How to connect Google Cloud BigQuery and Drip
Create a New Scenario to Connect Google Cloud BigQuery and Drip
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Drip will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Drip, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery Node
Select the Google Cloud BigQuery node from the app selection panel on the right.

Google Cloud BigQuery
Configure the Google Cloud BigQuery
Click on the Google Cloud BigQuery node to configure it. You can modify the Google Cloud BigQuery URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Drip Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Drip from the list of available apps, and choose the action you need from the list of nodes within Drip.

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Authenticate Drip
Now, click the Drip node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Drip settings. Authentication allows you to use Drip through Latenode.
Configure the Google Cloud BigQuery and Drip Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud BigQuery and Drip Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery, Drip, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery and Drip integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Drip (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery and Drip
Google Cloud BigQuery + Drip + Slack: When BigQuery identifies users who qualify for a specific Drip campaign based on defined criteria, their email addresses are extracted. Drip then subscribes these users to the designated campaign, and Slack sends a notification to a marketing channel informing them of the newly subscribed users.
Drip + Google Cloud BigQuery + Google Sheets: When a new subscriber is added to a Drip campaign, the event triggers a BigQuery query to analyze campaign performance. The results of this analysis, such as subscriber demographics or engagement metrics, are then logged in Google Sheets for reporting and further analysis.
Google Cloud BigQuery and Drip integration alternatives
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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About Drip
Use Drip in Latenode for automated marketing workflows. Sync customer data, trigger personalized email campaigns based on events, and analyze results. Scale your email marketing by connecting Drip to other apps in Latenode via visual flows. Benefit from advanced logic and data transformations to precisely target your audience.
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See how Latenode works
FAQ Google Cloud BigQuery and Drip
How can I connect my Google Cloud BigQuery account to Drip using Latenode?
To connect your Google Cloud BigQuery account to Drip on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and Drip accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I segment Drip subscribers based on BigQuery data?
Yes, using Latenode, you can. Automatically segment Drip subscribers based on Google Cloud BigQuery insights, personalizing campaigns and improving targeting. Latenode scales to handle large datasets.
What types of tasks can I perform by integrating Google Cloud BigQuery with Drip?
Integrating Google Cloud BigQuery with Drip allows you to perform various tasks, including:
- Automatically adding new Google Cloud BigQuery leads as Drip subscribers.
- Updating Drip subscriber information based on Google Cloud BigQuery data analysis.
- Triggering Drip campaigns based on Google Cloud BigQuery event tracking.
- Analyzing Drip campaign performance with Google Cloud BigQuery data warehousing.
- Creating custom reports by combining data from both platforms.
Can I use SQL queries directly within the Latenode BigQuery integration?
Yes, Latenode enables direct execution of SQL queries against your Google Cloud BigQuery datasets for granular control and data manipulation within your workflows.
Are there any limitations to the Google Cloud BigQuery and Drip integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets may require optimized queries for efficient processing.
- Drip API rate limits may affect the speed of data synchronization.
- Initial setup requires familiarity with both Google Cloud BigQuery and Drip.