Connect HubSpot to Google BigQuery: Step-by-Step Guide

Connecting Hubspot to Google BigQuery lets your team centralize marketing, sales, and service data for deeper analysis and reporting. This guide walks you through how to enable the integration, configure sync settings, and manage your data pipeline securely and efficiently.

The instructions below are based on the official integration behavior so you can safely set up, test, and maintain your connection without breaking existing reporting processes.

Before You Connect HubSpot and BigQuery

Before turning on the integration, make sure you meet the account and permission requirements on both platforms. This prevents connection failures and partial data syncs.

HubSpot access and subscription requirements

To use the native Google BigQuery integration, your HubSpot account must meet specific criteria. Typically, this includes having appropriate subscription tiers that support data sync integrations and sufficient user permissions to install apps from the marketplace.

Confirm that:

• You have super admin access or equivalent integration permissions in your HubSpot account.
• Your subscription includes operations, reporting, or data tools that allow external warehouse connections.
• Any required HubSpot add-ons for data integrations are active.

BigQuery and Google Cloud prerequisites

On the BigQuery side, you will need a Google Cloud project and an active BigQuery dataset that will store data from HubSpot.

Check that:

• You have permission to create or use datasets in BigQuery.
• Billing is enabled for the relevant Google Cloud project.
• Your organization’s security policies allow external app connections and service accounts.

For detailed, always up-to-date prerequisites and supported data, review the official documentation on the HubSpot and Google BigQuery connection page.

How to Install the HubSpot BigQuery Integration

Once prerequisites are confirmed, you can install the integration from within your CRM. The exact navigation labels can evolve, but the general flow remains consistent.

Step 1: Open the HubSpot app marketplace

1. Sign in to your HubSpot account with an admin-enabled user.
2. Navigate to the app marketplace from your main navigation (often found under a marketplace or integrations icon).
3. Use the search bar to look for “Google BigQuery”.

Step 2: Connect HubSpot to your BigQuery project

1. Select the Google BigQuery listing from the search results.
2. Click the button to connect or install the app.
3. When prompted, sign in to your Google account associated with your BigQuery project.
4. Review and approve the access permissions requested by the integration. These allow HubSpot to send data into your chosen warehouse.

Once permissions are granted, HubSpot will establish a secure connection to your BigQuery environment so you can configure datasets and sync settings.

Configure HubSpot Data Sync Settings

After installation, you decide exactly which object data should flow from HubSpot into BigQuery, and how often that sync runs. Careful configuration ensures you send only the data your team actually needs.

Select HubSpot objects and fields for export

In the integration settings, you will be able to choose which core objects you want to sync. Depending on the integration version, these may include:

• Contacts
• Companies
• Deals
• Tickets
• Custom objects (where supported)

Within each object, select only the fields that are relevant for analytics, modeling, or reporting in BigQuery. This keeps your warehouse lean and queries faster.

Choose your BigQuery dataset and tables

Next, map the data to a dataset and table structure inside BigQuery:

• Pick the BigQuery project and dataset you want to use for HubSpot data.
• Confirm or customize default table names for each object (for example, contacts, companies, deals).
• Validate that naming conventions align with your existing warehouse standards.

This mapping controls where HubSpot records will land so your data team can easily join them with other sources.

Set sync frequency and behavior

The integration typically supports scheduled syncs, so you should define how often HubSpot data is updated in BigQuery.

Common configuration options include:

• Initial full historical sync of supported data.
• Ongoing incremental sync on a regular schedule (for example, hourly or daily).
• Rules for how updates and deletions in HubSpot are reflected downstream.

Align sync frequency with your reporting needs and warehouse cost considerations.

Manage and Monitor the HubSpot–BigQuery Integration

After you configure the connection, you should regularly monitor integration health so that analytics teams always trust the data derived from HubSpot records.

Review sync status and logs

In your integration settings inside HubSpot, you can typically access:

• Overall connection status and last sync time.
• Object-level sync summaries (for example, number of contacts or deals processed).
• Error messages for failed records or permission issues.

Use these logs to quickly spot configuration mistakes, missing permissions, or schema mismatches in BigQuery.

Handle schema changes from HubSpot

When you add new properties or update field types in HubSpot, these changes can impact how data appears in BigQuery. To avoid pipeline failures:

• Periodically review object property definitions in HubSpot.
• Update warehouse schemas or transformation logic to account for new or changed fields.
• Coordinate changes with your data engineering team so dashboards stay accurate.

Pause or disconnect the integration safely

If you need to pause data flow from HubSpot to BigQuery, you can typically disable the integration from the app’s settings page. When doing so, document:

• Which objects and tables were impacted.
• Which dashboards or BI tools rely on those tables.
• Any steps needed to re-enable the integration later.

Disconnecting removes the live connection, but existing tables and historical data in BigQuery are usually preserved unless you manually delete them.

Best Practices for Using HubSpot Data in BigQuery

Once your integration is stable, your team can start building analytics and models that combine HubSpot data with other sources such as product usage, billing, or support platforms.

• Standardize IDs across systems so you can reliably join HubSpot records with external data.
• Create views in BigQuery that abstract away raw integration tables and provide analytics-friendly schemas.
• Document key metrics derived from HubSpot properties, such as lifecycle stages, deal stages, or ticket statuses.

For organizations building advanced data stacks around CRM, marketing, and revenue operations, it can be helpful to work with specialists in integrations and analytics architecture. For additional strategy, implementation guidance, and training, you can explore services from partners like Consultevo, who focus on CRM and data-driven growth solutions.

Next Steps for Your HubSpot and BigQuery Setup

By following the steps above, you can install the integration, configure object and field mappings, and maintain a reliable connection between HubSpot and BigQuery. From there, your analytics and RevOps teams can design dashboards, attribution reports, and predictive models that rely on always-fresh CRM data.

As the integration evolves, always refer back to the official HubSpot connection guide for Google BigQuery for any new features, supported objects, or configuration options that may improve your data pipeline.

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