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

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Authenticate pdfFiller
Now, click the pdfFiller node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your pdfFiller settings. Authentication allows you to use pdfFiller through Latenode.
Configure the LinkedIn Data Scraper and pdfFiller 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 pdfFiller 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring LinkedIn Data Scraper, pdfFiller, 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 pdfFiller integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and pdfFiller (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 pdfFiller
LinkedIn Data Scraper + pdfFiller + Email: Scrapes LinkedIn profile data using the LinkedIn Data Scraper, converts the data to a PDF document using pdfFiller, and then sends the PDF document as an email attachment to specified email addresses.
LinkedIn Data Scraper + pdfFiller + HubSpot: Retrieves LinkedIn profile data, converts it to a PDF document using pdfFiller. Then, creates or updates a contact in HubSpot with a link to the generated PDF.
LinkedIn Data Scraper and pdfFiller 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 pdfFiller
Automate PDF workflows with pdfFiller in Latenode. Fill, sign, and edit PDFs automatically as part of larger processes. Need to pre-fill contracts from a database, route signed documents to storage, or update records based on PDF content? Integrate pdfFiller into Latenode for scalable, no-code automation without per-step fees, and add custom logic if needed.
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FAQ LinkedIn Data Scraper and pdfFiller
How can I connect my LinkedIn Data Scraper account to pdfFiller using Latenode?
To connect your LinkedIn Data Scraper account to pdfFiller 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 pdfFiller accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically populate pdfFiller forms with LinkedIn data?
Yes, you can! Latenode lets you map scraped LinkedIn Data Scraper data directly into pdfFiller templates, automating document creation and saving significant time.
What types of tasks can I perform by integrating LinkedIn Data Scraper with pdfFiller?
Integrating LinkedIn Data Scraper with pdfFiller allows you to perform various tasks, including:
- Automatically creating contracts with scraped prospect data.
- Generating personalized reports with LinkedIn insights.
- Populating application forms using LinkedIn profiles.
- Building automated lead generation and outreach processes.
- Creating candidate profiles from LinkedIn data for HR.
How secure is LinkedIn Data Scraper data processing on Latenode?
Latenode uses advanced encryption and security protocols to protect your data during LinkedIn Data Scraper and pdfFiller workflows.
Are there any limitations to the LinkedIn Data Scraper and pdfFiller integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex pdfFiller templates might require adjustments for optimal data mapping.
- Rate limits of LinkedIn Data Scraper can affect the speed of large-scale data extraction.
- JavaScript coding might be needed to perform advanced data transformations.