# LinkedIn Post Engagers to Leads + Company Data | $3.99/1K (`cornersight/linkedin-post-engagers-enriched`) Actor

Turn the people who liked or commented on any LinkedIn post into scored leads, $3.99 per 1,000. Job title, company, website, industry, size, country and a free 0 to 100 ICP fit score for each person. No cookies, no login, no start fee.

- **URL**: https://apify.com/cornersight/linkedin-post-engagers-enriched.md
- **Developed by:** [Cornersight](https://apify.com/cornersight) (community)
- **Categories:** Lead generation, Social media
- **Security:** Limited permissions
- **Stats:** 7 total users, 1 monthly users, 100.0% runs succeeded, 8 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $3.19 / 1,000 enriched engagers

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Post Engagers Enriched + ICP Score | $3.99/1K

Turn the people who liked or commented on any LinkedIn post into scored leads, $3.99 per 1,000. Job title, company, website, industry, size, country and a free 0 to 100 ICP fit score for each person. No cookies, no login, no start fee.

### What does it do?

LinkedIn Post Engagers Enriched + ICP Score returns everyone who reacted to or commented on a LinkedIn post, then adds their job title, company, company website, industry, company size, location and country. Tell it your ideal customer and it scores every person from 0 to 100, so you can go straight to the people who fit.

No cookies, no LinkedIn account and no login. You pay only for results delivered to your dataset. No start fee.

### What can you use it for?

- Find the buyers in the crowd that engaged with a competitor's or influencer's post.
- Score your own post engagers against your ICP before outreach.
- Build account lists from the companies whose people engage with a topic.
- Push scored leads to your CRM, HeyReach, PlusVibe or any webhook through Apify integrations.

### How to use it

1. Paste one or more LinkedIn post URLs.
2. Optionally add your ideal customer: job titles, countries, industries and company sizes.
3. Click Start.
4. Sort by icpScore or filter on isIcp = true, then export.

### Pricing

Pay per result. Prices depend on your Apify plan:

| What you pay for | Starter | Scale | Business | Unit |
|---|---|---|---|---|
| Enriched engager | $3.99 | $3.59 | $3.19 | per 1,000 people returned with enrichment |
| Engager we could not enrich | $0.95 | $0.85 | $0.76 | per 1,000, charged at the list price instead |

1,000 enriched engagers cost $3.99 on the Starter plan. Free Apify plan: up to 100 results per run.

### Input example

```json
{
  "postUrls": [
    "https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/"
  ],
  "maxResultsPerPost": 500,
  "icpTitles": [
    "Founder",
    "Head of Sales"
  ],
  "icpCountries": [
    "United States",
    "United Kingdom"
  ],
  "icpCompanySizes": [
    "11-50",
    "51-200"
  ]
}
```

### Output example

One row per result. Example (fictional person):

```json
{
  "engagementType": "comment",
  "profileType": "person",
  "name": "Jane Example",
  "headline": "Head of Sales at Example Co",
  "linkedinUrl": "https://www.linkedin.com/in/jane-example",
  "linkedinUrn": "ACoAAExample0001",
  "avatarUrl": "https://media.licdn.com/...",
  "reactionType": null,
  "commentText": "Great breakdown, we saw the same thing in Q3.",
  "commentPostedAt": "2026-10-20T09:14:02.000Z",
  "isReply": false,
  "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/",
  "jobTitle": "Head of Sales",
  "company": "Example Co",
  "companyDomain": "example.com",
  "companyUrl": "https://example.com",
  "companyLinkedinUrl": "https://www.linkedin.com/company/example-co",
  "companyIndustry": "Software Development",
  "companyEmployeeCount": 84,
  "companyStaffRange": "51-200",
  "companyLocation": "London, England, GB",
  "country": "United Kingdom",
  "location": "London, England, United Kingdom",
  "icpScore": 100,
  "icpReasons": [
    "Title: Head of Sales",
    "Country: United Kingdom"
  ],
  "isIcp": true
}
```

Fields: Everything in LinkedIn Post Engagers, plus jobTitle, company, companyDomain, companyUrl, companyLinkedinUrl, companyIndustry, companyEmployeeCount, companyStaffRange, companyLocation, country, location, icpScore, icpReasons, isIcp.

