CHATBOTS

Post-callback satisfaction follow-up with voice survey

When an agent marks a queued IVR callback as completed in Postgres, ElevenLabs synthesizes a short spoken satisfaction survey offer and a Zendesk ticket is updated to close…

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCallback row marked completed in PostgresPostgreSQLPostgres
  • LogicConfirm resolved and contact present
  • ActionDraft tailored satisfaction-survey scriptOpenAI
  • ActionSynthesize spoken survey offerElevenLabsElevenLabs
  • OutputUpdate Zendesk ticket with outcome and surveyZendeskZendesk

What it does

Closes the loop after a deflected call is finally handled. The moment an agent resolves a queued callback, this synthesizes a brief spoken satisfaction-survey offer for the caller and updates the matching Zendesk ticket with the resolution and survey status, so the full journey from deflection to follow-up is recorded in one place.

When to use it

Use it when you want to measure how well your callback recovery actually works. It converts a resolved queue row into a measurable touchpoint and keeps your helpdesk system of record in sync.

How it works

  1. 1A Postgres trigger fires when a callback row is marked completed.
  2. 2A logic step confirms the call was resolved (not cancelled or duplicate) and a contact exists.
  3. 3OpenAI drafts a short, on-brand satisfaction-survey script tailored to the resolved intent.
  4. 4ElevenLabs synthesizes the survey offer as audio for the caller follow-up.
  5. 5The matching Zendesk ticket is updated with the resolution summary, survey audio link, and a follow-up status.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ElevenLabsText-to-speech, voice cloning.
  4. 4
    Connect ZendeskTickets, queues, knowledge base.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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