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

Add the LinkedIn Data Scraper Node
Select the LinkedIn Data Scraper node from the app selection panel on the right.

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

LinkedIn Data Scraper
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Fibery
Authenticate Fibery
Now, click the Fibery node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Fibery settings. Authentication allows you to use Fibery through Latenode.
Configure the LinkedIn Data Scraper and Fibery 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 LinkedIn Data Scraper and Fibery 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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Fibery
Trigger on Webhook
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LinkedIn Data Scraper
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring LinkedIn Data Scraper, Fibery, 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 LinkedIn Data Scraper and Fibery integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and Fibery (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect LinkedIn Data Scraper and Fibery
LinkedIn Data Scraper + Fibery + Slack: When LinkedIn Data Scraper finds potential leads by searching people, a new entity is created in Fibery, and a notification is sent to project managers in Slack.
Fibery + LinkedIn Data Scraper + Google Sheets: When a new client is added to Fibery, use LinkedIn Data Scraper to get profile data by URL and fill the client's details into a Google Sheet.
LinkedIn Data Scraper and Fibery integration alternatives
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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About Fibery
Sync Fibery's structured data—tasks, projects, wikis—into Latenode for automated workflows. Trigger actions like sending notifications on status changes or updating other tools. Latenode adds logic and integrations Fibery lacks, building complex flows with no code. Automate cross-functional workflows beyond Fibery's native capabilities.
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FAQ LinkedIn Data Scraper and Fibery
How can I connect my LinkedIn Data Scraper account to Fibery using Latenode?
To connect your LinkedIn Data Scraper account to Fibery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select LinkedIn Data Scraper and click on "Connect".
- Authenticate your LinkedIn Data Scraper and Fibery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically update Fibery with new LinkedIn leads?
Yes, you can! Latenode allows real-time updates using webhooks and advanced data transformations, keeping your Fibery workspace current with fresh LinkedIn Data Scraper data.
What types of tasks can I perform by integrating LinkedIn Data Scraper with Fibery?
Integrating LinkedIn Data Scraper with Fibery allows you to perform various tasks, including:
- Enrich Fibery accounts with scraped LinkedIn profile information.
- Create new Fibery tasks from LinkedIn search results.
- Automatically update lead status in Fibery based on LinkedIn activity.
- Generate reports in Fibery using LinkedIn data trends.
- Track competitor employee data directly in Fibery using LinkedIn data.
How does Latenode handle large data volumes from LinkedIn Data Scraper?
Latenode is designed for scalability, efficiently processing large datasets from LinkedIn Data Scraper with robust error handling and queue management.
Are there any limitations to the LinkedIn Data Scraper and Fibery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by LinkedIn Data Scraper and Fibery APIs apply.
- Complex data transformations may require JavaScript knowledge.
- Initial setup requires understanding of both platforms' data structures.