Count a company's people on LinkedIn
Fetch the counts on a company's People tab: where its people live, what they do, where they studied, what they are skilled at, each as a list of names and member counts. Use this to size a team, or to see where a company hires.
https://api.scrapefield.com/v1/linkedin/employee-statshttps://api.scrapefield.com/v1/linkedin/employee-stats?company_id=7050In your code
const params = new URLSearchParams({
"company_id": "1035"
});
const res = await fetch(`https://api.scrapefield.com/v1/linkedin/employee-stats?${params}`, {
headers: { Authorization: `Bearer ${process.env.SCRAPEFIELD_KEY}` },
});
const { data, meta } = await res.json();
console.log(data, meta.credits_charged);Parameters
| Parameter | What it does |
|---|---|
url | The company page URL. |
vanity_name | The part after /company/ in the URL. |
company_id | LinkedIn's numeric id for the company: company_id in linkedin/company. The fastest of the three. |
fresh | Skip the cache and fetch now. Charged normally. Not available on trial credits — buy any pack to unlock it. default false |
Response
Returns one linkedin_employee_stats. This is the demo’s answer, the one the playground above returns, in full rather than abbreviated — including the fields that come back null, because a field is null when the platform does not show it and you should know which ones those are before you build on them. A call with your key returns the account you ask for.
{
"data": {
"company_id": "8855339",
"vanity_name": "blue-door-coffee",
"url": "https://www.linkedin.com/company/blue-door-coffee/",
"stats": [
{
"dimension": "Where they live",
"values": [
{
"name": "Copenhagen, Denmark",
"count": 287
},
{
"name": "Brooklyn, United States",
"count": 264
},
{
"name": "Berlin, Germany",
"count": 191
},
{
"name": "Lisbon, Portugal",
"count": 158
},
{
"name": "Austin, United States",
"count": 19
}
]
},
{
"dimension": "What they do",
"values": [
{
"name": "Operations",
"count": 353
},
{
"name": "Engineering",
"count": 332
},
{
"name": "Finance",
"count": 150
},
{
"name": "Sales",
"count": 51
},
{
"name": "Marketing",
"count": 21
}
]
},
{
"dimension": "Where they studied",
"values": [
{
"name": "Technische Universität Berlin",
"count": 313
},
{
"name": "The University of Texas at Austin",
"count": 266
},
{
"name": "Technical University of Denmark",
"count": 136
},
{
"name": "Universidade de Lisboa",
"count": 82
}
]
},
{
"dimension": "What they are skilled at",
"values": [
{
"name": "TypeScript",
"count": 334
},
{
"name": "Product Strategy",
"count": 236
},
{
"name": "Data Modeling",
"count": 201
},
{
"name": "Go",
"count": 160
},
{
"name": "Figma",
"count": 152
},
{
"name": "PostgreSQL",
"count": 75
}
]
}
]
},
"meta": {
"request_id": "req_7f3ac1e94b2d40f8a1c6e5d2",
"credits_charged": 7,
"credits_remaining": 74218,
"cached": false,
"fetched_at": "2026-09-20T09:12:03Z",
"next_cursor": null
}
}Fields of linkedin_employee_stats
Who works at a company, counted: where they live, what they do, where they studied, what they are skilled at. Named after the words LinkedIn prints, since LinkedIn has no official data API.
| Field | What it is |
|---|---|
company_id | LinkedIn's numeric id for the company. |
vanity_name | The part after /company/ in the page URL. |
url | The company page. |
stats | One block per question the People tab answers. |
stats[].dimension | What LinkedIn counts them by, as its People tab names it: "Where they live", "What they do", "Where they studied", … |
stats[].values | The largest first. |
stats[].values[].name | What is counted: a place, a job function, a school, … |
stats[].values[].count | How many members. |
What it costs
7 credits per successful call, whether we fetch it or serve it from cache — you pay for the answer, not for how we produced it. Responses are cached for 7 days and a cached one tells you when the data was actually fetched. A call we fail costs 0 and is refunded automatically.
On the smallest pack that is $5.46 per 1,000 calls; on the largest, $3.08. The full table.
Questions
How much does the LinkedIn company employee insights API cost?
7 credits a call: $5.46 per 1,000 calls on the smallest pack and $3.08 on the largest. A call that fails costs nothing, and the refund is automatic. A cached answer costs the same as a fresh one. Credits are bought in packs and never expire; there is no subscription.
Do I need a LinkedIn account, a login or cookies?
No. You need a key from us and nothing from LinkedIn. We never take a customer's login, cookies or session, at any price, and no account of yours is ever at risk.
Can I try it without signing up?
Yes. Add demo=true and leave the key out, or press Send request in the playground on this page. The demo answers with a real answer about Ferrari, captured once a week, in exactly the shape a live call returns, whatever you ask, and charges nothing.
How fresh is the data?
An answer is kept for up to 7 days, and a cached one says when it was fetched, in meta.fetched_at. Add fresh=true to fetch it again now, at the same price; it needs any purchase, not the trial.
What does it return?
One linkedin_employee_stats object. Its fields are named after the words LinkedIn prints, since LinkedIn has no official data API. A field is null when LinkedIn does not show it, never missing. Every field is described on this page.
Can an AI agent call it?
Yes: it is the MCP tool get_linkedin_employee_stats on our MCP server, with the same parameters, answer and price. Without a key, the tool answers from the demo.