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

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Authenticate Motion
Now, click the Motion node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Motion settings. Authentication allows you to use Motion through Latenode.
Configure the LinkedIn Data Scraper and Motion 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 Motion 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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AI Anthropic Claude 3
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Motion
Trigger on Webhook
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Save and Activate the Scenario
After configuring LinkedIn Data Scraper, Motion, 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 Motion integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and Motion (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 Motion
LinkedIn Data Scraper + Motion + Slack: When a new lead is scraped from LinkedIn using LinkedIn Data Scraper and a task is created in Motion, a message is sent to a specified Slack channel containing the lead details and Motion task information.
Motion + LinkedIn Data Scraper + Pipedrive: When a new task event occurs in Motion, the workflow gets the lead's profile data from LinkedIn Data Scraper and then updates the lead details in Pipedrive with the information obtained from LinkedIn.
LinkedIn Data Scraper and Motion 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 Motion
Use Motion in Latenode to auto-schedule tasks and projects based on real-time data. Trigger Motion updates from other apps, or update other tools when Motion tasks change. Connect it to your CRM or calendar, and automate team workflows. The low-code editor simplifies customization, ensuring tasks are prioritized and deadlines are met across all platforms.
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See how Latenode works
FAQ LinkedIn Data Scraper and Motion
How can I connect my LinkedIn Data Scraper account to Motion using Latenode?
To connect your LinkedIn Data Scraper account to Motion 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 Motion accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically create Motion tasks from scraped LinkedIn profiles?
Yes, you can! Latenode allows seamless data transfer between LinkedIn Data Scraper and Motion. Automatically generate tasks for outreach, powered by AI-enhanced profile summaries, saving you time.
What types of tasks can I perform by integrating LinkedIn Data Scraper with Motion?
Integrating LinkedIn Data Scraper with Motion allows you to perform various tasks, including:
- Create Motion tasks for promising LinkedIn leads.
- Schedule follow-up activities based on scraped data.
- Prioritize tasks in Motion using LinkedIn profile details.
- Update Motion project timelines with scraped milestones.
- Automate lead enrichment using scraped LinkedIn information.
Can I filter LinkedIn Data Scraper results before they are sent to Motion?
Yes! Latenode provides advanced filtering options, allowing you to send only qualified leads to Motion based on specific criteria you define.
Are there any limitations to the LinkedIn Data Scraper and Motion 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 workflow speed.
- Motion's API limitations may restrict certain task creation options.
- Data transformations may require JavaScript knowledge for complex cases.