Introduction

Manual LinkedIn data collection is time-consuming, error-prone, and results
in inconsistent data quality across CRM/database records.

This workflow is great for organizations that struggle with:

• Incomplete contact records with only LinkedIn URLs but missing profile
  details
• Hours spent manually copying LinkedIn information into databases
• Inconsistent data formats due to copy-paste from LinkedIn (emojis, styled
  text, special characters)
• Outdated profile information that doesn't reflect current roles/companies
• No systematic way to enrich contacts at scale

Primary Users

1. Sales & Marketing Teams
2. Event Organizers & Conference Managers for event materials
3. Recruitment & HR Professionals
4. CRM Administrators

Specific Problems Addressed

1. Data Completeness: Automatically fills missing profile fields (headline,
   bio, skills, experience)
2. Data Quality: Sanitizes problematic characters that break
   databases/exports
3. Time Efficiency: Reduces hours of manual data entry to automated monthly
   updates
4. Error Handling: Gracefully manages invalid/deleted LinkedIn profiles
5. Scalability: Processes multiple profiles in batch without manual
   intervention
6. Standardization: Ensures consistent data format across all records

Cost

Each URL scraped by Apify costs $0.01 to get all the data above. Apify charges per scrape, regardless of how much dta or fields you extract/use.

Setup Instructions

Prerequisites

1. n8n Instance: Access to a running n8n instance (self-hosted or cloud)
2. NocoDB Account: Database with a table containing LinkedIn URLs
3. Apify Account: Free or paid account for LinkedIn scraping

Required fields in NocoDB table

Input:

• single LinkedIn URL

NocoDB Field name

LinkedIn

Output:

• first/last/full name
• e-mail
• bio
• headline
• profile pic URL
• current role
• country
• skills
• current employer
• employer URL
• experiences (all previous jobs)
• personal website
• publications (articles)

NocoDB Field names

linkedin_full_name
linkedin_first_name: 
linkedin_headline:
linkedin_email:
linkedin_bio:
linkedin_profile_pic
linkedin_current_role
linkedin_current_company
linkedin_country
linkedin_skills
linkedin_company_website
linkedin_experiences
linkedin_personal_website
linkedin_publications
linkedin_scrape_error_reason
linkedin_scrape_last_attempt
linkedin_scrape_status
linkedin_last_modified

Technically you also need an Id field, but that is always there so no need to add it :)

n8n Setup

1. Import the Workflow

- Copy the workflow JSON from the template
- In n8n, click "Add workflow" → "Import from JSON"
- Paste the workflow and click "Import"

2. Configure NocoDB Connection

- Click on any NocoDB node in the workflow
- Add new credentials → "NocoDB Token account"
- Enter your NocoDB API token (found in NocoDB → User Settings → API

Tokens)
- Update the projectId and table parameters in all NocoDB nodes

3. Set Up Apify Integration

- Create an Apify account at apify.com
- Generate an API token (Settings → Integrations → API)
- In the workflow, update the Apify token in the "Get Scraper Results"

node
- Configure HTTP Query Auth credentials with your token

4. Map Your Database Fields

- Review the "Transform & Sanitize Data" node
- Update field mappings to match your NocoDB table structure
- Ensure these fields exist in your table:
    - LinkedIn (URL field)
  - linkedin_headline, linkedin_full_name, linkedin_bio, etc.
  - linkedin_scrape_status, linkedin_last_modified

5. Configure the Filter

- In "Get Guests with LinkedIn" node
- Adjust the filter to match your requirements
- Default: (LinkedIn,isnot,null)~and(linkedin_headline,is,null)

6. Test the Workflow

- Click "Execute Workflow" with Manual Trigger
- Monitor execution for any errors
- Verify data is properly updated in NocoDB

7. Activate Automated Schedule

- Configure the Schedule Trigger node (default: monthly)
- Toggle the workflow to "Active"
- Monitor executions in n8n dashboard

Customization Options

1. Data Source Modifications

• Different Database: Replace NocoDB nodes with Airtable, Google Sheets, or
  PostgreSQL
• Multiple Tables: Add parallel branches to process different contact tables
• Custom Filters: Modify the WHERE clause to target specific record subsets

2. Enrichment Fields

• Add Fields: Include additional LinkedIn data like education,
  certifications, or recommendations
• Remove Fields: Simplify by removing unnecessary fields (publications,
  skills)
• Custom Transformations: Add business logic for field calculations or
  formatting

3. Scheduling Options

• Frequency: Change from monthly to daily, weekly, or hourly
• Time-based: Set specific times for different timezones
• Event-triggered: Replace with webhook trigger for on-demand processing

4. Error Handling Enhancement

• Notifications: Add email/Slack nodes to alert on failures
• Retry Logic: Implement wait and retry for temporary failures
• Logging: Add database logging for audit trails

5. Data Quality Rules

• Validation: Add IF nodes to validate data before updates
• Duplicate Detection: Check for existing records before creating new ones
• Data Standardization: Add custom sanitization rules for industry-specific
  needs

6. Integration Extensions

• CRM Sync: Add nodes to push data to Salesforce, HubSpot, or Pipedrive
• AI Enhancement: Use OpenAI to summarize bios or extract key skills
• Image Processing: Download and store profile pictures locally

7. Performance Optimization

• Batch Size: Adjust the number of profiles processed per run
• Rate Limiting: Add delays between API calls to avoid limits
• Parallel Processing: Split large datasets across multiple workflow
  executions

8. Compliance Additions

• GDPR Compliance: Add consent checking before processing
• Data Retention: Implement automatic cleanup of old records
• Audit Logging: Track who accessed what data and when

These customizations allow the workflow to adapt from simple contact enrichment to complex data pipeline scenarios across various industries and use cases.