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

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

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

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LinkedIn Data Scraper
Authenticate LinkedIn Data Scraper
Now, click the LinkedIn Data Scraper node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your LinkedIn Data Scraper settings. Authentication allows you to use LinkedIn Data Scraper through Latenode.
Configure the Google AppSheet and LinkedIn Data Scraper 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 AppSheet and LinkedIn Data Scraper 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.

JavaScript
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AI Anthropic Claude 3
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LinkedIn Data Scraper
Trigger on Webhook
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Google AppSheet
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google AppSheet, LinkedIn Data Scraper, 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 AppSheet and LinkedIn Data Scraper integration works as expected. Depending on your setup, data should flow between Google AppSheet and LinkedIn Data Scraper (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google AppSheet and LinkedIn Data Scraper
LinkedIn Data Scraper + Google AppSheet + Slack: When a new lead is scraped from LinkedIn using LinkedIn Data Scraper, the data is added to Google AppSheet. Then, a notification is sent to a designated Slack channel to alert the sales team of the new lead.
LinkedIn Data Scraper + Google AppSheet + Gmail: This flow starts by scraping LinkedIn profile data with LinkedIn Data Scraper. The scraped data is then added as a new record in Google AppSheet. Finally, an email is sent to the marketing manager via Gmail with the prospect's details.
Google AppSheet and LinkedIn Data Scraper integration alternatives
About Google AppSheet
Use Google AppSheet for no-code app creation and connect it to Latenode to automate back-end tasks. Trigger workflows on AppSheet events to update databases, send notifications, or process data. Centralize logic in Latenode, bypassing AppSheet limits and adding advanced features like AI, file parsing, or custom integrations via API and code.
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About LinkedIn Data Scraper
Need LinkedIn data for leads or market insights? Automate scraping profiles and company info inside Latenode workflows. Extract data, enrich it with AI, then push it to your CRM or database. Latenode's visual editor and affordable pricing make data-driven outreach scalable and cost-effective.
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FAQ Google AppSheet and LinkedIn Data Scraper
How can I connect my Google AppSheet account to LinkedIn Data Scraper using Latenode?
To connect your Google AppSheet account to LinkedIn Data Scraper on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google AppSheet and click on "Connect".
- Authenticate your Google AppSheet and LinkedIn Data Scraper accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically update AppSheet with scraped LinkedIn profiles?
Yes, you can! Latenode enables seamless automation, triggering updates in Google AppSheet whenever LinkedIn Data Scraper finds new profiles. Track leads and contacts effortlessly.
What types of tasks can I perform by integrating Google AppSheet with LinkedIn Data Scraper?
Integrating Google AppSheet with LinkedIn Data Scraper allows you to perform various tasks, including:
- Enriching AppSheet contacts with LinkedIn profile data automatically.
- Creating lead lists in AppSheet from LinkedIn searches.
- Tracking competitor employee movements directly in AppSheet.
- Building a real-time database of industry professionals.
- Updating AppSheet records with job title changes from LinkedIn.
How do I handle large datasets from LinkedIn in Google AppSheet?
Latenode allows efficient batch processing and data transformation to optimize Google AppSheet performance with large LinkedIn datasets.
Are there any limitations to the Google AppSheet and LinkedIn Data Scraper integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits on LinkedIn Data Scraper may affect data extraction frequency.
- Google AppSheet's API limits can impact write speeds for large datasets.
- Complex data transformations may require JavaScript for optimal performance.