Analyze support tickets for churn signals in minutes

Upload or paste your support tickets → instantly uncover hidden churn signals, at-risk user patterns, and the friction driving customers away

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Example insights from support tickets

Billing Frustration Spike
"I've been charged twice this month and no one has responded to my last two tickets. I'm seriously considering canceling."
Onboarding Drop-Off
"I still don't know how to connect my data source after two weeks. If I can't get this working soon, it's not worth it."
Feature Gap Driving Exits
"We switched from your competitor specifically for the reporting tools, but they're too limited for what we need. We may have to go back."
Repeated Unresolved Issues
"This is the fourth time I've submitted a ticket about the same sync error. Nothing changes and I'm running out of patience."

What teams usually miss

Churn signals buried in ticket volume

When hundreds of tickets come in weekly, the quiet but urgent frustrations of high-value customers get lost in the noise before anyone can act on them.

Repeat complainers who never escalate

Customers who submit the same issue multiple times without threatening to cancel are often the most likely to churn silently, and manual review rarely catches the pattern.

Cross-ticket themes that reveal systemic risk

Individual tickets look like isolated problems, but when analyzed together they reveal product gaps, broken workflows, or support failures that are pushing an entire customer segment toward the exit.

Decisions you can make from this

Prioritize outreach to customer segments submitting repeat tickets about the same unresolved issue before they cancel without warning.

Escalate accounts that mention competitors, switching, or cancellation language in tickets to your customer success team for immediate intervention.

Identify which product features or workflows generate the highest churn-risk ticket volume and fast-track them on the roadmap.

Redesign your onboarding flow for the specific steps where new users submit the most frustrated early-lifecycle tickets.

How it works

  1. 1Upload or paste your data
  2. 2AI groups similar feedback into themes
  3. 3Each insight is backed by real user quotes

Analyze your support tickets and catch churn signals before it's too late

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