How to Scrape LinkedIn Company Employees to CSV (2026)

Most ABM and account-based outreach starts the same way: pick a target account, then list every person inside that account who matches your ICP. The "list every person" step is where teams burn hours copying URLs into a spreadsheet. Here is the clean way to do it in 2026.

Step 1. Install the Chrome extension

Sign up for a free Leadsforlinked account. You start with 100 leads, no card. Install the Chrome extension and pin it to your toolbar.

Step 2. Open the company page on LinkedIn

Search the company on LinkedIn, click into its company page, then click the People tab. You will see the full employee count and a filter bar (job function, seniority, location, school, current company).

If you want all employees, skip the filter. If you want a specific slice ("engineering team in Paris"), set the filters in LinkedIn's native UI first. Leadsforlinked respects whatever filter you applied.

Step 3. Click Extract

Click the Leadsforlinked icon in your Chrome toolbar. Choose Company employees as the source. Confirm the scope. The extractor walks the filtered list in the background while you keep working.

1 credit = 1 enriched lead. No double billing.

Step 4. Export to CSV

Open the audience in the web app. Pick the columns you need: full name, current title, current company, location, LinkedIn URL, work email if available. Click Export. CSV downloads in under a minute and is ready to push into HubSpot, Pipedrive, Konekt CRM, Salesforce or any tool that takes a CSV.

For companies over 1,000 employees

LinkedIn's People tab caps visible profiles. To extract a Fortune 500 company cleanly, split the work:

• By department (engineering, sales, marketing, ops, finance, HR)
• By location (each major office as a separate extraction)
• By seniority (founder, C-level, VP, director, manager, IC)

Three or four targeted extractions beat one huge messy one. Dedupe at the end in your CRM.

Why pull a whole company at once

Most LinkedIn prospecting works one person at a time: find a title, find a person, send a message. That works until the deal needs more than one person to say yes, which in B2B is most of the time.

Pulling the employee list flips the order. You start from the account, see everyone in it, and then decide who to approach and in what sequence. That is the difference between hoping you found the decision maker and knowing who sits around them.

Three situations where it is clearly the right method:

• Named account lists. You already know the fifty companies you want. The question is who inside them, and a search by title across all fifty misses anyone whose title is worded unusually.
• Multi-threading a live deal. Your champion goes quiet. Having already mapped their colleagues means you have somewhere to go that is not a follow-up email to the same person.
• Understanding a buying committee. Before the first call, knowing whether the company has a dedicated ops function, or whether the founder still runs it, changes what you say.

Working out who actually matters inside the list

A 200-row employee export is not 200 prospects. It is usually three or four people who matter and a lot of context.

A practical way to sort it. First, the economic buyer: whoever owns the budget line, usually a department head or, at smaller companies, a founder. Second, the champion: the person who feels the problem daily and would benefit most, typically a level below. Third, the blocker: often IT, security, procurement or finance, and worth knowing about early rather than discovering in week six.

Company size changes this shape completely. Under about thirty people, the founder is all three. Over about five hundred, the champion may not even know who signs. Sorting your export by seniority before you do anything else makes that structure visible in a couple of minutes.

What the export contains

Each employee comes out as a row with first name, last name, headline, job title, location and the public profile URL, names split into columns and normalised, duplicates removed. It opens cleanly in a spreadsheet and imports into a CRM without manual cleanup.

One credit equals one lead. If someone appears in two exports, for example because you pulled a company twice, the duplicate is caught and the credit returns to your balance automatically.

Limits worth knowing before you start

• Not everyone lists their employer. Some profiles do not connect to the company page in a structured way, so a company with 500 staff may surface fewer than 500 profiles. That is a LinkedIn data limit, not an extraction one.
• Out-of-network profiles. People far outside your network can display as LinkedIn Member with no public profile behind them. Those cannot be exported by any tool.
• Search result caps. LinkedIn limits any single result set, so very large companies need splitting by function or location rather than pulling in one pass.
• Free plan pacing. Leads are released 20 at a time every hour on the free plan, so a large company arrives in batches. Nothing is lost; the import resumes where it stopped.

Common mistakes

• Messaging the whole list. Several people at one company receiving near-identical outreach in the same week is the fastest way to get discussed internally, and not in a good way.
• Starting at the top. Opening with the CEO of a 400-person company usually produces silence. Starting with the person who has the problem, then being referred upward, works better and takes less time.
• Ignoring recent joiners. Someone three months into a role is far more open to changing a process than someone who chose the current one.
• Treating the export as a contact list. It is a map of an organisation. The value is in reading the structure, not in blasting the rows.

GDPR posture

Leadsforlinked extracts only public profile data . same data you would see by opening each profile manually. The data controller in any subsequent outreach is you, the user. We provide opt-out reminders for any campaign you launch, and EU infrastructure for storage. The full posture is detailed in our LinkedIn scraping GDPR guide.

Sources & further reading

• LinkedIn help: viewing company employees . official documentation on the People tab.
• GDPR.eu . Personal data definitions . what counts as personal data in a B2B context.
• EDPB guidelines on controllers and processors . clarifies your role when running extraction.

Frequently asked questions