# Glassdoor Reviews Scraper (No Login) - $0.70 / 1000 Reviews (`scrapeunblocker/glassdoor-reviews-scraper`) Actor

Scrape Glassdoor employee reviews without a login: rating, 6 sub-ratings, pros, cons, advice, job title, location, recommend / CEO / outlook, employer reply, plus the company's rating summary. Public view only: up to 25 reviews per company per filter set. $0.70 per 1000 reviews.

- **URL**: https://apify.com/scrapeunblocker/glassdoor-reviews-scraper.md
- **Developed by:** [Scrapeunblocker](https://apify.com/scrapeunblocker) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 1,000 reviews

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 Reviews Scraper (No Login)

Scrape **Glassdoor employee reviews** as clean structured JSON without a Glassdoor account - overall rating, the six sub-ratings (work/life balance, culture and values, diversity and inclusion, career opportunities, compensation and benefits, senior management), recommend to a friend, CEO approval, business outlook, review title, pros, cons, advice to management, job title, employment status, current or former employee, years at the company, location, date, helpful votes and the employer's reply. Each company also gets a rating summary: overall and sub-rating averages, review counts, recommend / CEO approval / outlook percentages, the CEO, the star distribution of every rating and reviews in the last 7 and 30 days.

### What you get - read this first

Glassdoor shows visitors who are **not logged in** only the first page (3 reviews) of each sort order and filter; every deeper page asks for a sign-in. This Actor reads the public pages only: for each company and filter set it walks the other sort orders and each star rating and merges the distinct reviews, which gives **up to 25 reviews per company per filter set** (usually 15-25 for large employers). It does **not** return a company's full review history.

To reach more reviews of the same company, add **job titles**: each job title is its own filter set with up to 25 more reviews. Changing the order, star rating, keyword, topic, employment status or language also reaches different reviews.

Good for: a fresh snapshot of what employees say, the company rating summary at scale (thousands of companies), employer-brand monitoring, and role-specific sentiment. Not for: downloading all reviews of one company.

### Features

- **Any company input** - a Glassdoor company URL, the employer id (`9079`) or a company name (matched with Glassdoor's company search).
- **Filters** - order (most recent, most helpful, highest, lowest rated), star rating, job titles, keyword, topic (compensation, culture, career development, management, work/life balance, diversity and inclusion), employment status, review language, current employees only.
- **Full review data** - every rating and sub-rating, pros, cons, advice, job title, employment status, tenure, location, date, helpful / not helpful votes, featured flag and the employer's reply with its date.
- **Company summary** - the `COMPANIES` record per company: name, logo, website, industry, sector, headquarters, size, overall and sub-rating averages, rating distributions, recommend / CEO approval / business outlook percentages, the CEO, review counts and reviews in the last 7 and 30 days.
- **Deduplicated** - the same company given twice (URL and id) is collected once; reviews found under several job titles are returned once.

### Use cases

- **Employer branding and HR analytics** - track what current and former employees say, by role and location.
- **Competitive intelligence** - compare ratings, CEO approval and business outlook across companies in a sector.
- **Investment research** - employee sentiment and outlook as a signal, at scale.
- **Recruiting** - see what engineers or analysts say about a company before you pitch it.

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `companies` | array | Google | Glassdoor company URLs, employer ids or company names. |
| `maxReviewsPerCompany` | integer | `25` | Up to 25 per company and filter set. |
| `sort` | string | `recent` | `recent`, `helpful`, `highest`, `lowest`. |
| `rating` | string | - | Only this star rating (`"1"`-`"5"`). |
| `jobTitles` | array | - | Each job title is its own filter set (up to 25 more reviews). |
| `keyword` | string | - | Only reviews mentioning this keyword. |
| `topic` | string | - | `compensation`, `culture`, `career_development`, `management`, `work_life_balance`, `diversity_and_inclusion`. |
| `employmentStatus` | array | full-time + part-time | `full_time`, `part_time`, `contract`, `intern`, `freelance`. |
| `languages` | array | English | `eng`, `fra`, `deu`, `nld`, `por`, `spa`, `ita`. |
| `currentEmployeesOnly` | boolean | `false` | Only current employees. |

#### Example input

```json
{
  "companies": [
    "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm",
    "Bank of America"
  ],
  "jobTitles": ["software engineer", "analyst"],
  "sort": "recent",
  "maxReviewsPerCompany": 25
}
```

