How to connect Google Cloud BigQuery (REST) and SendPulse
Create a New Scenario to Connect Google Cloud BigQuery (REST) and SendPulse
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 SendPulse will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or SendPulse, 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 SendPulse Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select SendPulse from the list of available apps, and choose the action you need from the list of nodes within SendPulse.

Google Cloud BigQuery (REST)
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SendPulse

Authenticate SendPulse
Now, click the SendPulse node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your SendPulse settings. Authentication allows you to use SendPulse through Latenode.
Configure the Google Cloud BigQuery (REST) and SendPulse 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 SendPulse 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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SendPulse
Trigger on Webhook
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Google Cloud BigQuery (REST)
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), SendPulse, 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 SendPulse integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and SendPulse (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 SendPulse
SendPulse + Google Cloud BigQuery (REST) + Google Sheets: When a subscriber event occurs in SendPulse, such as a new subscription or unsubscription, the data is captured and stored in Google Cloud BigQuery. This data is then queried and visualized in Google Sheets to analyze email campaign performance.
SendPulse + Google Cloud BigQuery (REST) + Slack: When a subscriber event occurs in SendPulse, the data is captured and stored in Google Cloud BigQuery. Then a summary of the Sendpulse data is posted to a Slack channel.
Google Cloud BigQuery (REST) and SendPulse 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 SendPulse
Use SendPulse in Latenode for automated email & SMS marketing. Trigger campaigns based on real-time events, segment contacts dynamically, and personalize messages using data from any app. Automate list cleaning and optimize send times in response to user behavior. Connect SendPulse to any data source for smarter, event-driven communication workflows.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and SendPulse
How can I connect my Google Cloud BigQuery (REST) account to SendPulse using Latenode?
To connect your Google Cloud BigQuery (REST) account to SendPulse 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 SendPulse accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze user behavior and send targeted emails?
Yes! Latenode allows you to trigger personalized emails via SendPulse based on Google Cloud BigQuery (REST) data, enhancing engagement with targeted campaigns. Scale effortlessly with Latenode's architecture.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with SendPulse?
Integrating Google Cloud BigQuery (REST) with SendPulse allows you to perform various tasks, including:
- Automatically adding new BigQuery leads to a SendPulse mailing list.
- Sending personalized email campaigns based on BigQuery customer data.
- Updating contact properties in SendPulse from BigQuery data analysis.
- Triggering email sequences based on BigQuery event triggers.
- Creating detailed marketing reports combining data from both platforms.
How does Latenode handle data transformations in this integration?
Latenode provides flexible data mapping and transformation tools, including JavaScript code blocks, to ensure seamless data flow.
Are there any limitations to the Google Cloud BigQuery (REST) and SendPulse integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex BigQuery queries might require optimization for timely data retrieval.
- Rate limits of the SendPulse API can affect large-scale email sending.
- Initial setup requires familiarity with both Google Cloud BigQuery (REST) and SendPulse APIs.