Kununu Scraper – DACH Employer Reviews, Ratings & Salaries

🏢 Kununu Scraper – DACH Employer Reviews, Ratings & Salaries

Scrape kununu.com, the largest employer review site in Germany, Austria and Switzerland. Get each employer's kununu score, recommendation rate, category scores, benefits, culture compass, awards and salary ranges, plus the employee and applicant reviews with pros, cons, sub-ratings and employer responses. No login, no cookies, results in seconds, from $0.60 per 1,000 rows.

✨ Why use Kununu Scraper?

• ⚡ Fast – a company row and its newest reviews arrive in about 10 seconds; it reads kununu's own JSON data instead of rendering pages.
• 🔎 Three ways in – company names, kununu profile URLs or a free employer search (with industry filter).
• ⭐ Full reviews – overall rating, all 13 sub-ratings with comments, pros, cons, suggestions, position, department, recommendation and the employer's reply.
• 🎤 Interview reviews – applicant reviews with interview result, year, sub-ratings and questions.
• 💶 Salaries and benefits included – salary ranges per job title, salary satisfaction, the benefits employees confirm, Kulturkompass scores and awards, at no extra cost.
• 💸 Cheap and simple – one flat price per row, company rows and review rows alike.

🎯 Use cases

• 👔 Employer branding – track your own kununu score, new reviews and employer responses every week.
• 🕵️ Competitor benchmarking – compare scores, category ratings, benefits and salary ranges across rivals in your industry.
• 🧲 Recruiting and lead generation – find well-rated employers by industry or city, or employers with weak scores who need HR help.
• 📊 HR and labour market research – analyse sentiment, work-life balance or salary satisfaction across thousands of DACH companies.
• 🤖 AI and NLP datasets – German-language review text with structured ratings for sentiment models and summaries.

🚀 How to use

1. Enter company names (for example Bosch, SAP) or paste kununu URLs (for example https://www.kununu.com/de/bosch-gruppe), or type an employer search such as software.
2. Pick the country (Germany, Austria or Switzerland) for names and searches. Pasted URLs keep their own country.
3. Set Max results and how many reviews you want per company. Switch on applicant reviews or profile texts if you need them.
4. Click Start and download the results as JSON, CSV, Excel or HTML, or read them through the API.

📥 Input

{
  "companyNames": ["Bosch", "SAP"],
  "startUrls": ["https://www.kununu.com/at/oebb-konzern"],
  "countryCode": "de",
  "maxItems": 100,
  "includeReviews": true,
  "maxReviewsPerCompany": 30,
  "reviewSort": "newest",
  "includeApplicantReviews": true,
  "maxApplicantReviewsPerCompany": 10
}

📤 Output

Every row has a type: company or review (with reviewKind employee or applicant). The Output tab has separate tables for companies and reviews.

Example rows (shortened; the company and review are fictional samples in the real format):

[
  {
    "type": "company",
    "countryCode": "de",
    "slug": "beispiel-logistik",
    "url": "https://www.kununu.com/de/beispiel-logistik",
    "name": "Beispiel Logistik GmbH",
    "kununuScore": 3.9,
    "recommendationRate": 81,
    "industryAverageScore": 3.5,
    "reviewCount": 412,
    "employeeReviewCount": 371,
    "applicantReviewCount": 41,
    "categoryScores": {"atmosphere": 4.1, "workLife": 3.8, "salary": 3.6, "career": 3.4},
    "benefits": [{"id": "homeOffice", "label": "Homeoffice", "mentions": 188, "percentage": 51}],
    "salaries": [{"jobTitle": "Disponent:in", "min": 36200, "max": 52400, "median": 43800, "entries": 37, "period": "year"}],
    "culture": {"submissions": 120, "compassCompany": 104, "styleCompany": "MODERN"},
    "city": "Hamburg",
    "state": "Hamburg",
    "employeeCountText": "rund 900 Mitarbeitende"
  },
  {
    "type": "review",
    "reviewKind": "employee",
    "companyName": "Beispiel Logistik GmbH",
    "url": "https://www.kununu.com/de/beispiel-logistik/bewertung/00000000-0000-4000-8000-000000000001",
    "title": "Gutes Team, Schichtplanung ausbaufähig",
    "rating": 3.8,
    "datePublished": "2026-09-30",
    "recommended": true,
    "position": "employee",
    "department": "logistic",
    "pros": "Kollegialer Zusammenhalt und pünktliches Gehalt.",
    "cons": "Schichtpläne kommen oft sehr kurzfristig.",
    "suggestions": "Dienstpläne früher veröffentlichen.",
    "subRatings": {"atmosphere": 4, "workLife": 3, "salary": 4, "leadership": 3},
    "employerResponses": [{"text": "Danke für dein Feedback ...", "date": "2026-10-02", "author": "HR Team"}]
  }
]

💰 Pricing

You pay $0.60 per 1,000 rows ($0.0006 per company or review row), plus the small platform usage of the run (compute and datacenter proxy traffic), which is shown on every run.

• A company with its 19 newest reviews (20 rows) costs about $0.012 in row fees.
• 1,000 rows ≈ $0.60 in row fees plus a few cents of usage.

Set a spending limit on the run and the scraper stops cleanly when it is reached.

❓ FAQ

Is it legal to scrape kununu? The actor only reads public pages that anyone can open without an account. Reviews on kununu are anonymous. Check your local rules (for example GDPR) for how you store and use the data.

Do I need a login or proxy? No login. Datacenter proxies are set by default and work well; if kununu refuses them repeatedly, the run switches to residential proxies by itself.

How many reviews can I get? Without login kununu shows a limited set of each large employer's reviews: typically several hundred employee reviews and up to about 100 applicant reviews. Small and mid-sized employers are usually covered completely. The status message tells you how many were available.

Why is a field empty? Many reviews only have ratings and no text, and employers fill their profile texts, salary data and benefits to different degrees. Empty values are null or an empty list.

Can I schedule it or use the API? Yes. Schedule it for weekly monitoring, or start it from the API and read the dataset as JSON, CSV or Excel. Company and review rows have stable IDs (companyId, reviewId) for deduplication.

I used another kununu scraper before. The main fields have the same meaning (kununuScore, recommendationRate, reviewCount, pros, cons ...). Nested data such as categoryScores, benefits and salaries stays structured instead of being flattened into JSON strings.

⚠️ Limits

• Only public data: kununu's login-only views (all pages of a large employer's reviews, review filters) are not available.
• Large employers: a few hundred reviews per employer, not all thousands.
• Salary data is the summary shown on the profile (top job titles), not the full salary pages.
• Job postings are not included.
• Review text is in the language it was written in (mostly German).