CUSTOMER SUPPORT

Weekly top-gaps digest from Zendesk to Slack

Each Monday, ranks the past week's recurring unanswerable questions across Zendesk and posts a prioritized digest to Slack so the docs owner can pick what to write next.

CategoryCustomer Support
Enginesim
Difficultybeginner
Triggerschedule
Steps6
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly Monday schedule
  • ActionFetch last 7 days of Zendesk ticketsZendeskZendesk
  • ActionFlag unanswered tickets and extract questions (OpenAI)OpenAI
  • LogicGroup into themes; rank by frequency and priority
  • ActionDraft the top-10 gaps digest (OpenAI)OpenAI
  • OutputPost the ranked digest to SlackSlack

What it does

This workflow gives your team a weekly readout of where the documentation is failing customers. It pulls the past seven days of Zendesk tickets, uses an LLM to identify which questions were never satisfactorily answered, ranks the recurring themes by volume and customer impact, and posts a ranked top-ten digest to a Slack channel with ticket counts and example links.

When to use it

Use it for a standing weekly ritual — a docs standup or support sync — where someone decides what to write next. It complements real-time logging by giving leadership a digestible, prioritized view instead of a raw backlog. Best when your team lives in Slack.

How it works

  1. 1A weekly schedule fires every Monday morning.
  2. 2Zendesk returns the trailing seven days of tickets with tags and resolution status.
  3. 3An OpenAI step flags tickets that closed without a real answer and extracts each underlying question.
  4. 4A logic step groups questions into themes and ranks them by frequency and ticket priority.
  5. 5OpenAI drafts a concise, skimmable digest of the top ten gaps.
  6. 6The digest is posted to the chosen Slack channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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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