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

LinkedIn Data Scraper
⚙
Lark
Authenticate Lark
Now, click the Lark node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Lark settings. Authentication allows you to use Lark through Latenode.
Configure the LinkedIn Data Scraper and Lark 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 Lark 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
⚙
AI Anthropic Claude 3
⚙
Lark
Trigger on Webhook
⚙
LinkedIn Data Scraper
⚙
⚙
Iterator
⚙
Webhook response
Save and Activate the Scenario
After configuring LinkedIn Data Scraper, Lark, 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 Lark integration works as expected. Depending on your setup, data should flow between LinkedIn Data Scraper and Lark (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 Lark
LinkedIn Data Scraper + Lark + Slack: Scrapes LinkedIn for specific job postings based on keywords. Relevant job postings are then sent to a Lark group chat for review. Finally, a summary notification is sent to a designated Slack channel.
Lark + LinkedIn Data Scraper + Google Sheets: When a new message is posted to a specified Lark group chat, the flow triggers a search for corresponding lead data from LinkedIn, then archives the relevant discussion messages from Lark along with the scraped LinkedIn lead data into a Google Sheet.
LinkedIn Data Scraper and Lark 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.
Similar apps
Related categories
About Lark
Use Lark within Latenode to centralize team comms & automate notifications based on workflow triggers. Aggregate messages, streamline approvals, and post updates to specific channels. Benefit from Latenode's visual editor and logic tools for advanced routing that keeps everyone informed and aligned.
Similar apps
Related categories
See how Latenode works
FAQ LinkedIn Data Scraper and Lark
How can I connect my LinkedIn Data Scraper account to Lark using Latenode?
To connect your LinkedIn Data Scraper account to Lark 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 Lark accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I send new LinkedIn leads to Lark channels?
Yes, you can! Latenode allows automating this in a few clicks. Trigger workflows from LinkedIn Data Scraper to instantly notify your team on Lark. Improve lead response time and collaboration.
What types of tasks can I perform by integrating LinkedIn Data Scraper with Lark?
Integrating LinkedIn Data Scraper with Lark allows you to perform various tasks, including:
- Automatically posting new scraped leads to a Lark group.
- Sending daily summaries of LinkedIn Data Scraper results.
- Creating Lark tasks for each new identified prospect.
- Notifying team channels upon competitor profile updates.
- Alerting sales reps in Lark on new qualified leads.
Can I filter data from LinkedIn Data Scraper before sending to Lark?
Yes, you can filter scraped data easily using Latenode's no-code logic blocks or JavaScript. Send only the most relevant information to Lark, keeping your team focused.
Are there any limitations to the LinkedIn Data Scraper and Lark integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by LinkedIn Data Scraper and Lark APIs.
- The complexity of advanced data transformations may require JavaScript.
- Historical data migration requires custom workflow design.