CUSTOMER SUPPORT

Tiered Refund Policy Router for Intercom Conversations

Reads the refund window from a Postgres policy table keyed by product tier, evaluates an Intercom refund request against the correct tier rule.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIntercom conversation tagged refund-reviewIntercomIntercom
  • ActionFetch tier rule and order from PostgresPostgreSQLPostgres
  • LogicSelect tier rule and check window
  • LogicAssemble tier-specific rationale
  • OutputSend decision as private note in IntercomIntercomIntercom

What it does

Different products carry different refund windows. This workflow looks up the customer's product tier, fetches that tier's policy rule from your Postgres policy table, and evaluates the Intercom refund request against the right window rather than a single blanket rule.

When to use it

Use it when your refund policy is not uniform: SaaS plans, hardware, and add-ons each have their own window or non-refundable status. It guarantees agents apply the correct rule for each product instead of memorizing a matrix.

How it works

  1. 1An Intercom conversation tagged for refund review starts the flow.
  2. 2The flow reads the customer's product tier and purchase date from the Postgres policy and orders tables.
  3. 3A logic step selects the matching tier rule and checks whether the purchase falls inside that tier's window.
  4. 4It assembles a rationale naming the tier, the applicable window, and the elapsed days.
  5. 5The decision and rationale are sent back into the Intercom conversation as a private note for the agent.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect IntercomConversations, contacts, articles.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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