SALES

API-Usage Surge PQL Router

When an account's API call volume surges past a rolling baseline in the product DB, it qualifies the account as a product-qualified expansion lead.

CategorySales
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHourly schedule checks API volume
  • ActionQuery product DB for surge vs rolling baselinePostgreSQLPostgres
  • LogicRequire sustained surge to qualify as PQL
  • ActionCreate/advance expansion opp in SalesforceSalesforce
  • LogicRoute by segment to owning rep
  • OutputAssign HubSpot follow-up task with contextHubSpotHubSpot

What it does

Treats a sustained API-traffic surge as a product-qualified expansion signal. It confirms the surge is real (not a one-off spike) against a rolling baseline, marks the account as a PQL, advances or creates the expansion opportunity in Salesforce, and routes a follow-up task to the correct rep by segment.

When to use it

Use this for usage-based or API-metered products where rising consumption is the clearest buying signal. It closes the gap between "the account is clearly scaling" and "someone actually owns the expansion conversation."

How it works

  1. 1A schedule queries the product database hourly for accounts whose API volume exceeds their 30-day rolling baseline by the configured factor.
  2. 2A logic step requires the surge to persist across multiple intervals before qualifying, filtering out transient spikes.
  3. 3Qualified accounts are written back to Salesforce as a product-qualified expansion opportunity with the supporting usage metrics.
  4. 4A branch routes by account segment to pick the owning rep.
  5. 5A HubSpot task is created and assigned to that rep with the surge context and a suggested outreach angle.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect SalesforceAccounts, opportunities, cases.
  3. 3
    Connect HubSpotCRM, deals, marketing, support.
  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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