Sync data from
Google BigQuery to HubSpot
Connect your data from Google BigQuery to HubSpot with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.
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Integrate your data in 3 easy steps
01
Add your source and destination
Connect to 15+ data sources, like Google BigQuery, and 140+ destinations, like HubSpot.
Connect
Log in
02
Define your model
Use SQL or select an existing dbt or Looker model.
03
Sync your data
Define how fields from your model map to HubSpot, and start syncing.
email
email
name
name
total_orders
all_orders
last_login
last_login
Model your Google BigQuery data using any of these methods
dbt Model Selector
Sync directly with your dbt models saved in a git.
Looker
Query using looks. Hightouch turns your look into SQL and will pull from your source.
SQL Editor
Create and Edit SQL from your browser. Hightouch supports SQL native to Google BigQuery.
Table Selector
Select available tables and sheets from Google BigQuery and sync using existing views without having to write SQL.
Customer Studio
For less technical users, pass traits and audiences from Google BigQuery using our visual segmentation builder.
Where can you sync your Google BigQuery data in HubSpot
Contacts
Contacts store information about individuals. From marketing automation to smart content, the lead-specific data found in contact records helps users leverage much of HubSpot's functionality.
Companies
The companies object is a CRM object. You can use individual company records to store information about businesses and organizations within company properties. The companies endpoints allow you to manage this data and sync it between HubSpot and other systems.
Deals
A a deal represents an ongoing transaction that a sales team is pursuing with a contact or company. It’s tracked through pipeline stages until won or lost. The deals endpoints allow you to manage this data and sync it between HubSpot and other systems.
Tickets
In HubSpot, a ticket represents a customer request for help or support. The tickets endpoints allow you to manage this data and sync it between HubSpot and other systems.
Custom Objects
To represent and organize your CRM data based on your business needs, you can create custom objects. Use the custom objects API to define custom objects, properties, and associations to other CRM objects before syncing data from Hightouch.
Events
A marketing event is a CRM object, similar to contacts and companies, that enables you to track and associate marketing events, such as a webinar, with other HubSpot CRM objects. Below, learn more about working with the marketing event API to integrate marketing events into an app.
Does this integration support in-warehouse planning?
Yes, if you integerate Google BigQuery and HubSpot using Hightouch, in-warehouse planning is supported.
Great, but what is in-warehouse planning?
Between every sync, Hightouch notices any and all changes in your data model. This allows you to only send updated results to your destination (in this case HubSpot). With the baseline setup, Hightouch picks out only the rows that need to be synced by querying every row in your data model before diffing using Hightouch’s infrastructure.
The issue here is this can be slow for large models.
Warehouse Planning allows Hightouch to do this diff directly in your warehouse. Read more on how this works here.
Why is it valuable to sync Google BigQuery data to HubSpot?
HubSpot is the backbone of your sales org. It's where you manage all of your contacts, accounts, and deals. The problem is that most of your CRM data has to be manually input by individual sales reps, so it doesn't show you an accurate 360-degree view of your customer. You only have access to basic information and historical interactions.
All of your HubSpot data, in addition to the rich behavioral data captured through your app/website already, exists in Google BigQuery. Most of the time, this includes core metrics your data team has defined around lifetime value, workspaces, subscriptions, playlists, average order value, last login date, etc. There's a high chance you're probably even consuming this data in a dashboard, and your sales reps can't answer key questions like:
- Which accounts have the highest lifetime value?
- Which users have the highest utilization in our product?
- When did user X last log in to the app?
- Which leads/accounts should I be prioritizing?
- Which accounts are at risk of churning?
- What is the average order value of account X?
Your sales team doesn't want to hop back and forth between your various SaaS tools to answer these questions. They want to take action in HubSpot, and that means enriching your CRM with data directly from your warehouse.
Why should you use reverse ETL to connect Google BigQuery and HubSpot data?
Conventionally moving data from Snowflake to HubSpot meant downloading ad hoc CSV files and uploading them manually or forcing your data team to integrate with the HubSpot API and build and maintain custom pipelines. In reality, CSVs are not scalable, and in-house data pipelines and custom scripts break constantly.
Other point-to-point solutions create a weave complex web of pipelines to and from various SaaS applications and customer data platforms (CDPs), forcing you to pay for another layer of storage in addition to your data warehouses.
Reverse ETL solutions like Hightouch query against Snowflake and sync that data directly to HubSpot. You don't have to worry about CSVs or APIs. You can leverage your existing tables, data models, and audience segments. All you have to do is define your data and map it to the appropriate columns in HubSpot. You can schedule your syncs to run manually or even trigger them to run sequentially based on criteria that you define.
Hightouch automatically diffs data between syncs to ensure your only ever syncing the freshest data, and if any rows fail, Hightouch will automatically retry them later. A live debugger lets you analyze your API payload requests/responses and failed runs in real-time.
How to integrate BigQuery and Hubspot
You have a few options to activate your data from Bigquery so your data doesn't end its journey in a BI dashboard. We've outlined the 5 most best options to sync your data to Hubspot below:
Option 1: Reverse ETL (Hightouch)
Reverse ETL is easy to implement because it runs on top of your warehouse. With Hightouch, you can sync data directly from BigQuery to Hubspot in real-time to support your various business teams. Better yet, Hightouch lets you map on any unique object and doesn’t store any of your data. You can define your data using SQL or the custom data models that your data team has built within BigQuery. Using the Hightouch UI you can easily map the appropriate columns to Hubspot in a matter of minutes. All you have to do is follow these steps.
Step 1: Connect to Your Data Source

