Glassdoor

Glassdoor Reviews API

Up to THREE full employee reviews with per-axis scores, pros, cons, advice, job title, location, employment status and any employer response — plus the complete rating statistics, star distribution, aggregate pro/con highlight terms and per-job-title review counts for the whole population. Three is Glassdoor's own anonymous cap, so there is deliberately no page param: the aggregates are the full-population signal here, not the bodies. Costs 1 credit.

POST/api/v1/glassdoor/reviews

Authorizations

Authorizationstringheaderrequired

Bearer authentication header of the form Bearer <token>, where <token> is your Scavio API key (e.g. Bearer sk_live_your_key).

Body

application/json

employer_idstring

Glassdoor employer id, 1-50 characters, as a STRING (1699, E1699 or IE1699) — a JSON number is rejected. Get one from the Glassdoor Company Search endpoint. Either this or url is required. Addressing by id costs two upstream fetches because the case-sensitive /Reviews/ slug has to be read off the profile first; your price is unchanged, but url is the faster path.

Example: 1699

urlstring

Any glassdoor.com employer URL, 1-500 characters. Pass back the reviews_url that the Company Profile endpoint returned to skip the resolve fetch. A non-glassdoor.com host is rejected. Either this or employer_id is required.

Example: https://www.glassdoor.com/Reviews/NIKE-Reviews-E1699.htm

categoryenum<string>

Restrict to reviews Glassdoor files under one topic. This is one of the two levers that move the three-review window. CLOSED SET: Glassdoor ignores a value it does not recognise and serves the UNFILTERED set under a 200, so a typo silently buys the wrong data. Read filtered_review_count on the response to see how many reviews match.

Example: work_life_balance

career_development — Growth, promotion and progression.
compensation — Pay and benefits.
culture — Culture and values.
diversity_and_inclusion — Diversity and inclusion.
management — Senior management and leadership.
work_life_balance — Hours, flexibility and balance.

employment_statusenum<string>

Restrict to reviewers of one employment type — the other lever on the window. Closed for the same reason as category. FREELANCE is deliberately absent: it was never confirmed to change the result set, and offering it would sell a filter that may not run.

Example: full_time

full_time — Full-time employees.
part_time — Part-time employees.
contract — Contractors.
intern — Interns.

companystring

Employer name as it appears in a Glassdoor slug, 1-200 characters. COSMETIC ONLY: ignored entirely when url is set, and it does NOT satisfy the employer_id-or-url requirement.

Example: NIKE

Request

from scavio import ScavioClient

client = ScavioClient(api_key="sk_live_your_key", timeout=180)

# Fastest path: chain on reviews_url from the profile (one upstream fetch)
profile = client.glassdoor.company(employer_id="1699")
reviews = client.glassdoor.reviews(
    url=profile["data"]["reviews_url"],
    category="work_life_balance",
    employment_status="full_time",
)

# Three bodies max - the aggregates describe the whole population
print(reviews["data"]["filtered_review_count"], reviews["data"]["ratings"])

Response

"employer_id": 1699,

"name": "NIKE, Inc.",

"short_name": "NIKE",

"url": "https://www.glassdoor.com/Reviews/NIKE-Reviews-E1699.htm",

"reviews_url": "https://www.glassdoor.com/Reviews/NIKE-Reviews-E1699.htm",

"salaries_url": "https://www.glassdoor.com/Salary/NIKE-Salaries-E1699.htm",

"rating": 3.9,

"total_review_count": 17798,

"rating_count": 15171,

"filtered_review_count": 13251,

"count": 3,

"response_time": 10679,

"credits_used": 1,

"credits_remaining": 4820

}

from scavio import ScavioClient client = ScavioClient(api_key="sk_live_your_key", timeout=180) # Fastest path: chain on reviews_url from the profile (one upstream fetch) profile = client.glassdoor.company(employer_id="1699") reviews = client.glassdoor.reviews( url=profile["data"]["reviews_url"], category="work_life_balance", employment_status="full_time", ) # Three bodies max - the aggregates describe the whole population print(reviews["data"]["filtered_review_count"], reviews["data"]["ratings"])