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Curious Context Labs

Customer service · Automation

Sentiment and churn-risk alerts

AI churn-risk alerts from customer conversations

Reads support conversations for frustration and cancellation signals, and alerts the account owner while there is still time to fix things.

01 today

The problem

Customers rarely announce they are about to leave. The signs are scattered across support tickets, emails and chats: a sharp tone, a repeat complaint, a question about notice periods. By the time the cancellation arrives, the account owner is hearing about the problem for the first time.

02 the run

What the AI does

  1. Step 1: Reads new tickets, chats and emails in Zendesk, Intercom and Gmail as they arrive.
  2. Step 2: Scores the tone of each conversation and picks out specific risk signals, such as mentions of competitors, cancelling, contracts or repeated unresolved issues.
  3. Step 3: Combines those signals with account details from HubSpot, Salesforce or Stripe, such as plan size, renewal date and recent payment problems.
  4. Step 4: Sends a short alert to the account owner in Slack with the reason, the quotes behind it and a suggested next step.
  5. Step 5: Adds a weekly roll-up of at-risk accounts and common complaint themes for the support and account leads.

paused: waiting for a person to approve

03 human in the loop

Where a person approves

Alerts only inform. The account owner decides whether to call, offer help or leave it, and no message goes to the customer without a person writing or approving it.

04 after

What changes

Account owners hear about unhappy customers while the relationship can still be saved. Leaders see which problems are driving frustration instead of finding out from cancellation emails.

Results from a real build

[CASE STUDY] We only publish results we can name and check with the client.

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Working with teams in the United States, United Kingdom and Australia.