Step 2: Connect Hightouch to Your Destination

Step 3: Create a data model or leverage an existing one
You can use SQL to define your data directly in the Hightouch UI or even leverage your existing data models.


Step 4: Choose Your Primary Key
With Hightouch you can map on any unique key, not just users and accounts.

Step 5: Create Your Sync
Once you have created your sync, you simply have to choose the appropriate columns and map them to the fields in your end destination.

Step 6: Schedule Your Sync
Once your sync is created you can run it manually, define a set interval, or schedule it to run after a dbt job is completed.

The first integration with Hightouch is completely free so you can actually get started today. If you want to learn more about Reverse ETL, download our guide.
Option 2: Manual CSV Files
An easy option for moving data from BigQuery to Hubspot is to simply download a CSV file and then upload that same CSV. This method is relatively simple as there is no barrier to entry and you can do it immediately. The problem with this method is that there is no continuous flow of data.
You have to manually download a dataset every time you receive a request. When data is stored in this format it becomes stale really fast, making it really difficult for your marketing and sales teams to actually act on the information in their business tools.
Option 3: Custom Integrations
Building your own in-house data pipeline is one way to tackle the challenge of moving data from BigQuery to Hubspot, but this requires your engineering team to spend a substantial amount of time not only getting this integration up and running but also managing and maintaining it.
BigQuery and Hubspot are constantly changing/updating their APIs and this usually translates into upstream or downstream failures unless properly addressed. If your data needs are relatively small this option could be worthwhile pursuing, but if you need to sync data to additional SaaS applications, this will quickly become unscalable and you will find that your engineers are spending all of their time building/maintaining data pipelines.
Option 4: iPaaS (Integration Platform as a Service)
Integration platforms like Tray and Workato, are great solutions for moving data from one source to another. They let you build intuitive workflows to automate tasks and processes between different SaaS applications.
The problem is, these workflows can get complex really quickly depending on your business needs, and most likely you will find yourself neck-deep trying to manage massive workflows with numerous if/then statements and various dependencies within each individual step. There is a high chance that you will even have to write custom code to get your workflows functional.
Option 5: CDPs (Customer Data Platform)
CDPs are probably the single most popular solution for moving data from one source to another. CDPs come with a number of built-in features, but the main use case they solve is enabling you to easily consolidate all of your customer data into a managed platform where it can then be sent directly to 3rd party SaaS applications and tools.
Pushing your data into a CDP means that it is no longer in your own cloud environment and this can sometimes cause problems around compliance. Additionally, it's important to note that CDPs have a long-drawn-out implementation process. It can take anywhere from six months to a year to start seeing value. In addition to this, CDPs do not let you map on custom objects, you are forced to use fields like users and accounts.
Target customers to upsell based on the product features they currently use
See a customer's Stripe and NetSuite invoices directly from HubSpot
Personalize content in marketing emails based on a customer's product usage
Send lifecycle emails to customers based on their recent activity in the product (like abandoning a shopping cart)
Send tips to customers on valuable features they haven't used yet
Congratulate customers for reaching milestones within the product
Why sync data from
Google BigQuery to HubSpot?
Today nearly every single interaction between your customers and prospects across both sales and marketing channels is captured in Hubspot. There’s a problem though. HubSpot only shows you one view of your customer. All of your unique customer data (e.g. product usage data, event data, custom audiences, etc.) is stored in BigQuery. To truly create a personalized customer experience your business teams need access to this information in Hubspot.
About Google BigQuery
BigQuery is a fully-managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.
Learn more about Google BigQueryAbout HubSpot
HubSpot is an inbound marketing and sales platform that helps companies attract visitors, convert leads, and close customers. Its products and services aim to provide tools for social media marketing, content management, web analytics, CRM and search engine optimization.
Learn more about HubSpotOther Google BigQuery Integrations
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Hightouch Playbooks: Best practices to leverage reverse ETL
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