### FAQ

**How is the ICP score worked out?**
Job title is worth 40 points, country 30, industry 15 and company size 15. Only the filters you fill in count. A value we cannot find earns half its points. isIcp is true when the title matches and the score is 40 or more.

**How much data is filled in?**
In our tests: job title 96%, company 95%, industry 85%, company size 84%, country 100%.

**Do I need a LinkedIn account or cookies?**
No. You never log in and never share cookies, so there is no risk to your LinkedIn account.

**Am I charged for failed lookups?**
No. You pay only for results delivered to your dataset.

**Can I cap my spend?**
Yes. Set a maximum cost per run in Apify. The actor stops cleanly when it is reached.

**Can I use it from code, Make, Zapier, n8n or an AI agent?**
Yes. Run it through the Apify API, any Apify integration, or the Apify MCP server. The example input below works as is.

**Is this data public?**
It covers public LinkedIn posts and public profile information. You are responsible for using the data in line with the laws that apply to you, such as GDPR.

### Related actors

- [LinkedIn Post Engagers Scraper (No Cookies)](https://apify.com/cornersight/linkedin-post-engagers)
- [LinkedIn New Engagers Monitor](https://apify.com/cornersight/linkedin-new-engagers-monitor)
- [LinkedIn Influencer Finder (No Cookies)](https://apify.com/cornersight/linkedin-influencer-finder)

### For AI agents

- **When to use:** Find the buyers in the crowd that engaged with a competitor's or influencer's post.
- **Example input:** the JSON in "Input example" works as is.
- **Output:** one dataset row per result, fields as listed above.
- **Cost:** 1,000 enriched engagers cost $3.99 on the Starter plan.

Want this done for you every day, with a dashboard and push to HeyReach, PlusVibe or your own webhook? Try Cornersight: https://www.cornersight.io/?utm_source=apify\&utm_medium=marketplace\&utm_campaign=linkedin-post-engagers-enriched

# Actor input Schema

## `postUrls` (type: `array`):

One or more LinkedIn post URLs (or urn:li:activity ids).

## `engagementTypes` (type: `array`):

Which engagers to return.

## `includeReplies` (type: `boolean`):

Also return people who replied to comments. Slower on posts with many threads.

## `maxResultsPerPost` (type: `integer`):

Stop after this many engagers per post.

## `icpTitles` (type: `array`):

Optional. Example: Founder, Head of Sales.

## `icpCountries` (type: `array`):

Example: United Kingdom, United States.

## `icpIndustries` (type: `array`):

Example: Software Development, Business Consulting and Services.

## `icpCompanySizes` (type: `array`):

LinkedIn ranges, for example 11-50, 51-200.

## Actor input object example

```json
{
  "postUrls": [
    "https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/"
  ],
  "engagementTypes": [
    "reactions",
    "comments"
  ],
  "includeReplies": false,
  "maxResultsPerPost": 1000
}
```

# Actor output Schema

## `results` (type: `string`):

One row per result. Fields: Everything in LinkedIn Post Engagers, plus jobTitle, company, companyDomain, companyUrl, companyLinkedinUrl, companyIndustry, companyEmployeeCount, companyStaffRange, companyLocation, country, location, icpScore, icpReasons, isIcp.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "postUrls": [
        "https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("cornersight/linkedin-post-engagers-enriched").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "postUrls": ["https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/"] }

# Run the Actor and wait for it to finish
run = client.actor("cornersight/linkedin-post-engagers-enriched").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "postUrls": [
    "https://www.linkedin.com/feed/update/urn:li:activity:7497415374964027392/"
  ]
}' |
apify call cornersight/linkedin-post-engagers-enriched --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,cornersight/linkedin-post-engagers-enriched"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/bD5CiBHwpviK4jRWE/builds/Rlr504pM0cNexP7zG/openapi.json