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Kununu Reviews Scraper

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$24.99/month + usage

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Kununu Reviews Scraper

Kununu Reviews Scraper

Developed by

Radeance

Radeance

Maintained by Community

Scrape company reviews, job salaries, HR responses, ratings, and timestamps. Fast, reliable, and built for scaling. Perfect for HR analytics, employer branding, and competitor research. Export clean data as JSON, CSV, XLSX, or JSONL.

3.8 (4)

Pricing

$24.99/month + usage

4

Total users

17

Monthly users

9

Runs succeeded

>99%

Last modified

6 days ago

💎 Kununu Company Reviews & Salary Scraper

Kununu Scraper Cover Image

Try our other scrapers ►Wellfound Premium Jobs ScraperGlassdoor Premium Jobs ScraperSimilarweb Scraper

Welcome to this Kununu Company Reviews Scraper on Apify!

This blazing-fast, feature-rich actor is designed to extract rich company review data from Kununu like a pro — whether you’re in HR, recruitment, employer branding, or market research. It effortlessly scrapes authentic employee and candidate reviews, delivering deep insights including overall company scores, review timelines, and detailed metadata on workplace experience.

This scraper is built for scale and insight — capable of pulling years of review data in seconds ⚡️⚡️

✨ Key Features

  • Comprehensive Company Review Scraping:
    • Scrapes all public reviews & HR responses from a specified Kununu company profile
    • Collects both employee and candidate reviews across all available years
    • Captures full review metadata including scores, timestamps, and source types
  • Detailed Rating Breakdown:
    • Extracts overall company rating, employee rating, and candidate rating
    • Includes both raw and rounded scores for consistent reporting
    • Supports review time-span analysis with oldest and newest review dates
  • Clean, Structured Output:
    • Outputs data in machine-readable JSON format, ready for immediate analysis
    • Ideal for integrating into HR dashboards, BI tools, or data pipelines
    • All data is stored securely in Apify Dataset for easy export and automation
  • Built for Performance:
    • Optimized for fast, reliable scraping even across large review histories
    • Intelligent error handling and retries ensure high data integrity
    • Scales seamlessly with large numbers of requests via Apify proxy infrastructure
  • Flexible Export Options:
    • Download data as JSON, CSV, XLSX, or JSONL
    • Easily import into tools like Python, R, Power BI, or Excel
    • Perfect for internal benchmarks, competitor analysis, or employer branding research

