What Does BrowserAct LinkedIn Email Scraper Do?
Collect email addresses that people display on their LinkedIn profiles, together with their names, roles, companies and source links. Start with profile URLs you already have, connect your LinkedIn account and review the available contact information in a structured export.
Email availability depends on what your signed-in account can see. This template extracts visible addresses; it does not guess missing emails or verify whether an inbox can receive messages.
Key Features of LinkedIn Email Scraper
Submit multiple exact profile URLs in one run. Keep one row per person, including people without a visible email. Review names, companies, headlines, observed addresses and their source sections, then download CSV and JSON files.
How to Use LinkedIn Email Scraper
1. Open the template
Open the published template and use its Run tab. Configure your own LinkedIn Website Login before your first run. Create an editable duplicate only if you need to change the Bot logic.
2. Connect LinkedIn
In Browser settings, choose Standard Browser and save it. Configure your LinkedIn login using the supported account credentials, cookie import or manual login method. Use the browser settings available for your own account; author credentials and proxy access are not included. Confirm that the Bot can open the profiles before starting extraction.
3. Add your profile URLs
Enter exact LinkedIn personal profile URLs, separated by semicolons or commas in the single-line input. Start with one profile whose email you can see when signed in. The input accepts 1–10 distinct URLs. A two-profile batch has been tested; a ten-profile run has not been validated.
4. Run and review the export
Run the Bot, then inspect the returned profiles and email availability. Download the email table and the profile audit. Keep profiles without visible emails in the audit so you can distinguish missing contact details from a failed run.
Input Parameters
| Parameter | What to enter |
|---|---|
| profile_urls | 1–10 exact personal profile URLs, separated by semicolons or commas. Duplicate URLs and tracking parameters are removed. Default: https://www.linkedin.com/in/dina-popowski-a4392344/; https://www.linkedin.com/in/ernabalayan/ . Two-profile batch tested. Adjacent https:// URLs are also separated safely if line breaks are removed by the form. |
What Data Can I Extract?
| Data | Meaning |
|---|---|
| Name and LinkedIn URL | The person whose profile was checked. |
| Headline and company | Visible professional context, when available. |
| An address actually observed on the target profile. | |
| Email source | The profile or Contact info URL and the section where the address appeared. |
| Availability | Whether an email was found, was not visible, or could not be checked because of an access problem. |
| Verification status | Not verified. Finding an address does not establish deliverability. |
Example Output
Example record extracted from a LinkedIn profile. Email visibility varies by profile and by your signed-in account.
| Field | Result |
|---|---|
| full_name | Dina Popowski |
| company | Addison Group |
| headline | HR Professional Recruiter - Let’s connect email me at dina.popowski@addisongroup.com |
| dina.popowski@addisongroup.com | |
| email_status | found |
| verification_status | not_verified |
| linkedin_url | https://www.linkedin.com/in/dina-popowski-a4392344/ |
| email_source_url | https://www.linkedin.com/in/dina-popowski-a4392344/ |
| email_source_section | Introduction |
| checked_at | 2026-11-03T02:57:57.714331+00:00 |
| error_message |
How Does It Work?
The workflow opens each supplied profile, reads the person’s visible introduction and About section, and checks the native Contact info dialog. Each extracted email stays associated with that person and its observed source. Duplicate profile URLs and repeated email addresses within the same profile are removed.
Only text currently visible in the introduction, About section and Contact info is checked. Collapsed About text is not expanded. Email discovery through external databases, domain guessing and email verification are outside this version’s scope.
How to Build a New Scraper Bot with Agent Built
1. Describe the profile information you need and which account-visible sources the Bot should use.
2. Let Agent Built build and test the Bot. Review its inputs and login requirements.
3. Run the completed Bot with your own account and review the structured results and exports.
Why Use LinkedIn Email Scraper?
Turn a prepared list of profile URLs into a source-linked contact research file. Keeping people without visible emails makes gaps clear and helps you decide which records need further research.
Who Can Use LinkedIn Email Scraper?
Sales researchers, recruiters and operations teams who already have LinkedIn profile URLs and need to organize the contact details visible to their account.
How Many Results Can You Scrape?
Each run accepts 1–10 distinct personal profile URLs. Start with a small batch and inspect the results. The number of email addresses depends on profile visibility; a profile with no visible email remains in the people table. Login or access failures are reported for review.
Automation and Export
BrowserAct returns structured people records and downloadable CSV and JSON files. Use leads.csv for the complete person list and emails.csv for observed profile–email pairs. API automation requires an authenticated runtime with the caller’s own LinkedIn session; consult the API tab when available. CSV files can also be imported into your existing research tools.
Downloads and Missing Emails
The native download package contains leads.csv, emails.csv, profile_audit.csv, result.json and audit.json. The primary result table and leads.csv keep one row for every requested person, including people without a visible email. The original summary and source evidence are stored in audit.json. The email table has one observed profile–email pair per row. The audit includes every input profile, including those without a visible address. The native exports are CSV and JSON.
Check email_status and error_message before using the export. A checked profile without a visible email is retained as not_visible in the audit. Do not interpret an empty email table as a list of verified contacts. Login, access and verification issues need review before another run.
Need Help?
Join the Discord Community or email service@browseract.com.
