Find LinkedIn Profiles from Names in CSV or Excel - In Bulk

Need to find LinkedIn profile URLs from a list of names?

Datablist's LinkedIn Profile Finder from Name enrichment searches for LinkedIn profiles in bulk from a CSV or Excel file. Give it a full name, or first name and last name, and add a keyword such as company name, school, job title, or location to improve the match.

Use it for sales prospecting, recruiting, CRM cleaning, event lists, alumni lists, and lead enrichment.

What This Enrichment Does

This enrichment looks for a matching LinkedIn profile URL for each row in your list.

It can use:

• Full name
• First name and last name
• A keyword to narrow the search
• A target country for Google search results
• A strict name-match option to filter weak matches

For each row, Datablist returns:

• LinkedIn Page - The LinkedIn profile URL when found.
• LinkedIn Profile Page Title - The title from the search result. It often includes role, company, or location.
• LinkedIn Profile Summary - The search result snippet when available.
• Profile Confidence - High, Medium, Low, or Very Low.
• Processed - A status flag to avoid running the same row again.

Rows with no input name are marked as an error and cost 0 credits.

Why Use a LinkedIn Profile Finder?

Finding LinkedIn profiles by hand takes time.

If you have 100 people in a spreadsheet, you can search manually. If you have 5,000 leads, candidates, speakers, or customers, manual search breaks fast.

This enrichment helps you:

• Find LinkedIn URLs from names in bulk
• Enrich lead lists before outreach
• Match candidates to LinkedIn profiles
• Clean CRM contacts with missing LinkedIn URLs
• Prepare account research for sales teams
• Add profile links to event attendee lists
• Review confidence before trusting a match

Best Inputs for Better Results

A name alone can work, but many people share the same name.

Add a keyword when you can. Good keywords include:

• Company name
• School or university
• Job title
• City or country
• Website domain
• Industry

Examples:

• Jane Smith + Datablist
• Alex Martin + HEC Paris
• Maria Garcia + Product Manager
• John Lee + Singapore fintech

The keyword helps Datablist pick the profile that matches the person in your file.

Confidence Levels

Datablist returns a confidence level for each profile match.

• High - The name matches well, or the LinkedIn handle matches the full name.
• Medium - The match looks likely, but one part may be shortened or partial.
• Low - Some name evidence exists, but you should review it.
• Very Low - The match is weak.

Use the confidence output to filter your list before outreach.

For sensitive workflows, such as recruiting or investor outreach, review Low and Very Low matches before using them.

Use Cases

Sales Prospecting

Start with a list of prospects from a trade show, website form, company page, or CRM export.

Run the LinkedIn Profile Finder to add profile URLs. Then use the profile title and summary to check role, company, and seniority.

Recruiting

Recruiting lists often start with names, schools, job boards, event attendees, or applicant data.

Add a company, school, or location keyword to improve the match. Then review confidence before contacting candidates.

CRM Cleaning

If your CRM has contacts without LinkedIn URLs, export the contacts to CSV and run this enrichment.

Use the Processed output to avoid rerunning rows that were already checked.

Event and Community Lists

For attendee lists, speaker lists, member lists, or alumni directories, add profile URLs so your team can research people faster.

Use an organization, event name, or school as the keyword when the name is common.

Lead Scoring and Research

LinkedIn profile URLs help later workflows.

You can use them to enrich profiles, check job titles, route leads, or prepare outreach messages.

Pricing Examples

The enrichment costs 2.5 credits per lookup for rows with enough name data to search.

Empty rows cost 0 credits.

Examples:

• 100 people: about 250 credits
• 1,000 people: about 2,500 credits
• 10,000 people: about 25,000 credits

If your list has many empty names, those rows are skipped and marked with an error status.

Learn more about the Datablist Credits System.

Step-by-Step Guide

Step 1: Load Your CSV or Excel File

Create a free account and import your data file.

Datablist works as a CSV editor, so you can open large CSV and Excel files with contact lists, prospect lists, recruiting lists, or CRM exports.

Create a new collection and import your file.

Step 2: Select the "LinkedIn Profile Finder" Enrichment

Click Enrich and search for LinkedIn Profile Finder.

Step 3: Map the Name Fields

Map either:

• Full Name
• Or First Name and Last Name

If your file has both formats, use the full name when it is clean. Use first and last name fields when they are split in your spreadsheet.

Step 4: Add a Keyword

Map the Keyword input when you have context.

Use the company name for sales lists. Use school, location, or job title for recruiting lists.

This helps when several people share the same name.

Step 5: Choose Search Settings

You can set:

• Target Country - Adjusts Google search results by country. Use it when your list is country-specific.
• Skip if not matching name - Skips weak name matches. Enable it when precision matters more than coverage.

If you want more results, leave Skip if not matching name unchecked and filter later with the confidence output.

Step 6: Review the Output

After the run, review:

• LinkedIn profile URL
• Page title
• Profile summary
• Confidence level
• Error status for missing names or no result

For outreach, filter out Low and Very Low matches unless you review them manually.

Tips for Better LinkedIn Profile Matches

• Add a company keyword when possible.
• Use a school keyword for alumni or student lists.
• Set the target country for local lists.
• Keep first and last names clean.
• Remove company names from the name column.
• Review Low and Very Low confidence matches.
• Use the page title to check role and company.
• Use the processed flag to avoid duplicate runs.

FAQ

Can I find LinkedIn profiles from names in bulk?

Yes. Import a CSV or Excel file into Datablist, map the name fields, and run the LinkedIn Profile Finder enrichment.

Do I need a company name?

No. A full name can be enough.

But a company, school, location, or role keyword improves matching when the name is common.

Does it return a confidence score?

Yes. Datablist returns High, Medium, Low, or Very Low confidence.

Use this field to review weak matches before adding them to your CRM or outreach workflow.

What happens if no LinkedIn profile is found?

The row is marked with an error status. You can filter those rows, add a better keyword, and run the enrichment again.

Can I use it for recruiting?

Yes. This is useful for candidate sourcing, alumni lists, event attendees, and applicant research.

Add a keyword such as current company, school, city, or target role to improve results.

Can I use it for sales prospecting?

Yes. Add a company keyword when you have it. Then use the LinkedIn URL, title, and summary to qualify leads or prepare outreach.

Does it scrape private LinkedIn data?

No. The enrichment finds public LinkedIn profile URLs from search results. It does not access private LinkedIn profile data.

How much does it cost?

The listed price is 2.5 credits per lookup for rows with valid name data.

For example, 1,000 lookups cost about 2,500 credits. Empty rows cost 0 credits.