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

Google Cloud BigQuery
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ConvertKit

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

Save and Activate the Scenario
After configuring Google Cloud BigQuery, ConvertKit, 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 ConvertKit integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and ConvertKit (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 ConvertKit
ConvertKit + Google Ads + Slack: When a new subscriber joins ConvertKit, their information is used to add them to a customer list in Google Ads. A notification is then sent to Slack to announce the new subscriber.
ConvertKit + Google Ads + Slack: A new subscriber in ConvertKit triggers adding them to a customer list in Google Ads. Google Ads then sends offline conversion data. Finally, a Slack message is sent to a specified channel.
Google Cloud BigQuery and ConvertKit 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 ConvertKit
Automate email marketing with ConvertKit in Latenode. Sync new subscribers, trigger campaigns based on events, and segment lists dynamically. Connect ConvertKit to any app via Latenode's visual editor. Enrich data and personalize flows with JavaScript, ensuring relevant messaging and optimized deliverability, without complex coding.
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See how Latenode works
FAQ Google Cloud BigQuery and ConvertKit
How can I connect my Google Cloud BigQuery account to ConvertKit using Latenode?
To connect your Google Cloud BigQuery account to ConvertKit 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 ConvertKit accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I update ConvertKit with BigQuery customer data?
Yes, you can! Latenode allows you to automate data transfers, enriching ConvertKit profiles with BigQuery insights. This enables highly personalized marketing campaigns based on data-driven insights.
What types of tasks can I perform by integrating Google Cloud BigQuery with ConvertKit?
Integrating Google Cloud BigQuery with ConvertKit allows you to perform various tasks, including:
- Automatically adding new BigQuery leads to ConvertKit as subscribers.
- Segmenting ConvertKit subscribers based on BigQuery data analysis.
- Updating custom fields in ConvertKit with BigQuery data insights.
- Triggering email sequences in ConvertKit based on BigQuery triggers.
- Analyzing ConvertKit campaign performance using BigQuery data.
HowsecureistheGoogleCloudBigQueryintegrationonLatenode?
Latenode employs robust security measures, including encryption and secure authentication protocols, ensuring your data's safety during integration and automation workflows.
Are there any limitations to the Google Cloud BigQuery and ConvertKit integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization may take time depending on dataset size.
- Complex BigQuery queries might require JavaScript for optimal performance.
- Rate limits of the ConvertKit API may affect high-volume data transfers.