Lead generation can become very repetitive when you are manually searching LinkedIn Sales Navigator, copying profile details, checking whether the scraper has finished, and then adding every lead into a CRM or database.
To solve this, I built a simple n8n workflow that connects LinkedIn Sales Navigator, Apify, and Airtable to automate the lead collection process.
The goal of this workflow is simple:
Capture leads from LinkedIn Sales Navigator, wait until the Apify dataset is ready, and then automatically add those leads into Airtable or a CRM.
Workflow Overview
The workflow starts with a manual trigger for testing. Once triggered, it sends a request to an Apify LinkedIn Sales Navigator scraper using the Sales Navigator input URL.
After the scraper starts, n8n retrieves the dataset and checks whether the data is available. This step is important because Apify scraping jobs do not always return results instantly. Sometimes the dataset takes a little time to become available.
If the dataset is ready, n8n sends the scraped lead data into Airtable and creates new CRM records. If the dataset is not ready yet, the workflow waits and checks again.
Main Workflow Steps
The workflow follows this structure:
Manual Trigger
Starts the workflow for testing.
LinkedIn Sales Navigator Scraper
Sends the Sales Navigator search input to Apify.
Merge Node
Combines the input data and scraper response so the workflow can continue with the right context.
Retrieve Dataset
Fetches the dataset generated by Apify.
Verify Dataset Availability
Checks whether the dataset contains lead data.
IF Node
Routes the workflow based on whether the dataset is ready.
Add Leads to CRM
If the dataset is available, the leads are added to Airtable or another CRM.
Wait Node
If the dataset is not ready, the workflow waits and retries.
Why This Workflow Is Useful
This setup is useful for sales teams, agencies, recruiters, and B2B companies that collect leads from LinkedIn Sales Navigator and want to reduce manual work.
Instead of copying leads manually, the workflow can automatically collect, verify, and store lead data in a structured system.
It also makes the process more reliable because the workflow does not assume the dataset is ready immediately. It checks availability first, waits if needed, and only moves forward when the data is ready.
Possible Improvements
This workflow can be extended further by adding:
Duplicate checking before adding leads to Airtable
Lead enrichment using email finder or company data APIs
Slack notifications when new leads are added
Filters based on job title, location, company size, or industry
Automatic assignment of leads to sales reps
CRM integrations with HubSpot, GoHighLevel, Pipedrive, or Salesforce
AI-based lead scoring before storing the record
Important Note
When using scraping tools, always make sure you are following the platform’s terms of service and only processing data you are allowed to access and use.
Final Thoughts
This workflow shows how n8n can be used as the logic layer between different tools. Apify handles the scraping, n8n manages the workflow logic, and Airtable or the CRM stores the final lead data.
It is a simple but powerful example of how automation can turn a manual lead generation process into a repeatable and scalable system.