Output

Table Views

Reviews

Reviews Table View Output

Companies

Company Table View Output

Salaries

Reviews Table View Output

JSON

{
"company_uuid": "a5dd88da-e3a9-4553-a503-49cdc624862b",
"company_slug": "mercedes-benz-group",
"company_name": "Mercedes-Benz Group",
"industry": "Automobil",
"verified": true,
"paying_top_company_badge": false,
"company_website": "https://www.career.daimler.com",
"company_overall_score": 3.9,
"industry_average_score": 3.5,
"employees_overall_score": 4.0,
"employees_overall_score_rounded": 4.0,
"candidates_overall_score": 2.7,
"candidates_overall_score_rounded": 2.5,
"newest_employee_review_date": "2025-06-18T00:00:00Z",
"oldest_employee_review_date": "2025-05-15T00:00:00Z",
"newest_candidate_review_date": "2025-04-23T00:00:00Z",
"oldest_candidate_review_date": "2024-09-05T00:00:00Z",
"company_recommendation_percentage": 78.0,
"company_recommended_reviews_count": 1013,
"company_not_recommended_reviews_count": 289,
"salary_reviews_score": 4.2,
"salary_reviews_score_rounded": 4.0,
"salary_statisfaction_positive_percentage": 80.0,
"salary_statisfaction_negative_percentage": 8.0,
"salary_statisfaction_neutral_percentage": 12.0,
"salary_roles_count": 325,
"salary_reviews_count": 6328,
"salary_industry_comparison": 20.0,
"salaries": [
{
"job_company_slug": "mercedes-benz-group",
"job_id": 24326,
"job_role": "Entwicklungsingenieur:in",
"job_slug": "entwicklungsingenieur-in",
"average_salary": 86600.0,
"median_salary": 88000.0,
"min_salary": 47200.0,
"max_salary": 118500.0,
"number_of_reports": 300
},
{
"job_company_slug": "mercedes-benz-group",
"job_id": 23921,
"job_role": "Ingenieur:in",
"job_slug": "ingenieur-in",
"average_salary": 85200.0,
"median_salary": 85400.0,
"min_salary": 49000.0,
"max_salary": 129100.0,
"number_of_reports": 198
},
{
"job_company_slug": "mercedes-benz-group",
"job_id": 25050,
"job_role": "Projektmanager:in",
"job_slug": "projektmanager-in",
"average_salary": 81500.0,
"median_salary": 80000.0,
"min_salary": 49000.0,
"max_salary": 132900.0,
"number_of_reports": 178
},
{
"job_company_slug": "mercedes-benz-group",
"job_id": 15019,
"job_role": "Softwareentwickler:in",
"job_slug": "softwareentwickler-in",
"average_salary": 79900.0,
"median_salary": 80000.0,
"min_salary": 49000.0,
"max_salary": 117000.0,
"number_of_reports": 142
}
],
"reviews_count": 7075,
"employee_reviews_count": 6603,
"reviews_apprenticeship_count": 175,
"candidate_reviews_count": 472,
"candidate_reviews_score_4_to_5": 140.0,
"candidate_reviews_score_4_to_5_percentage": 30.0,
"candidate_reviews_score_3_to_4": 56.0,
"candidate_reviews_score_3_to_4_percentage": 12.0,
"candidate_reviews_score_2_to_3": 71.0,
"candidate_reviews_score_2_to_3_percentage": 15.0,
"candidate_reviews_score_1_to_2": 205.0,
"candidate_reviews_score_1_to_2_percentage": 43.0,
"employee_reviews_score_4_to_5": 4000.0,
"employee_reviews_score_4_to_5_percentage": 61.0,
"employee_reviews_score_3_to_4": 1561.0,
"employee_reviews_score_3_to_4_percentage": 24.0,
"employee_reviews_score_2_to_3": 746.0,
"employee_reviews_score_2_to_3_percentage": 11.0,
"employee_reviews_score_1_to_2": 296.0,
"employee_reviews_score_1_to_2_percentage": 4.0,
"reviews_ai_summary": "Die Mitarbeiter:innen des Mercedes-Benz Group bewerten die Arbeitsatmosphäre überwiegend positiv. Es werden Kooperation, Harmonie und hilfreiche Kolleg:innen hervorgehoben, insbesondere in der Entwicklung und in modernen Büroräumen. Trotz einzelner negativer Äußerungen über die Auswirkungen von Umstrukturierungen und Unsicherheit im Markt bleibt der allgemeine Eindruck positiv. Auch das Verhalten von Vorgesetzten wird positiv wahrgenommen, wobei wertschätzendes und verständnisvolles Management bescheinigt wird..",
"reviews": [
{
"uuid": "514e562a-7ffe-4c3c-a185-bf01a37f15c1",
"type": "employer",
"created_at": "2025-05-31T00:00:00Z",
"updated_at": "2025-05-31T00:00:00Z",
"position": "employee",
"title": "Arbeitsatmosphäre unterschiedlich je nach Team",
"score": 4.3,
"score_rounded": 4.5,
"recommended": true,
"multiple_review": false,
"ratings": [
{
"category": "leadership",
"score": 5.0,
"score_rounded": 5.0,
"text": "Teamabhängig"
},
{
"category": "tasks",
"score": 5.0,
"score_rounded": 5.0,
"text": "Teamabhängig"
},
{
"category": "atmosphere",
"score": 5.0,
"score_rounded": 5.0,
"text": null
},
{
"category": "image",
"score": 4.0,
"score_rounded": 4.0,
"text": null
},
{
"category": "workLife",
"score": 5.0,
"score_rounded": 5.0,
"text": null
},
{
"category": "career",
"score": 4.0,
"score_rounded": 4.0,
"text": null
},
{
"category": "salary",
"score": 5.0,
"score_rounded": 5.0,
"text": null
},
{
"category": "environment",
"score": 3.0,
"score_rounded": 3.0,
"text": null
},
{
"category": "teamwork",
"score": 5.0,
"score_rounded": 5.0,
"text": null
},
{
"category": "oldColleagues",
"score": 4.0,
"score_rounded": 4.0,
"text": null
},
{
"category": "workConditions",
"score": 4.0,
"score_rounded": 4.0,
"text": null
},
{
"category": "communication",
"score": 3.0,
"score_rounded": 3.0,
"text": null
},
{
"category": "equality",
"score": 4.0,
"score_rounded": 4.0,
"text": null
}
],
"reactions": {
"agree_count": 0,
"helpful_count": 0
},
"pros": "Betriebsvereinbarung zum mobilen Arbeiten",
"cons": "Luxus-Strategie",
"suggestions": "Echte Teamarbeit fördern, die meisten Teams sind Gruppen von Einzelkämpfern<br/>Bei der Führungskräfte-Auswahl Sozialkompetenz stärker berücksichtigen",
"company": "Mercedes-Benz Düsseldorf Werk65 Sprinter",
"review_company_slug": "mercedes-benz-group",
"department": "it",
"location": "Düsseldorf",
"response": null
}
]
}

