# Glassdoor Reviews Scraper (`epicscrapers/glassdoor-reviews-scraper`) Actor Scrape Glassdoor employee reviews of any company by name, URL or id: title, pros, cons, advice, overall and 6 sub-ratings, CEO approval, job title, location and employer responses. Every review, 7 languages, filters by stars, job, place and keyword. - **URL**: https://apify.com/epicscrapers/glassdoor-reviews-scraper.md - **Developed by:** [Epic Scrapers](https://apify.com/epicscrapers) (community) - **Categories:** Jobs, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.20 / 1,000 review saveds 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 ### Glassdoor Reviews Scraper: employee reviews, ratings, pros and cons ![Every Glassdoor review as clean data: enter company names or URLs and get pros, cons, advice, the overall and 6 sub-ratings, and the reviewer's job and location, with every review, filters by stars, job and place, 7 languages and no login](https://api.apify.com/v2/key-value-stores/oL5CbUbbpmq6hJdZm/records/hero.png)

Pros, cons & advice · Overall + 6 sub-ratings · CEO approval · Job title & location · Employer responses
No Glassdoor account · Every review, not just the first pages · 7 languages · Filters by stars, job, place and keyword

Glassdoor Reviews Scraper turns a company's Glassdoor reviews into a clean dataset. Enter company names, Glassdoor URLs or employer ids and get every review with its title, pros, cons, advice to management, the overall rating and all six sub-ratings, recommend / CEO approval / business outlook, the reviewer's job title, location, employment status and tenure, helpful votes, and the employer's replies.
📚 Every review
No cap at a few hundred reviews: the Actor reads a company's reviews to the last page.
Chipotle: all 22,278 reviews in 52 seconds 		🎯 Glassdoor's own filters
Star rating, job title, location, a keyword in the text, employment status, current employees, date posted, and 7 review languages.
e.g. 1★ reviews mentioning "layoffs" in Seattle 		🧾 ~40 fields per review
Full text, 7 ratings, 3 sentiment answers, job title and location with Glassdoor ids, tenure, employer responses, review and company links.
No duplicates, each review charged once
- **Several companies in one run.** A list of names, URLs or ids; each one gets its own limit. - **Paste the URL you already have.** Company reviews pages from any Glassdoor domain; a reviews page filtered to a job title or location keeps that filter. Single review links save just that review. - **Monitor new reviews.** Schedule the Actor with "Reviews posted since: 7 days" to collect each week's new reviews. - **Fast and light.** Glassdoor's mobile API, no browser, no login. ### Who it's for | You are… | Use it to… | | --------------------------- | -------------------------------------------------------------------------------------- | | HR and employer-brand teams | Track what employees say about you and competitors, by location, role and rating | | Investors and analysts | Follow employee sentiment, CEO approval and business outlook over time as a signal | | Recruiters and job seekers | Compare culture, pay and management across companies before an outreach or an offer | | Researchers and data teams | Build datasets of workplace reviews for NLP, sentiment or labor-market studies | | Consultants and sales teams | Find companies with morale problems (low ratings, "layoffs", "management") to approach | ### Quick start 1. Enter one or more companies, e.g. `Microsoft`, or `https://www.glassdoor.com/Reviews/Microsoft-Reviews-E1651.htm`. 2. Set **Max reviews per company** (0 = all) and **Sort by**. 3. Optionally add filters: star rating, job title, location, keyword, language, date. 4. Click **Start**, then download the reviews as JSON, CSV or Excel, or read them through the API. ```json { "companies": ["Microsoft", "https://www.glassdoor.com/Reviews/Google-Reviews-E9079.htm"], "maxReviews": 500, "sortBy": "newest", "rating": "1", "keyword": "layoffs" } ``` ### Real output One review from a run (Chipotle, newest first): ```json { "reviewId": "105446676", "reviewUrl": "https://www.glassdoor.com/Reviews/Employee-Review-Chipotle-RVW105446676.htm", "reviewDate": "2026-09-03", "reviewDateTime": "2026-09-03T09:22:25.530", "title": "Good benefits overshadowed by poor pay and conditions", "pros": "Tuition Reimbursement and Free food", "cons": "Poor structure, low pay, bad working conditions", "adviceToManagement": "Get it together", "ratingOverall": 1, "ratingWorkLifeBalance": 1, "ratingCultureAndValues": 1, "ratingDiversityAndInclusion": 3, "ratingCareerOpportunities": 3, "ratingCompensationAndBenefits": 1, "ratingSeniorManagement": 2, "recommendToFriend": "NEGATIVE", "ceoApproval": "DISAPPROVE", "businessOutlook": "NEGATIVE", "jobTitle": "Kitchen Manager", "jobTitleId": 25283, "location": "Stillwater, OK", "locationId": 1136989, "locationType": "CITY", "isCurrentEmployee": false, "employmentStatus": "REGULAR", "yearsAtCompany": 