health

When an event triggers (e.g., a payment fails), don't just send a generic "Update your card" email. That's what everyone does.

Instead, use AI to analyze the customer's value.

The Workflow:

Get Customer Details: Retrieve the customer's total spend (amount_paid) and tenure (created date) from Stripe.

AI Analysis: Send this data to OpenAI (GPT-4).

* Prompt: "Analyze this customer. They have been with us for [X] months and spent $[Y]. Their latest payment failed. Classify their VIP status (High/Medium/Low) and draft a personalized outreach email based on their value."

Why AI Matters Here

A generic automated email is fine for a $10/mo user. But if a $500/mo enterprise client's card fails, you do not want a robot talking to them. You want the AI to alert you so you can call them.

Step 3: The "Usage Drop" Trigger (Advanced)

This is where the magic happens. If you have a SaaS app, you likely have a database.

You can set up a daily automation (using a Schedule trigger in Make) that runs a SQL query or API call to your app:

Find users where last_login_date > 30 days ago AND status = 'active'.* The Action:

For every user found:

Check Stripe: Are they still paying?

Draft Email: Have AI write a "checking in" email.

Tone:* Helpful, not salesy. "Hey [Name], noticed you haven't logged in for a while. Is there a feature you're stuck on?"

Alert You: Post a message to a dedicated Slack channel #churn-risk.

In practice, this approach transforms the way you handle daily tasks. Instead of getting bogged down in details, you can focus on the high-level strategy while the system handles the execution. Many solopreneurs find that this shift alone saves them hours of mental energy every week.

Step 4: The "Save" Playbook

When the system flags a user, what do you do?

For Low-Value Accounts:

* Trigger an automated email sequence (e.g., via ConvertKit or ActiveCampaign) offering a free 1-on-1 setup call to get them re-engaged.

For High-Value Accounts:

* Slack Alert: "🚨 VIP CHURN RISK: Acme Corp (LTV: $5,000) hasn't logged in for 21 days."

* Task Creation: Automatically create a task in your Todoist or Asana: "Call Acme Corp founder."

Real-World Example: The "Payment Failed" Opportunity

I used to send a generic "Payment Failed" email. It felt cold.

I changed it to an AI-drafted email that said:

"Hey [Name], noticed the card for [Product] didn't go through. No stress—I know cards expire. Since you've been with us for [X] years, I just wanted to make sure you didn't lose access..." Result: People replied apologizing and thanking me for the personal note. They updated their card immediately. The "personal" touch (even if automated) makes them feel valued, not processed.

This small adjustment can have a significant impact on your overall workflow efficiency. It turns a manual, error-prone process into a reliable, set-it-and-forget-it system.

Conclusion

You work too hard to acquire customers to let them slip away silently.

By connecting Stripe and your usage data to an AI monitoring system, you give yourself a superpower: Precognition. You can see the churn coming before it happens and intervene.

Next Step: Go to Stripe and look at your "Failed Payments" list. How many of those could have been saved with a personal touch?

* Start automating with Make.com

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Want to automate the sales side of your business too? Read our guide on Auto-Detecting Leads in Gmail.