CUSTOMER SUPPORT

Detect a bug spike across users and post a proactive status banner

Watches Intercom conversations for a sudden cluster of tickets describing the same new problem.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Intercom conversation receivedIntercomIntercom
  • ActionSummarize message into a symptom signatureOpenAI
  • LogicCount matching signatures in rolling window vs threshold
  • LogicOnly proceed if cohort crosses threshold and no banner is live
  • OutputPublish proactive status banner to usersIntercomIntercom

What it does

It continuously samples incoming support conversations, groups them by the symptom they describe, and detects when an unusual number of users hit the same brand-new issue. Once a cohort forms above your threshold, it publishes a proactive in-app status banner so the next wave of affected users sees an acknowledgement instead of opening a ticket.

When to use it

Run this when a regression or outage tends to generate dozens of near-identical tickets before anyone notices the pattern. It turns a flood of duplicate contacts into one acknowledged incident, cutting first-response load and reassuring customers.

How it works

  1. 1New Intercom conversations arrive on a webhook trigger.
  2. 2An OpenAI step normalizes each message into a short symptom signature.
  3. 3A logic step counts matching signatures inside a rolling time window and checks the cohort against your threshold (for example 8 users in 15 minutes).
  4. 4If the threshold is crossed and no banner is already live, it composes a customer-safe message.
  5. 5It posts the banner back through Intercom so affected users self-deflect.

Set it up

What you configure once, before turning it on.

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

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