# LinkedIn Buying Signal Finder (`thenetaji/linkedin-buying-signal-finder`) Actor

Find companies whose open roles show they are investing in what you sell, and who to contact at each. A company hiring three Kubernetes engineers has a budget and a problem; the row carries how many roles, how long the oldest has sat, and the leader's work email.

- **URL**: https://apify.com/thenetaji/linkedin-buying-signal-finder.md
- **Developed by:** [The Netaji](https://apify.com/thenetaji) (community)
- **Categories:** Lead generation, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 company with a contacts

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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## LinkedIn Buying Signal Finder

A company hiring three Kubernetes engineers has a budget, a deadline, and a problem it has not solved. That is a better lead than any firmographic filter, and it is public. The Actor searches current openings for a skill, tool, or role that signals someone is investing in your category, groups the results by employer, and returns the leader of the function doing the hiring with their work email.

### Accepted input

| Field | Type | Default | Description |
|---|---|---|---|
| `keywords` | string | — | Required. The skill, tool, or role that means a company is buying, e.g. `kubernetes` or `demand generation`. |
| `location` | string | — | Optional place name to restrict the search to. |
| `min_open_roles` | integer | `1` | Only return companies with at least this many matching openings. `2` filters out a company that posted once and moved on. |
| `verify_emails` | boolean | `false` | Confirm each address against the company's mail server. |
| `date_posted` | select | last 30 days | How recent the openings must be. |
| `maxItems` | integer | `50` | Maximum companies to save. `0` removes the limit. |

```json
{
  "keywords": "kubernetes",
  "location": "United States",
  "min_open_roles": 2,
  "verify_emails": true
}
```

### What comes back

One row per company, not per posting — three openings at one employer is a stronger signal than one, and it is still a single person to contact.

Each row carries the company, how many of its current openings match, how long its longest-unfilled matching role has sat, one opening as evidence with a link, and the contact: name, headline, seniority, LinkedIn profile, and best-match work email with a confidence score.

Rows are ordered by how many matching roles a company has, then by how long the oldest has been open. Both say the same thing about how badly the company needs what you sell.

### How the contact is chosen

The Actor matches the signal to the function doing the hiring, then returns the most senior person it can confirm in that function at that company.

`contact_basis` says this on every row, because it is an inference. Nobody publishes who holds which budget, so the honest claim is "the most senior engineering leader we could confirm here", not "this person will sign your invoice". Everyone returned is confirmed to hold a current role at the company — ex-employees and people who merely mention it are excluded.

### What it cannot do

A company that is buying quietly, without hiring, is invisible to this. So is one whose postings do not name the tool. This finds the companies that announced themselves.

Coverage of the contact side depends on what search engines have indexed, so smaller companies return fewer leaders. A company where no leader can be confirmed is not returned at all and is not charged for — a lead nobody can act on is not a lead.

Some company domains accept mail addressed to anything, so no service can confirm a mailbox there. That is detected before anything is spent, reported on the row, and never charged for.

### Pricing

Charged per company returned with a contact. A search that matches no companies, or companies where nobody can be confirmed, costs nothing. The verified add-on is charged only when a mailbox is actually confirmed.

# Actor input Schema

## `keywords` (type: `string`):

A skill, tool, or role that means a company is investing in your category, e.g. 'kubernetes' or 'demand generation'. Companies hiring for it are the leads.

## `location` (type: `string`):

A place name to search jobs in. Resolved to a LinkedIn geo ID automatically; ignored when geo\_id is set.

## `min_open_roles` (type: `integer`):

Only return companies with at least this many matching openings. Three roles is a stronger signal than one, and filters out a company that posted once and moved on.

## `verify_emails` (type: `boolean`):

Confirm each address against the company's mail server before returning it. Around 40% of company domains accept every address (catch-all), where no mailbox can be confirmed by anyone — those are reported as unverifiable rather than guessed at, and are never charged for.

## `date_posted` (type: `string`):

Only return jobs posted within this window.

## `maxItems` (type: `integer`):

Maximum companies to save. Set 0 for no limit.

## Actor input object example

```json
{
  "keywords": "Data Scientist",
  "location": "London",
  "min_open_roles": 2,
  "verify_emails": false,
  "maxItems": 20
}
```

# Actor output Schema

## `dataset` (type: `string`):

All records scraped by this run

# 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 = {
    "keywords": "Data Scientist",
    "location": "London",
    "min_open_roles": 2,
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("thenetaji/linkedin-buying-signal-finder").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 = {
    "keywords": "Data Scientist",
    "location": "London",
    "min_open_roles": 2,
    "maxItems": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("thenetaji/linkedin-buying-signal-finder").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 '{
  "keywords": "Data Scientist",
  "location": "London",
  "min_open_roles": 2,
  "maxItems": 20
}' |
apify call thenetaji/linkedin-buying-signal-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thenetaji/linkedin-buying-signal-finder"
        }
    }
}

```

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/I4QILOXfSQ4JKWiBO/builds/lNd5lwTGfzfhkpkTJ/openapi.json