🗂️ Use Cases

  • HR & People Teams: Benchmark your employer brand by analyzing public employee and candidate feedback
  • Employer Branding Agencies: Track sentiment trends and identify key areas for reputation improvement
  • Recruiters & Talent Acquisition: Understand how candidates perceive the hiring process at specific companies
  • Data Scientists & Analysts: Collect structured review data for modeling sentiment, trends, or retention risks
  • Competitor Intelligence Teams: Monitor public perception of competing employers to inform strategy
  • Academics & Researchers: Study workplace culture, employee satisfaction, and employer reputation across industries

📌 Input

Scraper Sample Input

  • companies: (Required) (Array of Strings) Provide one or more Company Profile URLs or just the company slug to scrape. You can add them individually or use the Bulk edit option to paste in multiple links at once.
    Default: ["https://www.kununu.com/bmw", "https://www.kununu.com/de/mercedes-benz-group", "sap", "Bundesagentur für Arbeit"]
  • reviewType: (Optional) (Selection) Select which types of reviews you want to scrape. Available options are All, Employee, Candidate.
    Default: All
  • review_posted: (Optional) (String) Specify the number of days from today that you want to retrieve reviews.
    Default: 1 year
  • max_reviews: (Optional) (String) Specify the number of reviews per company you want to retrieve.
    Default: 100
  • max_salaries: (Optional) (String) Specify the maximum number of salary reports per company you want to retrieve.
    Default: 20
  • include_reviews: (Optional) (Boolean) Set to true if you want to include review data in the output. If set to false, only company data and optionally salary data will be returned.
    Default: true
  • include_salaries: (Optional) (Boolean) Set to true if you want to include salary data in the output. If set to false, only company and optionally review data will be returned.
    Default: true
  • format: (Optional) (Boolean) Choose the output format for the data. You can select between formatted (best for CSV/Excel/Google Sheets) or raw (legacy format, best for further processing in code).
    Default: formatted

Supported URL Formats

URL formatSupported
https://www.kununu.com/de/sap
https://www.kununu.com/at/mercedes-benz-group
https://www.kununu.com/ch/bmw
https://www.kununu.com/sap
https://kununu.com/de/mercedes-benz-group
https://kununu.com/bmw
https://www.kununu.com/de/sap/kommentare
https://kununu.com/mercedes-benz-group/kommentare
bmw

🎛️ Advanced Options

Scraper Sample Advanced Options Input

  • proxySettings: (Optional) (Object) Customize the proxy settings used by the scraper. For example Apify Residential proxies from the US can be used for stability and region-specific access. You can change the proxy group or country as needed.
    Default:
    { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "DE" }

JSON Input

Sample JSON input if you use the apify api via CURL, Python, JS etc.

{
"companies": [
"https://www.kununu.com/sap",
"https://www.kununu.com/de/bmw",
"mercedes-benz-group"
],
"include_salaries": true,
"max_reviews": 100,
"proxySettings": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
},
"review_posted": "30 days"
}

Usage Limits

This service has different usage limits depending on your subscription status:

User TypeCompanies per RunReviews per CompanyReview HistorySalaries per Company
FreeMax 5 companiesLatest 100 reviewsLast 365 daysFirst 20 salaries
PaidUnlimitedUp to 10,000 reviewsLast 10 yearsUp to 10,000 salaries

How Limits Work

Free Users:

  • Maximum 5 companies per run
  • Latest 100 reviews per company (from last 365 days)
  • First 20 salaries per company

Paid Users:

  • Unlimited companies per run
  • Up to 10,000 reviews per company (from last 10 years)
  • Up to 10,000 salaries per company

Note: All users can scrape multiple companies in a single run (within their respective limits).

⚙️ While the scraper is running

During the run, the actor will output log messages letting you know what is going on at any point. Each message always contains specific information about the process including which url / page the actor is working on.

If you provide invalid inputs to the actor, it will immediately stop with a failure state and output log messages explaining what is wrong. If you are unsure what went wrong feel free to open up an issue in the issue tab.

🔗 Legality of web scraping and scraping of job listings

The Kununu Reviews Scraper is designed to ethically extract only publicly available data, and it does not scrape private user data such as personal email addresses or personal identifiers.

Our scrapers are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our scrapers, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. You can also read this blog post blog post on the legality of web scraping

💬 Feedback and Support

Your satisfaction is important to us! Therefore we are constantly striving to enhance the performance of our Actors.

If you have any technical feedback or encounter any bugs with the Kununu Reviews Scraper, please create an issue in the Actor’s Issues tab on the Apify Console.

You can also contact us directly for custom integrations or project use cases at business@radeance.com.