CUSTOMER SUPPORT

Make-Good Follow-Up No-Reply Chaser

Tracks detractors who received a make-good offer and, if there's no reply within three days, sends a gentle reminder and books a fallback call so recovery attempts don't go cold.

CategoryCustomer Support
Enginesim
Difficultybeginner
Triggerschedule
Steps6
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily morning schedule
  • ActionQuery make-goods sent 3+ days agoAirtableAirtable
  • LogicKeep only non-responders
  • ActionDraft warm reminder noteOpenAI
  • ActionHold fallback recovery callGoogle CalendarGoogle Calendar
  • OutputSend reminder and mark record chasedGmailGmail

What it does

Closes the loop on recovery offers. After a make-good email is sent to a detractor, this checks back in three days; if the customer hasn't responded, it sends one tactful nudge and reserves a fallback call slot so the save attempt actually lands instead of dying in an inbox.

When to use it

Use it as the second half of any detractor-recovery play. Pair it with a make-good drafter so offers that get ignored are automatically chased exactly once before the agent steps in.

How it works

  1. 1A daily schedule trigger runs each morning.
  2. 2The flow queries Airtable for make-good records sent three or more days ago.
  3. 3A logic step checks each record's reply status.
  4. 4For non-responders, an OpenAI step drafts a short, warm reminder referencing the original offer.
  5. 5A fallback recovery call is held on Google Calendar in case they want to talk.
  6. 6The reminder is sent from Gmail and the Airtable record is marked chased so it's never nudged twice.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Google CalendarEvents, attendees, availability.
  4. 4
    Connect GmailRead, draft, send, label.
  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.

Run this workflow in your colony.

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