# Glassdoor Salary Scraper - $1 / 1000 Salaries (`scrapeunblocker/glassdoor-salaries-scraper`) Actor

Glassdoor company salaries without login: base and total pay percentiles (P10-P90) per job title, currency, report count and date, plus company rating, industry and size. By company name, employer id or URL, with a job-title filter. $1 per 1000 salary rows.

- **URL**: https://apify.com/scrapeunblocker/glassdoor-salaries-scraper.md
- **Developed by:** [Scrapeunblocker](https://apify.com/scrapeunblocker) (community)
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 salary rows

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

## Glassdoor Salary Scraper

Scrape **Glassdoor company salaries** in bulk as clean JSON - base-pay and total-pay percentiles (P10, P25, median, P75, P90) for every job title, the currency, how many salaries Glassdoor has for the title and the latest report date, together with the company's rating, industry, size and headquarters. **No Glassdoor account, no cookies, no login**, no proxies or browsers to configure.

Give companies by name, Glassdoor employer id or any Glassdoor company URL, and optionally narrow to a job title.

### Features

- **Pay percentiles as numbers** - `basePay` and `totalPay` (base plus bonus, stock and other pay) with `P10`, `P25`, `P50`, `P75`, `P90`, plus flat `basePayMedian` / `totalPayMedian` for easy sorting.
- **Every job title** - most-reported titles first, up to 100 per company, or only the titles matching a **job-title filter** (Glassdoor's own job-title search, e.g. `software engineer`).
- **Company context on every row** - company name, employer id, rating, industry, size, headquarters and the market the pay is for (e.g. United States).
- **Flexible company input** - a Glassdoor salary / overview / reviews / jobs URL, a numeric employer id (`9079` is Google) or a plain company name (matched with Glassdoor's company search).
- **Company summary** - the `COMPANIES` record lists each company's details and how many job titles have salary data.

### Use cases

- **Compensation benchmarking** - median and P10-P90 base and total pay for any role at a company.
- **Offer and levelling analysis** - compare a company's pay bands across job titles.
- **Market pay research** - pull the same role across a list of employers and chart it side by side.
- **Recruiting and sales intelligence** - back up a pitch with a company's own Glassdoor pay data.

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `companies` | array | `["https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm"]` | Glassdoor company URLs, employer ids or company names. |
| `job_title` | string | - | Only job titles matching this text, e.g. `software engineer`. |
| `max_results_per_company` | integer | `20` | Salary rows per company (1-100), most-reported titles first. |
| `proxy_country` | string | `""` | Optional exit country (ISO-2). Empty = US exit, pay for the US market in USD. |
| `concurrency` | integer | `2` | Companies fetched at the same time (1-3). |

#### Example input

```json
{
  "companies": [
    "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm",
    "1651",
    "Bank of America"
  ],
  "job_title": "software engineer",
  "max_results_per_company": 30
}
```

### Output

One dataset item per job title per company:

```json
{
  "company": "Google",
  "employerId": 9079,
  "location": "United States",
  "companyRating": 4.4,
  "companyIndustry": "Internet & Web Services",
  "companySize": "10000+ Employees",
  "companyHeadquarters": "Mountain View, CA",
  "jobTitleFilter": null,
  "salariesUrl": "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm",
  "input": "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm",
  "jobTitle": "Software Engineer",
  "jobTitleId": 4279,
  "basePay": { "P10": 134264.84, "P25": 156158.89, "P50": 184722.83, "P75": 218511.57, "P90": 254143.41 },
  "totalPay": { "P10": 207909.08, "P25": 251388.51, "P50": 311695.65, "P75": 396273.52, "P90": 486503.67 },
  "currency": "USD",
  "salaryCount": 51173,
  "mostRecent": "2026-09-25T22:31:54.373",
  "basePayMedian": 184722.83,
  "totalPayMedian": 311695.65
}
```

Every item has the same keys; a value Glassdoor does not show is `null`.

Companies that return no salary rows (unknown company, no job title matching the filter, blocked after retries) are listed in the `ERRORS` record of the key-value store and are **not billed**.

### Pricing

**$1 per 1000 salary rows** (one row = one job title at one company, with all its percentiles). Company details and the `COMPANIES` summary are included at no extra charge. Failed companies are not charged.

### Notes

- Glassdoor shows at most 10 job titles per page; the Actor pages through them for you, up to 100 per company and job-title filter. For more titles of a large employer, run it again with different job-title filters.
- A Glassdoor URL or employer id is matched exactly; a company name uses Glassdoor's company search and takes its best company match.

# Actor input Schema

## `companies` (type: `array`):

Companies to get salaries for: a Glassdoor company URL (salary, overview, reviews or jobs page, e.g. https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm), a Glassdoor employer id (e.g. 9079) or a company name (e.g. Bank of America, matched with Glassdoor's company search). A URL or id is the most precise.

## `job_title` (type: `string`):

Only job titles matching this text, using Glassdoor's own job-title search, e.g. software engineer. Leave empty for all job titles, most-reported first.

## `max_results_per_company` (type: `integer`):

How many job-title salary rows to collect per company (1-100), most-reported job titles first. Glassdoor shows 10 per page.

## `proxy_country` (type: `string`):

ISO-2 country to browse Glassdoor from. Leave empty for a US exit, so pay is reported for the US market in USD.

## `concurrency` (type: `integer`):

How many companies to fetch at the same time (1-3).

## Actor input object example

```json
{
  "companies": [
    "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm"
  ],
  "max_results_per_company": 20,
  "proxy_country": "",
  "concurrency": 2
}
```

# Actor output Schema

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

One item per job title per company: base-pay and total-pay percentiles, currency, report count

## `companies` (type: `string`):

Company details and totals per company (rating, industry, size, number of job titles with salaries)

## `errors` (type: `string`):

Companies that returned no salary rows (unknown company, no match for the job title, or blocked), with the reason (not billed)

# 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 = {
    "companies": [
        "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapeunblocker/glassdoor-salaries-scraper").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 = { "companies": ["https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm"] }

# Run the Actor and wait for it to finish
run = client.actor("scrapeunblocker/glassdoor-salaries-scraper").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 '{
  "companies": [
    "https://www.glassdoor.com/Salary/Google-Salaries-E9079.htm"
  ]
}' |
apify call scrapeunblocker/glassdoor-salaries-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapeunblocker/glassdoor-salaries-scraper"
        }
    }
}
```

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/GBv8trr399NwaSXON/builds/LDVT389FFe4UL04OX/openapi.json