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

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

Google Cloud Firestore
Configure the Google Cloud Firestore
Click on the Google Cloud Firestore node to configure it. You can modify the Google Cloud Firestore 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 Cloud Firestore 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 Cloud Firestore 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 Cloud Firestore 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 Cloud Firestore
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google Cloud Firestore, 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 Cloud Firestore and LinkedIn Data Scraper integration works as expected. Depending on your setup, data should flow between Google Cloud Firestore 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 Cloud Firestore and LinkedIn Data Scraper
LinkedIn Data Scraper + Google Cloud Firestore + Slack: Scrape LinkedIn profiles using the LinkedIn Data Scraper, then check if the scraped data matches the ideal customer profile stored in Google Cloud Firestore. If a match is found, notify the team via a Slack channel message.
LinkedIn Data Scraper + Google Cloud Firestore + Google Sheets: Scrape LinkedIn profile data using the LinkedIn Data Scraper, then save the scraped data to Google Cloud Firestore. Simultaneously, append the data to a Google Sheet for reporting and analysis.
Google Cloud Firestore and LinkedIn Data Scraper integration alternatives
About Google Cloud Firestore
Use Google Cloud Firestore in Latenode to build real-time data workflows. Automate database tasks like data synchronization, backups, or event-driven updates without coding. Combine Firestore with AI tools and webhooks for powerful apps. Create complex workflows with simple visual tools and scale affordably with Latenode's pay-as-you-go pricing.
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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 Cloud Firestore and LinkedIn Data Scraper
How can I connect my Google Cloud Firestore account to LinkedIn Data Scraper using Latenode?
To connect your Google Cloud Firestore account to LinkedIn Data Scraper on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Firestore and click on "Connect".
- Authenticate your Google Cloud Firestore and LinkedIn Data Scraper accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I enrich my Firestore leads using LinkedIn Data Scraper?
Yes, you can! With Latenode, enrich leads in Firestore using scraped LinkedIn data. Automate the process, saving time, improving data quality, and enabling personalized outreach at scale.
What types of tasks can I perform by integrating Google Cloud Firestore with LinkedIn Data Scraper?
Integrating Google Cloud Firestore with LinkedIn Data Scraper allows you to perform various tasks, including:
- Automatically back up LinkedIn profile data to Google Cloud Firestore.
- Update Firestore records with the latest LinkedIn profile information.
- Trigger alerts based on changes in LinkedIn profiles stored in Firestore.
- Analyze LinkedIn data from Firestore using Latenode's built-in data tools.
- Create custom reports on LinkedIn profiles using Firestore data.
How does Latenode handle large Firestore datasets?
Latenode offers efficient data handling and scalability. Process large datasets from Firestore by using JavaScript code and pagination.
Are there any limitations to the Google Cloud Firestore and LinkedIn Data Scraper integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by LinkedIn Data Scraper may affect data extraction speed.
- Complex data transformations may require JavaScript knowledge for optimal performance.
- Changes to LinkedIn's website structure can impact the accuracy of scraped data.