How to connect Google Cloud BigQuery (REST) and Drip
Create a New Scenario to Connect Google Cloud BigQuery (REST) 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 (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or Drip will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Drip, and select the appropriate trigger to start the scenario.

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

Google Cloud BigQuery (REST)
Configure the Google Cloud BigQuery (REST)
Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) 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 (REST) 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 (REST) 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 (REST) 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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AI Anthropic Claude 3
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Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), 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 (REST) and Drip integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) 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 (REST) and Drip
Google Cloud BigQuery (REST) + Drip + Slack: When a new row is added to a BigQuery table containing marketing data, this triggers Drip to create or update a subscriber with the new data. Subsequently, a Slack notification is sent to the marketing team to inform them of the new subscriber/updated data.
Drip + Google Cloud BigQuery (REST) + Shopify: When a new subscriber is added to Drip, the subscriber data is inserted into a BigQuery table. If an anomaly is detected via BigQuery analysis (simulated with a new row), this triggers an update to a product in Shopify to reflect a promotion.
Google Cloud BigQuery (REST) and Drip integration alternatives
About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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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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FAQ Google Cloud BigQuery (REST) and Drip
How can I connect my Google Cloud BigQuery (REST) account to Drip using Latenode?
To connect your Google Cloud BigQuery (REST) account to Drip on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Drip accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I update Drip subscriber data using BigQuery analysis?
Yes, with Latenode, automatically update Drip based on BigQuery insights. Segment audiences and personalize campaigns for improved engagement. Use flexible no-code and JavaScript steps!
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Drip?
Integrating Google Cloud BigQuery (REST) with Drip allows you to perform various tasks, including:
- Automatically adding new BigQuery data entries as Drip subscribers.
- Updating Drip subscriber properties based on BigQuery data analysis.
- Triggering Drip email campaigns based on BigQuery data thresholds.
- Segmenting Drip subscribers using advanced BigQuery query results.
- Analyzing Drip campaign performance using BigQuery’s data processing.
Can I scale BigQuery/Drip automations easily within Latenode?
Yes, Latenode provides scalable infrastructure for handling high-volume data, ensuring consistent performance for Google Cloud BigQuery (REST) and Drip workflows.
Are there any limitations to the Google Cloud BigQuery (REST) and Drip integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex BigQuery queries may require optimization for real-time Drip updates.
- Data transfer limits imposed by the Google Cloud BigQuery (REST) API apply.
- Drip API rate limits can affect the speed of subscriber updates.