4, "jobEndingYear": 2026, "helpfulCount": 0, "notHelpfulCount": 0, "isFeatured": false, "language": "English", "hasEmployerResponse": true, "employerResponses": [ { "date": "2026-10-07", "response": "We appreciate the review and are glad you were able to take advantage of our tuition reimbursement benefits. We take your outlined concerns seriously and will use these to continue to improve the employee experience.", "responderJobTitle": "Social Listening Analyst" } ], "companyId": 15228, "companyName": "Chipotle", "companyLogoUrl": "https://media.glassdoor.com/sql/15228/chipotle-squareLogo-1674754456717.png", "companyReviewsUrl": "https://www.glassdoor.com/Reviews/Chipotle-Reviews-E15228.htm", "scrapedAt": "2026-10-21T22:19:38.318Z" } ``` ### Input #### Companies Each line is a company name (`Microsoft`), a Glassdoor URL from any domain (`https://www.glassdoor.de/Bewertungen/...-E1651.htm`), or a Glassdoor employer id (`1651`). A name is matched with Glassdoor's company search; paste the URL when a name is ambiguous. A single review link (`...-RVW106027521.htm`) saves only that review. #### Limit, order and date - **Max reviews per company**: the most to save per company; 0 = all. - **Sort by**: newest, oldest, most relevant (Glassdoor's default order), highest or lowest rated. With a limit, this decides which reviews you get. - **Reviews posted since**: a date (`2026-01-01`) or a relative period (`30 days`). Fastest with newest first: the Actor stops at the first older review. #### Language Glassdoor keeps reviews in each language apart: English (what glassdoor.com shows), German, French, Spanish, Portuguese, Italian and Dutch. English is the default. Pick All languages for companies with many European or Latin American employees: with a limit, you then get the newest (or best, or worst) reviews across all languages. #### Filters | Filter | What it does | | ---------------------- | --------------------------------------------------------------------------- | | Star rating | Only reviews with this overall rating (1–5) | | Job title | Only reviewers in this job; Glassdoor also matches similar titles | | Location | A city, metro area, state or country, e.g. `Seattle`, `California`, `India` | | Reviews mentioning | Only reviews containing this word | | Employment status | Full-time, part-time, contract, intern, freelance | | Current employees only | Leave out former employees | Filters apply to every company in the run. ### Output fields | Field | Description | | -------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | `reviewId`, `reviewUrl` | Glassdoor review id and link | | `reviewDate`, `reviewDateTime` | When the review was posted | | `title`, `pros`, `cons`, `adviceToManagement` | The review text | | `ratingOverall` | 1–5 stars | | `ratingWorkLifeBalance` … `ratingSeniorManagement` | The 6 sub-ratings, 1–5, null when the reviewer skipped one | | `recommendToFriend`, `ceoApproval`, `businessOutlook` | POSITIVE / NEGATIVE, APPROVE / DISAPPROVE / NO_OPINION, POSITIVE / NEUTRAL / NEGATIVE | | `jobTitle`, `jobTitleId` | Reviewer's job | | `location`, `locationId`, `locationType` | Reviewer's work location | | `isCurrentEmployee`, `employmentStatus`, `yearsAtCompany`, `jobEndingYear` | Employment details | | `helpfulCount`, `notHelpfulCount`, `isFeatured`, `language` | Votes, featured flag, review language | | `hasEmployerResponse`, `employerResponses` | The company's replies with date and responder job title | | `companyId`, `companyName`, `companyLogoUrl`, `companyReviewsUrl` | The company | The **Ratings** view in the dataset shows all ratings side by side; the run's `SUMMARY` record lists per company how many reviews were saved and how many Glassdoor has. ### Pricing You pay per review saved, with everything included: all fields, employer responses, filters and languages. Duplicates are never charged. | Plan | Free | Bronze | Silver | Gold | | ----------------- | ----- | ------ | ------ | ----- | | Per 1,000 reviews | $4.50 | $4.00 | $3.60 | $3.20 | Platform usage is included. Set a spending limit on the run and the Actor stops cleanly when it is reached. ### Tips and limits - **Names vs URLs.** Company names go through Glassdoor's company search, which picks the best match. For subsidiaries or common names, paste the company's Glassdoor URL. - **Glassdoor's counts.