CHATBOTS
Intercom Out-of-Window Return Deflector
Detects return requests in Intercom for orders past the return window and replies with a personalized decline that offers a store-credit or repair alternative instead of a refund.
How it runs
The automated pipeline, trigger to output.
- TriggerIntercom return-intent conversation openedIntercom
- ActionRead purchase date from Postgres and charge from StripePostgres
- LogicConfirm order is past the return window
- ActionCompose decline with cutoff date and alternative offer
- OutputPost save-offer reply and tag conversation in IntercomIntercom
What it does
Catches the return requests you cannot approve and turns the rejection into a save attempt. When an Intercom return request maps to an order outside your return window, it confirms the cutoff against Stripe and Postgres, then sends a tailored message offering an alternative like partial store credit or a repair, rather than a flat no.
When to use it
Use it when late return asks pile up and a blunt "sorry, too late" burns goodwill. This keeps the answer consistent, on-brand, and oriented toward retaining the customer.
How it works
- 1An Intercom return-intent conversation triggers the flow.
- 2The order's purchase date is read from Postgres and the original charge confirmed in Stripe.
- 3A logic step confirms the order is genuinely past the return window and not a data error.
- 4If out of window, the bot composes a decline that names the specific cutoff date and proposes an alternative offer.
- 5The personalized message is posted to the Intercom thread and the conversation is tagged for save-offer reporting.
Set it up
What you configure once, before turning it on.
- 1Connect IntercomConversations, contacts, articles.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect StripeCustomers, subscriptions, payments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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