CUSTOMER SUPPORT

Refund eligibility pre-check from an Intercom conversation

When a support rep tags an Intercom conversation 'refund-request', this gathers the customer's Stripe billing status, usage data, and prior refund history.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIntercom conversation tagged 'refund-request'IntercomIntercom
  • ActionFetch Stripe customer, subscription, and recent chargesStripeStripe
  • ActionQuery usage and prior refunds in PostgresPostgreSQLPostgres
  • LogicScore eligibility against refund policy
  • OutputPost approve/decline recommendation as Intercom noteIntercomIntercom

What it does

Turns a raw refund ask in Intercom into a decision-ready brief. It pulls everything an agent needs — subscription state, payment history, product usage, and whether this customer has been refunded before — and writes a single recommendation note into the conversation so the rep can act in one pass instead of digging through three dashboards.

When to use it

Use it when support reps handle refund requests inside Intercom and you want consistent, evidence-backed decisions without each rep manually cross-checking Stripe and your usage database.

How it works

  1. 1A conversation is tagged `refund-request` in Intercom, firing the trigger.
  2. 2The customer email is used to look up the Stripe customer, subscription status, and recent charges.
  3. 3A Postgres query returns product usage in the billing period and any prior refunds on this account.
  4. 4A logic step scores eligibility against your policy (active sub, usage below threshold, no repeat refunds).
  5. 5The recommendation, reasons, and supporting numbers are posted as an internal Intercom note on the conversation.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect IntercomConversations, contacts, articles.
  2. 2
    Connect StripeCustomers, subscriptions, payments.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  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.

Run this workflow in your colony.

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