CUSTOMER SUPPORT

Daily At-Risk Digest for the Save Specialist

Each morning compiles every Front thread flagged at-risk in the last 24 hours into a single prioritized briefing — ranked by anger and account value.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily morning schedule
  • ActionFetch last 24h of at-risk Front threadsFront
  • ActionLook up plan tier and account value in AirtableAirtableAirtable
  • LogicSummarize and rank by anger and account value via OpenAIOpenAI
  • OutputSend prioritized digest to save specialist in SlackSlack

What it does

Once a day it gathers all Front conversations tagged `at-risk` or scored negative in the prior 24 hours, looks up each account's plan tier in Airtable, and asks OpenAI to draft a one-line situation summary and suggested next action per thread. It ranks them by a blend of anger severity and account value, then posts a single ordered digest to the save specialist in Slack — turning a scattered set of flags into one actionable worklist.

When to use it

Use it when angry threads are already being flagged through the day but your save specialist has no consolidated view of what to tackle first. This replaces inbox scrolling with a prioritized morning briefing.

How it works

  1. 1A daily morning schedule triggers the run.
  2. 2Front returns all at-risk conversations from the last 24 hours.
  3. 3Airtable supplies each customer's plan tier and lifetime value.
  4. 4OpenAI writes a summary and next-action suggestion and the flow ranks threads by anger times account value.
  5. 5Slack delivers the ordered digest as a direct message to the save specialist.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect AirtableBases, tables, views, automations.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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