CUSTOMER SUPPORT

Intercom Bot-Miss Topics to Linear Backlog

Daily, collects Intercom conversations the resolution bot failed to deflect, clusters the unresolved questions by topic.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule
  • ActionFetch bot-unresolved conversations from IntercomIntercomIntercom
  • LogicDrop conversations with no real question
  • ActionCluster questions into topics with outlinesOpenAI
  • LogicKeep clusters above volume threshold
  • OutputFile top gaps as Linear issuesLinearLinear

What it does

Measures where your Intercom resolution bot keeps failing and turns those misses into a concrete content backlog. It gathers conversations the bot could not resolve, clusters them into topics, and creates one Linear issue per high-volume gap with examples and suggested article scope.

When to use it

Run it daily when you rely on bot deflection and want to systematically expand the answers it can give. Best for teams tracking deflection rate who need a feedback loop into help content.

How it works

  1. 1A daily schedule starts the run.
  2. 2Intercom returns conversations from the last day where the bot did not resolve the question (handed off or abandoned).
  3. 3A filter drops conversations with no real question (spam, greetings only).
  4. 4OpenAI clusters the remaining questions into named topics with counts and a recommended article outline.
  5. 5A threshold step keeps only clusters above a minimum volume to avoid noise.
  6. 6Each qualifying cluster becomes a Linear issue tagged for the content team, with example conversation links.

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
    Connect LinearIssues, projects, cycles, triage.
  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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