DATA OPS
Reverse-ETL HubSpot Drop Detector and Auto-Requeue
Detects warehouse rows that failed to land in HubSpot, writes the missing records to a retry table in Postgres.
How it runs
The automated pipeline, trigger to output.
- TriggerSchedule fires on sync cadence
- ActionRead batch source rows from BigQueryBigQuery
- ActionQuery HubSpot for expected contacts and companiesHubSpot
- LogicCompute source IDs with no HubSpot match
- ActionInsert missing rows into Postgres retry tablePostgres
- OutputSend drop-count metric to AxiomAxiom
What it does
Closes the loop on reverse-ETL drops into HubSpot. It identifies BigQuery source rows that did not produce a matching HubSpot contact or company, stages those records in a Postgres retry table the next sync can pick up, and pushes a count metric to Axiom so you can chart drop rates over time instead of discovering a pattern by accident.
When to use it
Use it when reverse-ETL syncs into HubSpot occasionally lose rows to property validation, list-membership limits, or association failures, and you want failed rows automatically captured for the next run rather than lost. The Axiom metric makes a creeping drop rate visible before it becomes a data-trust problem.
How it works
- 1A schedule fires on the cadence of your HubSpot sync.
- 2Read the batch's source rows from BigQuery with their external IDs.
- 3Query HubSpot for the contacts and companies that should now exist.
- 4Compute which source IDs have no HubSpot match.
- 5Insert the missing rows into a Postgres retry table, deduplicating against any already queued.
- 6Send a drop-count metric, tagged by object type, to Axiom for trend dashboards.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect HubSpotCRM, deals, marketing, support.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 4Connect AxiomLog streams, queries, dashboards.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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