CUSTOMER SUPPORT

Front Escalation to Linear Churn-Risk Ticket

When a Front conversation shows repeated frustration, it opens a Linear churn-risk ticket with the thread summary and root-cause hypothesis so product and support can act before…

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFront conversation tagged or updatedFront
  • ActionJudge sustained frustration across threadOpenAI
  • LogicBranch: repeated frustration, not one-off?
  • ActionSummarize and hypothesize root causeOpenAI
  • ActionCreate churn-risk issue in LinearLinearLinear
  • OutputComment Linear link back on Front threadFront

What it does

Detects when a single Front conversation has tipped into sustained frustration, not just a one-off bad day, and turns it into a tracked Linear issue. The ticket carries a plain-language summary, the suspected root cause, and a link back to the Front thread, so escalations become work items instead of lost emails.

When to use it

Use it when frustrated customers signal product or process problems that support alone can't fix. It routes the escalation to the team that owns the fix and keeps a paper trail for churn reviews.

How it works

  1. 1A Front conversation is tagged or updated, firing the trigger.
  2. 2The full thread is pulled and an LLM judges whether frustration is sustained across multiple replies.
  3. 3A branch filters out single-message venting and keeps repeat-frustration threads.
  4. 4The model writes a summary plus a root-cause hypothesis from the conversation.
  5. 5A Linear issue is created in the churn-risk project with labels and the Front permalink.
  6. 6The Front conversation is commented with the Linear link to close the loop.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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