BigQuery integration for Dimension Labs
If your conversations already land in a BigQuery table, you can send them to Dimension Labs from there. A scheduled job on your side queries the rows that are new since its last run and posts each message to the universal API.
- Platform
- Google BigQuery
- Type
- Data warehouses
- Connects by
- Universal API
- Setup
- 5 steps
- Guide checked
- 2026-10-13, against Google Cloud's documentation
Every BigQuery message, in the same shape as everything else.
Each record lands in the Dimension Labs conversation format, so Dimensions, reports and the agent work the same way as for every other source.
body text Skip rows where it is empty. Strip HTML if bodies are HTML.
customer_id userId If it is null, use the sessionId.
sender_type incoming true only when the customer wrote it. Agent and bot rows are false.
conversation_id sessionId Replace any colons.
conversation_id conversationId Same value as sessionId.
sent_ms dimensionlabs_timestamp Already milliseconds. Pass it through toMillis.
message_id, channel platformJson Add any join keys you have, such as an account or store id. If your only customer key is an email, send a consistent hash of it instead.
5 steps. Then it runs on its own.
A small job on your side reads BigQuery through its API and posts each message to the Dimension Labs universal API. The guide gives the steps, the field mapping and the code. Run the job once for history, then every 15 minutes. A live source is enriched automatically every day; history is enriched with a backfill.
Open the full BigQuery guide ›- 01Get access
- 02Query new rows
- 03Map the columns
- 04Send it
- 05Run it
What you need
- A Google Cloud role that can create service accounts and grant IAM roles on the project and dataset.
- A service account for the job.
- A Dimension Labs API key for a new Universal API source.
[03] What you can ask
Questions teams answer with BigQuery data.
- Which conversations came before the accounts that churned?
- Did the change we shipped move the metric?
- Which issues hit our highest-value customers?
BigQuery integration questions
Does Dimension Labs integrate with BigQuery?
Yes. A small job on your side reads BigQuery through its API and posts each message to the Dimension Labs universal API. The guide gives the steps, the field mapping and the code. The setup guide was checked against Google Cloud's documentation on 2026-10-13.
What BigQuery data does Dimension Labs bring in?
If your conversations already land in a BigQuery table, you can send them to Dimension Labs from there. A scheduled job on your side queries the rows that are new since its last run and posts each message to the universal API.
What do I need to connect BigQuery?
A Google Cloud role that can create service accounts and grant IAM roles on the project and dataset. A service account for the job. A Dimension Labs API key for a new Universal API source.
How often does BigQuery data update?
Run the job once for history, then every 15 minutes. A live source is enriched automatically every day; history is enriched with a backfill.
Can I connect a platform that is not BigQuery?
Yes. Any platform with an API connects through the same universal API, and any tool with an export button works as a file upload. The integrations page lists the platforms with a written guide.
Stop reporting. Start understanding.
Start with one file. Ask why a number moved. Plans from $299 a month, no demo and no contract on monthly plans.