MARKET RESEARCH

Allocate Sales Territory TAM from BigQuery Geo Data to HubSpot

When triggered by a webhook, queries BigQuery public ZIP-level business data to compute TAM per sales territory.

CategoryMarket Research
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook fires with territory-to-ZIP mappingHTTP webhook
  • ActionQuery ZIP-level business data in BigQueryGoogle BigQueryBigQuery
  • LogicAggregate ZIPs into territories; flag uncovered ones
  • ActionConvert counts to TAM dollars and balance notes via OpenAIOpenAI
  • OutputWrite territory TAM onto HubSpot company recordsHubSpotHubSpot

What it does

Gives RevOps a data-backed way to balance territories. On a webhook call (e.g. from your territory-planning tool), it queries BigQuery public ZIP Business Patterns data, rolls establishment counts and revenue proxies up to your defined territory boundaries, computes TAM per territory, and pushes the per-territory dollar value onto the relevant HubSpot records.

When to use it

During territory design or rebalancing, when you need each rep's patch sized consistently from the same public-data source instead of hand-built spreadsheets.

How it works

  1. 1An incoming webhook triggers the run with the current territory-to-ZIP mapping in the payload.
  2. 2A BigQuery action queries ZIP-level business counts and size bands for all ZIPs in scope.
  3. 3A logic step aggregates ZIP rows into territories using the mapping and flags territories with no coverage.
  4. 4An OpenAI action converts aggregated counts into TAM dollars and notes any over- or under-loaded territories.
  5. 5An output step writes the territory TAM values to the corresponding HubSpot company records.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect HubSpotCRM, deals, marketing, support.
  4. 4
    Connect HTTP webhookTrigger any URL on agent actions.
  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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