TICKET MANAGEMENT

Forecast aging Intercom conversations and open ClickUp follow-ups before they breach

Every 30 minutes, projects which open Intercom conversations will exceed first-response or resolution SLA based on reply cadence.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 30 minutes
  • ActionFetch open Intercom conversations with reply timestampsIntercomIntercom
  • LogicProject time-to-breach from reply cadence
  • LogicKeep conversations within warning window
  • ActionOpen or update ClickUp follow-up tasksClickUpClickUp
  • OutputPost at-risk list to SlackSlack

What it does

This workflow watches open Intercom conversations and forecasts which ones are drifting toward an SLA miss based on how their reply cadence is trending. Instead of waiting for the SLA timer to fire, it projects time-to-breach from the gap since last agent reply and the conversation's response history, then creates a tracked follow-up so nothing silently ages out.

When to use it

Use this when support runs in Intercom but work and accountability live in ClickUp, and conversations breach because they quietly stall between replies. It bridges the conversation and the task systems.

How it works

  1. 1A schedule fires every 30 minutes.
  2. 2Pulls open Intercom conversations with timestamps of last customer and agent messages.
  3. 3Projects each conversation's time-to-breach from reply cadence and the applicable SLA target.
  4. 4A branch keeps conversations forecast to breach within the warning window.
  5. 5Creates or updates a ClickUp follow-up task for each at-risk conversation with a deep link and deadline.
  6. 6Posts the at-risk conversation list to Slack for the team lead.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect IntercomConversations, contacts, articles.
  2. 2
    Connect ClickUpDocs + tasks + chats in one workspace.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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