CUSTOMER SUPPORT

Turn Zendesk Tickets With No Matching Macro into Confluence Drafts

When a Zendesk ticket is solved without any macro applied, this workflow checks whether the same question keeps recurring and, if so, drafts a Confluence knowledge-base page…

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZendesk ticket solvedZendeskZendesk
  • LogicCheck whether a macro was applied
  • ActionSearch recent tickets for the same recurring questionZendeskZendesk
  • LogicBranch: stop if one-off, continue if recurring
  • ActionDraft a knowledge-base page from the threadOpenAI
  • OutputCreate draft Confluence page and assign docs ownerConfluenceConfluence

What it does

This workflow watches for solved Zendesk tickets that closed without an agent applying a macro, which is a reliable signal that no canned answer existed. It checks recent history to confirm the underlying question has shown up repeatedly, then drafts a Confluence page answering it and assigns review to your documentation owner. A counter in the page tracks how many tickets the gap has caused.

When to use it

Reach for this when macros are your team's source of truth and a ticket closing without one means a hole in coverage. It keeps your Confluence space growing in step with the questions customers actually ask, instead of relying on someone to remember to write docs.

How it works

  1. 1A Zendesk ticket-solved event triggers the run.
  2. 2Check whether any macro was applied to the ticket.
  3. 3If none, search recent solved tickets for the same question to confirm it recurs.
  4. 4Branch: stop if it is a one-off, continue if it recurs.
  5. 5Use OpenAI to draft a Confluence page from the ticket thread and the public reply.
  6. 6Create the page as a draft in Confluence and assign the docs owner to review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  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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