# LinkedIn Engagement Leads — Turn Reactions into Warm Leads (`noniner/linkedin-engagement-leads`) Actor

Point it at any LinkedIn post reactions/comments scraper's dataset and get a ranked list of warm leads — who engaged, their role, an AI intent read and a suggested opener. The people who liked/commented are your warmest prospects.

- **URL**: https://apify.com/noniner/linkedin-engagement-leads.md
- **Developed by:** [Fredrik Hansson](https://apify.com/noniner) (community)
- **Categories:** AI, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$50.00 / 1,000 lead scoreds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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 Engagement Leads — Turn Reactions into Warm Leads

The people who liked and commented on a relevant LinkedIn post are your **warmest prospects**. Point this at any LinkedIn post reactions/comments scraper's dataset and get them back as **ranked, ready-to-contact leads**.

### What you get

Per engager: name, headline, profile URL, engagement type, a **lead score**, an **AI intent read**, and a **suggested opener** — commenters ranked above likers.

### How to use

1. Run any LinkedIn post reactions/comments scraper on Apify for a relevant post (yours or a competitor's).
2. Copy its **dataset ID**.
3. Run this actor with that `datasetId` and your `offering`.

```json
{ "datasetId": "YOUR_ENGAGEMENT_DATASET_ID", "offering": "We help B2B teams book more meetings", "maxLeads": 50 }
```

### Pricing

Pay per lead scored.

### Note

Uses only the public engagement data you provide. You are the data controller — use business contact data responsibly (GDPR/local rules). Not legal advice.

Actively maintained.

***

**Part of the [No Niner](https://noniner.io) toolkit** — no-code web scraping, enrichment & AI data tools, all pay-per-use. Browse the full set at **[noniner.io](https://noniner.io)**.

# Actor input Schema

## `datasetId` (type: `string`):

The dataset ID from any LinkedIn post reactions or comments scraper's run. The actor auto-detects name, headline and comment fields.

## `offering` (type: `string`):

Your product or the kind of person you want to reach. Drives the lead score, intent read and opener.

## `maxLeads` (type: `integer`):

Cap on how many engagers to score (comments rank above likes).

## `model` (type: `string`):

gpt-4o-mini is the cost-effective default.

## Actor input object example

```json
{
  "offering": "We help B2B teams book more meetings with AI-personalized outreach.",
  "maxLeads": 50,
  "model": "gpt-4o-mini"
}
```

# Actor output Schema

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

All rows in the default dataset.

# 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 = {
    "offering": "We help B2B teams book more meetings with AI-personalized outreach."
};

// Run the Actor and wait for it to finish
const run = await client.actor("noniner/linkedin-engagement-leads").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 = { "offering": "We help B2B teams book more meetings with AI-personalized outreach." }

# Run the Actor and wait for it to finish
run = client.actor("noniner/linkedin-engagement-leads").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 '{
  "offering": "We help B2B teams book more meetings with AI-personalized outreach."
}' |
apify call noniner/linkedin-engagement-leads --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,noniner/linkedin-engagement-leads"
        }
    }
}
```

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/P9gd5fyu6btI7Sn7N/builds/0CXITGcMflnQol4fr/openapi.json