** The total Glassdoor reports can differ by one or two from what is served, as reviews are added or removed during a run. - **Review times** are Glassdoor's stored times, without a time zone. ### Monitor reviews with scheduled runs Create a task with your companies, **Sort by: Newest first** and **Reviews posted since: 7 days**, and schedule it weekly. Each run returns only the past week's reviews; connect a webhook, Slack, Google Sheets or Zapier integration to get them delivered. ### Use the API ```bash curl -X POST "https://api.apify.com/v2/acts/epicscrapers~glassdoor-reviews-scraper/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"companies": ["Microsoft"], "maxReviews": 200, "sortBy": "newest"}' ``` ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("epicscrapers/glassdoor-reviews-scraper").call( run_input={"companies": ["Microsoft"], "maxReviews": 200, "rating": "1"} ) for review in client.dataset(run["defaultDatasetId"]).iterate_items(): print(review["reviewDate"], review["ratingOverall"], review["title"]) ``` ### For AI agents Call the Actor with `companies` (names, Glassdoor URLs or employer ids) and optionally `maxReviews`, `sortBy` (`newest`, `oldest`, `mostRelevant`, `highestRated`, `lowestRated`), `reviewsSince` (`YYYY-MM-DD` or `30 days`), `language` (`eng`, `deu`, `fra`, `spa`, `por`, `ita`, `nld` or `all`), `rating` (`"1"`–`"5"`), `jobTitle`, `location`, `keyword`, `employmentStatus` (`REGULAR`, `PART_TIME`, `CONTRACT`, `INTERN`, `FREELANCE`) and `onlyCurrentEmployees`. Each dataset item is one review; ids are stable across runs. ### FAQ **Do I need a Glassdoor account?** No. The Actor uses no login and no cookies. **Can I get all reviews of a big company?** Yes. Set Max reviews per company to 0. Microsoft has over 66,000 English reviews; the Actor reads 100 per request. **Why do I get fewer reviews than I expected?** Glassdoor keeps each language apart, and English is the default. Pick All languages under Language, and check that no filter is set. **Does it get interviews, salaries or jobs?** No, reviews only. See our Glassdoor Jobs Scraper and Glassdoor Salaries Scraper. **Is scraping Glassdoor legal?** The Actor collects publicly visible reviews and no personal account data. Reviews are anonymous; check the laws that apply to your use, especially for personal data in review text. # Actor input Schema ## `companies` (type: `array`): Enter one company per line: a name ("Microsoft"), a Glassdoor company URL from any Glassdoor domain ("https://www.glassdoor.com/Reviews/Microsoft-Reviews-E1651.htm") or a Glassdoor employer id ("1651"). Paste the URL when a name is ambiguous.

A reviews URL filtered to a job title or location keeps that filter. A single review link ("…/Employee-Review-Microsoft-RVW106027521.htm") saves just that review. ## `maxReviews` (type: `integer`): Set the most reviews to save for each company. 0 = all of them (Microsoft has over 66,000 English reviews). ## `sortBy` (type: `string`): Choose which reviews come first. With a limit, this decides which reviews you get. ## `reviewsSince` (type: `string`): Get only reviews posted on or after this date, e.g. 2026-01-01 or the last 30 days. Good for scheduled runs that collect new reviews. ## `language` (type: `string`): Choose the review language. Glassdoor keeps each language apart: English is what glassdoor.com shows. Pick "All languages" for companies with many reviews in Europe or Latin America (Microsoft has ~66,000 English, ~1,000 Portuguese and ~900 French reviews). ## `rating` (type: `string`): Get only reviews with this overall rating, e.g. 1 star for complaints. ## `jobTitle` (type: `string`): Get only reviews from people in this job, e.g. "Software Engineer". Glassdoor matches similar titles too ("Senior Software Engineer"). ## `location` (type: `string`): Get only reviews from this place: a city, metro area, state or country, e.g. "Seattle", "California", "India". Add the country when a name is ambiguous ("London, Ontario"). ## `keyword` (type: `string`): Get only reviews that mention this word or phrase, e.g. "layoffs", "remote", "bonus". ## `employmentStatus` (type: `string`): Get only reviews from this kind of employee. ## `onlyCurrentEmployees` (type: `boolean`): Get only reviews from people still working at the company. ## `proxyConfiguration` (type: `object`): Keep the default. Glassdoor limits requests per IP address, so the Actor spreads its requests over several proxy IPs and changes IP when one is limited. Datacenter proxy is enough. ## Actor input object example ```json { "companies": [ "Microsoft" ], "maxReviews": 100, "sortBy": "newest", "language": "eng", "rating": "", "employmentStatus": "", "onlyCurrentEmployees": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "companies": [ "Microsoft" ], "maxReviews": 100, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("epicscrapers/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "companies": ["Microsoft"], "maxReviews": 100, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("epicscrapers/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": [ "Microsoft" ], "maxReviews": 100, "proxyConfiguration": { "useApifyProxy": true } }' | apify call epicscrapers/glassdoor-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,epicscrapers/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 ` 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/EGx0Hkgv4jaHdD9BC/builds/LSXKUGNHKfOZAENJp/openapi.json