CUSTOMER SUPPORT

Front Order-Aware Draft: Pull Stripe Facts Before Suggesting a Macro

When a billing question hits a Front inbox, this looks up the customer's Stripe payment and subscription state, picks the macro that matches their actual account situation.

CategoryCustomer Support
Enginesim
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew conversation in billing Front inboxFront
  • ActionRead customer email and questionFront
  • ActionLook up charges, subscription, and refund window in StripeStripeStripe
  • LogicIf no Stripe record, tag verify-identity and skip
  • ActionSelect account-matched macro and fill with real figuresOpenAI
  • OutputSave order-aware reply as Front draftFront

What it does

Billing replies fail when the macro doesn't match the customer's real account state. This workflow fetches the customer's Stripe data first — last charge, subscription status, refund eligibility — then chooses and fills the macro that actually fits, so the suggested draft references the right amounts and dates instead of generic placeholders.

When to use it

Use it for billing and subscription inboxes where the correct answer depends on whether a payment succeeded, a card failed, or a refund window is still open. Removes the agent's manual hop into Stripe.

How it works

  1. 1A new conversation in the billing Front inbox triggers the run.
  2. 2The customer email and question are read from Front.
  3. 3Stripe is queried for the customer's charges, subscription, and refund window.
  4. 4OpenAI selects the macro matching the actual account state and fills it with real Stripe figures.
  5. 5If no customer record is found in Stripe, the conversation is tagged "verify-identity" and skipped.
  6. 6The order-aware reply is saved as a Front draft for the agent to send.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FrontShared inbox, conversations.
  2. 2
    Connect StripeCustomers, subscriptions, payments.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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.

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