### Output

One dataset item per review:

```json
{
  "companyName": "Google",
  "employerId": 9079,
  "companySlug": "Google",
  "id": 105832357,
  "url": "https://www.glassdoor.com/Reviews/Employee-Review-Google-E9079-RVW105832357.htm",
  "title": "Great wellness perks overshadowed by office politics",
  "rating": 5,
  "workLifeBalance": 5,
  "cultureAndValues": 5,
  "diversityAndInclusion": 5,
  "careerOpportunities": 5,
  "compensationAndBenefits": 5,
  "seniorManagement": 5,
  "recommendToFriend": true,
  "ceoApproval": "approve",
  "businessOutlook": "positive",
  "pros": "Excellent wellness perks and health benefits. ...",
  "cons": "Office politics happened at the more senior level. ...",
  "advice": null,
  "jobTitle": "Technical Program Manager",
  "employmentStatus": "full_time",
  "isCurrentEmployee": false,
  "yearsOfEmployment": 6,
  "location": "San Francisco, CA",
  "date": "2026-10-02T22:14:11.313",
  "helpfulCount": 0,
  "notHelpfulCount": 0,
  "featured": false,
  "employerResponseText": null,
  "employerResponseDate": null,
  "employerResponderTitle": null,
  "view": "recent",
  "jobTitleFilter": null,
  "companyInput": "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
}
```

`view` tells which public page the review came from (e.g. `recent`, `helpful`, `recent_rating_1`); `jobTitleFilter` is the job title filter set it was found under.

The key-value store also holds:

- `COMPANIES` - per company: company meta, the rating summary and, per filter set, how many reviews match on Glassdoor, how many were collected and which public pages were read.
- `ERRORS` - companies that returned no reviews (unknown company, no match for the filters, blocked) with the reason. These are **not billed**.

### Pricing

**$0.70 per 1000 reviews.** You pay only for reviews delivered; failed companies are not charged.

### Notes

- Public pages only, no login: up to 25 reviews per company per filter set (see above). `publicLimitReached` in the `COMPANIES` record shows when more reviews match than the public pages hold.
- A company name goes through Glassdoor's company search; for companies with common names a URL or employer id is the safest input.
- Dates are Glassdoor's review timestamps (ISO, no time zone).

# Actor input Schema

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

Companies to collect reviews for: a Glassdoor company URL (https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm), a Glassdoor employer id (9079) or a company name (Bank of America - matched with Glassdoor's company search). A URL or id is the most reliable.

## `maxReviewsPerCompany` (type: `integer`):

Up to 25. Glassdoor shows visitors who are not logged in only the first 3 reviews of each order and filter; to reach more, the scraper reads the other orders and each star rating and merges the distinct reviews - usually 15-25 per company. Add job titles below to reach further reviews.

## `sort` (type: `string`):

Which reviews are read first.

## `rating` (type: `string`):

Optional. Only reviews with this overall rating.

## `jobTitles` (type: `array`):

Optional. Only reviews from these job titles, e.g. 'software engineer' (Glassdoor's job-title search). Each job title is its own filter set with up to 25 reviews, so several job titles also reach more of a company's reviews.

## `keyword` (type: `string`):

Optional. Only reviews mentioning this keyword, e.g. 'remote' or 'layoffs'.

## `topic` (type: `string`):

Optional. Only reviews about one topic.

## `employmentStatus` (type: `array`):

Optional. Empty = Glassdoor's own default (full-time and part-time).

## `languages` (type: `array`):

Optional. Empty = English.

## `currentEmployeesOnly` (type: `boolean`):

Only reviews written by current employees.

## Actor input object example

```json
{
  "companies": [
    "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"
  ],
  "maxReviewsPerCompany": 25,
  "sort": "recent",
  "currentEmployeesOnly": false
}
```

# Actor output Schema

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

One item per review, with the company name and employer id

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

Per company: overall and sub-rating averages, review counts, recommend / CEO approval / business outlook shares, the CEO, star distribution, company meta and the reviews collected per filter set

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

Companies that returned no reviews (unknown company, no match for the filters, 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/Reviews/Google-Reviews-E9079.htm"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapeunblocker/glassdoor-reviews-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/Reviews/Google-Reviews-E9079.htm"] }

# Run the Actor and wait for it to finish
run = client.actor("scrapeunblocker/glassdoor-reviews-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/Reviews/Google-Reviews-E9079.htm"
  ]
}' |
apify call scrapeunblocker/glassdoor-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapeunblocker/glassdoor-reviews-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/XVJhvoP4Ant7G5MH1/builds/ZJvoFy5Pe3fq8SZg9/openapi.json