How to spot churn signals in Gorgias tickets

In a subscription store, most cancellations are preceded by a support ticket that did not say “cancel”. A late box. A damaged jar. A question about why the price went up. A request to skip, then another skip. Each one is handled, closed and forgotten, and two months later the subscription ends.

This guide shows how to use Gorgias’s built-in signals (intents, sentiments, managed ticket fields, tags and the customer timeline) to see those patterns, and how to check which ones actually come before cancellations in your store. It relies on Gorgias’s documentation: intents and sentiments, customer sentiments, ticket fields, rules, customer history, helpdesk performance reports, the tags report and exporting tickets (all accessed November 2026). For handling the cancellation itself, see subscription cancellations in Gorgias.

The signals that matter in subscription commerce

These are hypotheses to test, not rules:

Signal	Example	Gorgias source
Delivery problems	Late, lost or damaged box	Intents such as Order/Damaged, Shipping/Status
Product disappointment	“Didn’t like this flavour”	Negative sentiment, Contact Reason
Repeated skips or frequency changes	Third skip in a row	Subscription intents, tags
Price questions	“Why was I charged more?”	Contact Reason, tags
Threats to leave	“I’ll buy elsewhere”	Threatening sentiment
Repeat contact	Same issue, several tickets	Customer timeline

Intents and sentiments: free, automatic labels

Gorgias detects intent and sentiment on incoming messages automatically (intents and sentiments). If it cannot assign one confidently, it leaves it blank.

Intents describe what the customer wants. Gorgias’s list includes subscription intents (such as subscription/cancel and subscription/change), order intents (such as Order/Damaged, Order/Wrong and Order/Cancel), Shipping/Status, and refund, return and exchange requests.

Sentiments describe how they feel. Gorgias’s sentiments page documents, among others:

• negative: general dissatisfaction with a product or the service;
• threatening: the customer threatens legal action, buying elsewhere or a negative review;
• urgent: impatience after several unsuccessful contacts, or an urgent need such as cancelling an order before it ships.

For churn, “threatening” is the most direct signal: “I’ll buy elsewhere” is a cancellation in waiting. “urgent” after repeated contacts says your support is losing the customer, whatever the original problem was.

Turn them into tags with rules

Intents and sentiments are visible on messages, but tags are easier to report on. Gorgias rules can add tags based on detected intents and sentiments. Use ticket created or new message as the trigger: Gorgias notes that “ticket updated” does not fire on intent changes. For example:

1. WHEN new message, IF message sentiments contain “threatening”, THEN add tag risk-threat and set priority high.
2. WHEN ticket created, IF intents contain Order/Damaged, THEN add tag risk-delivery.

Tags are case-sensitive in Gorgias, so agree on one spelling.

Contact Reason: the human label

Gorgias’s managed ticket fields include Contact Reason, Resolution and Product, with suggested dropdown values you can edit. Gorgias can pre-fill Contact Reason with AI once it has enough labelled history. Its advice is to describe what the customer sees (“Delayed shipment”), not the internal cause (“Warehouse problem”).

Contact Reason and Product together answer a question intents cannot: which product generates the most disappointment. Make sure agents confirm the field before closing a ticket.

Repeat contact: the customer timeline

Gorgias’s customer timeline shows a customer’s tickets alongside their Shopify orders (for Shopify stores). The sidebar shows a ticket count and previews the three most recent tickets.

Make it a habit for agents: when a customer has several recent tickets, open the timeline before replying. Three tickets about late deliveries in two months is a customer about to leave, even if each ticket was “resolved”.

Where to look: Analytics

Gorgias’s helpdesk performance reports let you track tags, ticket fields and intents over time and break them down by store, channel or agent. The tags report shows the 10 most used tags for the period, a trend chart and a full table you can export as CSV; you can choose whether the date range applies to when the tag was added or when the ticket was created.

A monthly review:

1. Trend of risk- tags and of negative and threatening sentiment.
2. Contact Reason by Product: which products drive complaints.
3. Resolution on subscription tickets: how many ended in a cancellation versus a skip or swap.

Checking signals against real cancellations

Gorgias shows you what customers talk about. Only your subscription data shows who left. To connect them:

1. Export tickets. From a view, you get ticket data such as tags, subject and timings; from the Analytics drill-down you can export with message content for the most recent 30 days of the period (exporting tickets).
2. Export subscriptions from your subscription app: customer email, start date, cancellation date and reason if captured.
3. Join on email. For each subscriber who cancelled, list their tags and Contact Reasons in the 90 days before. Do the same for a similar group who did not.
4. Compare. Keep the signals that show up clearly more often before cancellations. Show counts with every percentage; a pattern in eight customers is a lead, not a fact.

Our guide on finding what predicts churn covers the method, including why correlation is not cause.

What to do when you see a signal

• Delivery problem: fix it and say so. A replacement or credit on the second problem often matters more than the first.
• Product disappointment: offer a swap if your subscription app supports it.
• Repeated skips: suggest a slower frequency instead of another skip.
• Threat to leave: answer the complaint itself, promptly, from a person.
• Clear cancellation request: cancel. Do not use signals as a reason to delay.

Common mistakes

• Too many tags. Ten risk- tags nobody applies consistently are worse than three that everyone trusts. Start small and add only when a new signal proves useful.
• Treating sentiment as a verdict. AI-detected sentiment is a hint. “This is killing me, I love it” can read as negative. Agents should correct obvious errors.
• Counting tickets, not customers. One very vocal subscriber can produce ten negative tickets. Report signals per customer as well as per ticket.
• Ignoring the quiet ones. Many subscribers cancel without ever opening a ticket. Support signals cover only the customers who talk to you; usage, skips and failed payments cover the rest.
• Reviewing once and forgetting. Signals change with seasons, products and prices. Repeat the comparison every quarter.

Doing this with NoChurn

NoChurn’s Gorgias connector is read-only: it reads tickets and never adds tags, replies or runs actions in Gorgias. Tickets are matched to your customers by email; doubtful matches are suggested for you to confirm and never merged automatically. They feed a churn score from 0 to 100 and a churn drivers view that ranks attributes by correlation with churn, and are kept as dated, verbatim evidence for disputes on Stripe and Braintree. Intents, rules, fields and Analytics stay in Gorgias. See NoChurn + Gorgias.