> ## Documentation Index
> Fetch the complete documentation index at: https://docs.markifact.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Get Profile Details

> Extract detailed information from LinkedIn profiles for lead generation and research.

**Get Profile Details** scrapes comprehensive information from LinkedIn profiles including name, headline, location, experience, and other professional details. Perfect for lead generation, prospect research, and building contact databases.

***

## When to Use It

* Research prospects before sales outreach
* Build detailed contact databases for lead generation
* Verify and enrich existing contact information
* Gather professional background for personalized messaging
* Create comprehensive prospect profiles for CRM systems

***

## Inputs

| Field                      | Type | Required | Description                                                  |
| -------------------------- | ---- | -------- | ------------------------------------------------------------ |
| **URL Input Type**         | Tabs | Yes      | Choose "Single Profile" or "Multiple Profiles"               |
| **Profile URL/Username**   | Text | Yes\*    | LinkedIn profile URL or username (\*For Single Profile)      |
| **Profile URLs/Usernames** | List | Yes\*    | List of LinkedIn URLs or usernames (\*For Multiple Profiles) |

### URL Format Options

**Full URL:**

```
https://www.linkedin.com/in/john-doe13/
```

**Username Only:**

```
john-doe13
```

Both formats work - the system will process either format automatically.

***

## Outputs

The node returns comprehensive profile information including:

| Field           | Description                        |
| --------------- | ---------------------------------- |
| **Name**        | Full name of the profile owner     |
| **Headline**    | Professional headline/title        |
| **Location**    | Geographic location                |
| **About**       | Profile summary/about section      |
| **Experience**  | Work history and positions         |
| **Education**   | Educational background             |
| **Connections** | Number of connections (if visible) |
| **Profile URL** | Standardized LinkedIn profile URL  |

***

## Credit Cost

10 credits per profile processed.

***

## Real-World Examples

**CRM Enrichment:**

```
Sheets Read Data (contact list) → Get Profile Details → Rename Fields → Write back to Sheets
"Enrich existing CRM contacts with detailed LinkedIn information"
```

**Lead Qualification:**

```
Get Profile Details → AI Analyze Data → Conditional Split
"Analyze prospect profiles and route qualified leads to sales team"
```

***

## FAQ

<Accordion title="Do I need to be connected to the profile to get their details?">
  No, this scrapes publicly available information from LinkedIn profiles. However, some profiles may have privacy settings that limit what information is visible to non-connections.
</Accordion>

<Accordion title="What happens if a profile doesn't exist or is private?">
  The node will return an error or limited data for non-existent or highly restricted profiles. Consider this when processing large lists - some profiles may not return complete data.
</Accordion>

<Accordion title="Can I process the same profile multiple times?">
  Yes, but each processing uses 10 credits even if it's the same profile. Use Remove Duplicates on your input list to avoid unnecessary costs.
</Accordion>

<Accordion title="How current is the profile data?">
  The data is scraped in real-time when you run the workflow, so it reflects the current state of the profile at the time of processing.
</Accordion>

<Accordion title="What's the difference between single and multiple profile modes?">
  Single mode processes one profile at a time, while multiple mode can process a list of profiles in bulk. Use multiple mode for efficiency when processing many profiles.
</Accordion>

<Accordion title="Are there any limits on how many profiles I can process?">
  The main limit is your available credits (10 credits per profile). There may also be rate limiting to prevent abuse, so consider processing large lists in smaller batches.
</Accordion>