CUSTOMER SUPPORT

Triage feature requests by tier and log expansion-blocked asks

Reviews inbound Intercom feature requests, checks the requester's Stripe tier, and logs plan-blocked requests to a Postgres table while routing genuine product gaps to Linear.

CategoryCustomer Support
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIntercom feature-request conversation taggedIntercomIntercom
  • ActionResolve requester plan tier in StripeStripeStripe
  • LogicDecide tier-gated vs true product gap
  • ActionLog expansion-blocked ask to PostgresPostgreSQLPostgres
  • OutputFile genuine gaps as Linear issuesLinearLinear

What it does

This agent-driven workflow reads feature requests arriving in Intercom and decides whether the ask is already available on a higher tier (an expansion opportunity) or a true product gap (a roadmap input). Tier-blocked requests are logged to a Postgres demand table for the revenue team; real gaps are filed in Linear for product.

When to use it

Use it when feature requests are a mixed signal and you want to stop treating every "can it do X" as roadmap fuel. It cleanly splits requests that an upgrade would satisfy from requests that need engineering work.

How it works

  1. 1A new Intercom conversation tagged as a feature request triggers the flow.
  2. 2Stripe resolves the requester's current plan tier.
  3. 3An agent step decides whether the requested capability exists on any tier the customer is not on.
  4. 4If it is tier-gated, the request is appended to the expansion-demand table in Postgres.
  5. 5If it is a genuine gap, a roadmap issue is created in Linear with the customer context attached.

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
    Connect LinearIssues, projects, cycles, triage.
  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.

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