Extract reviews data from Glassdoor and pipe into Make automatically
Navigate to the Glassdoor Reviews scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.
Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".
Paste the Glassdoor URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.
Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.
When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 35 fields like overview_id, review_id, review_url, company_name. Route the data to any downstream app — CRMs, databases, email tools, and more.
Cost per record
1 credit
Output fields
35 fields
Destination
Make
Preview the data you'll receive — 5 sample records
35 fields returned per record
Unique identifier for the company overview (100.00% fill rate)
Unique identifier for each review (100.00% fill rate)
Link to the specific review on Glassdoor (99.89% fill rate)
Name of the reviewed company (99.97% fill rate)
Summary overview of the review (98.83% fill rate)
Positive aspects mentioned in the review (100.00% fill rate)
Negative aspects mentioned in the review (100.00% fill rate)
Advice provided by the reviewer (1.93% fill rate)
Advice to the company's management (19.78% fill rate)
Overall rating given by the reviewer (100.00% fill rate)
Rating for work-life balance (83.49% fill rate)
Rating for company culture and values (82.89% fill rate)
Rating for diversity and inclusion (70.17% fill rate)
Rating for compensation and benefits (83.53% fill rate)
Rating for senior leadership (82.91% fill rate)
Rating for career opportunities (83.07% fill rate)
Date when the review was submitted (85.58% fill rate)
Employment status of the reviewer (e.g., full-time, part-time) (59.74% fill rate)
Status of employment (e.g., former employee, current employee) (80.79% fill rate)
Job title of the reviewing employee (44.72% fill rate)
Location of the reviewing employee (39.16% fill rate)
Length of time the employee worked at the company (78.73% fill rate)
Year when the employee's job ended (17.79% fill rate)
Number of responses provided by the employee (0.94% fill rate)
Sub-fields
responseTextEmployer response textdateTextResponse datetitleTextRespondent titleNumber of users who found the review helpful (72.19% fill rate)
Number of users who found the review unhelpful (65.89% fill rate)
Flag indicating if the review mentions COVID-19 (55.56% fill rate)
Flag indicating if the review is featured (56.15% fill rate)
Flags related to business outlook (67.65% fill rate)
Flags related to CEO approval (55.92% fill rate)
Flags related to recommending the company (63.89% fill rate)
Link to the reviews page on Glassdoor (53.85% fill rate)
Link to the company overview on Glassdoor (9.49% fill rate)
Original URL of the review (7.00% fill rate)
Glassdoor employer id (53.85% fill rate)
Common questions about How to Scrape Glassdoor Reviews into Make
Start extracting glassdoor reviews data and pipe into Make in minutes.