Kununu Scraper — DACH Employer Reviews & Ratings

Extract kununu.com employer reviews and ratings for any DACH company — overall and per-category scores, pros/cons/suggestions, reviewer details and company aggregates — as clean structured JSON through kununu's own data endpoints. This is the cheapest pay-per-result Kununu scraper on the Apify Store (from ~$0.001 per review), built for employer brand monitoring, HR research and recruitment intelligence.

Main Use Cases

• Employer review monitoring — track your company's kununu Score, recommendation rate and category scores over time.
• HR & recruitment intelligence — check what employees and candidates say before you hire, partner or apply.
• Employer branding & reputation management — surface recurring complaints and praise without reading hundreds of pages.
• Competitor benchmarking — compare employer ratings across companies in the same industry before making decisions.
• Labor-market research — build large-scale DACH employer review datasets for academic or market analysis.
• Candidate experience analysis — evaluate interview and application feedback from candidate reviews.

Extract Kununu Employer Reviews for DACH Companies

Kununu is the leading employer-review platform in the German-speaking market (Germany, Austria, Switzerland — DE, AT, CH) and part of New Work SE. kununu reports over 15 million workplace insights, including 4 million+ employer reviews. This actor turns those public reviews into a structured dataset you can query, filter and analyze.

Point it at one or more company profiles and it returns two row types:

• Company aggregate rows — one per company: overall score, total review count, recommendation rate, recommended/not-recommended counts, score ranges, factor scores and category scores.
• Review rows — one per review: headline, overall rating, recommendation flag, date, employment status, former-employee flag, department, location, pros/cons/suggestions, per-category ratings, reactions and employer responses.

Monitor Employer Ratings Without an Official Kununu API

Kununu does not offer an official public API, and its pages sit behind AWS CloudFront and AWS WAF, which block datacenter IPs and automated browsers. This actor solves both problems:

• It reads kununu's own JSON data endpoints — the same ones the kununu website uses internally — so there is no HTML parsing and no browser overhead.
• It solves AWS WAF JS-challenge tokens per residential proxy session and retries blocked requests automatically (up to 8 attempts) from fresh German residential IPs.
• Each company is scraped in one warm session (same IP + cookies), mimicking a real visitor so the WAF rate limiter does not kick in.

The result: a fast, lightweight HTTP scraper (no browser, no login) that is significantly cheaper per review than browser-based crawlers.

Export Review Data for HR Analytics and Employer Brand Research

Everything the actor collects lands in an Apify dataset that you can download as JSON, CSV, HTML or Excel, or pull programmatically via the Apify API. Typical research workflows:

• Aggregate pros/cons themes across hundreds of reviews per company.
• Slice reviews by department, location or employment status.
• Compare category scores (work-life balance, salary, career, culture) between companies.
• Feed review rows into BI dashboards, Power BI, Excel or Python/pandas pipelines.

Input Configuration

Field	Type	Required	Default	Notes
companyUrls	array	✅	["https://www.kununu.com/de/sap"]	Kununu profile URLs (https://www.kununu.com/de/sap), country-prefixed slugs (at/red-bull), or bare slugs (sap). DE, AT and CH can be mixed in one run.
maxReviewsPerCompany	integer	—	50	Upper limit of reviews collected per company (10 per API page). Free accounts get a capped preview of 10 per company.
reviewType	string	—	all	Which reviewer group to collect: all (employees + candidates), employees, or candidates.
includeCompanyAggregates	boolean	—	true	Emit a company row with overall score, review counts, recommendation rate and category scores.
maxItems	integer	—	200	Hard cap on total dataset rows — your main cost control.
proxyConfiguration	object	—	{ "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "de" }	Apify proxy selector. kununu is behind AWS WAF and blocks datacenter + non-EU IPs, so keep Apify Proxy on, use RESIDENTIAL and a German IP.

Output Fields

Review rows (type: "review"):

Field	Type	Description
reviewId	string	Unique review identifier (UUID)
companySlug / companyCountry	string	Company profile slug and country (de / at / ch)
companyName	string	Display name of the company
reviewTitle	string	Headline written by the reviewer
overallRating	number	Overall star rating (1.0 to 5.0)
recommended	boolean	Whether the reviewer recommends the employer
reviewDate	string	Date the review was posted (ISO 8601)
employmentStatus	string	Reviewer group (e.g. employee, manager, student)
isFormerEmployee	boolean	Whether the reviewer is a former employee
department	string	Department the reviewer worked in
location	string	City of the reviewed location
pros / cons / suggestions	string	Free-text review sections ("Was mir am Arbeitgeber gefällt", "Schlecht am Arbeitgeber", "Verbesserungsvorschläge")
categoryRatings	object	Per-category scores and comments (work-life balance, salary, culture, career…)
reactions	object	Reaction counts (e.g. helpful)
employerResponses	array	HR responses to the review
reviewUrl	string	Canonical URL of the review on kununu

Company aggregate rows (type: "company"):

Field	Type	Description
profileUrl	string	Canonical kununu company profile URL
companyId	string	Kununu company UUID
overallScore	number	Overall kununu score (e.g. 4.1)
totalReviews	number	Total review count shown on the profile
recommendationRate	number	Share of reviewers who recommend the employer (%)
recommendedTotalReviews / notRecommendedTotalReviews	number	Recommended / not-recommended review counts
scoreRanges	array	Score distribution buckets
factorScores	array	Per-factor scores (id, categoryId, score, roundedScore, totalReviews)
categoryScores	object	Category → { score, totalReviews } map

Example Input

{
    "companyUrls": [
        "https://www.kununu.com/de/sap",
        "at/red-bull",
        "sap"
    ],
    "maxReviewsPerCompany": 100,
    "reviewType": "all",
    "includeCompanyAggregates": true,
    "maxItems": 250,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "DE"
    }
}

Example Output

Company aggregate row:

{
    "type": "company",
    "companySlug": "sap",
    "companyCountry": "de",
    "profileUrl": "https://www.kununu.com/de/sap",
    "companyId": "a558284b-93ad-4015-a649-a1e152c479c8",
    "overallScore": 4.1,
    "totalReviews": 4671,
    "recommendationRate": 91,
    "recommendedTotalReviews": 4251,
    "notRecommendedTotalReviews": 420,
    "scoreRanges": [],
    "factorScores": [
        { "id": "workLifeBalance", "categoryId": "workLife", "score": 4.0, "roundedScore": 4.0, "totalReviews": 4510 }
    ],
    "categoryScores": {}
}

Review row:

{
    "type": "review",
    "reviewId": "80195042-b1aa-461d-9bed-5299f182295f",
    "companySlug": "sap",
    "companyCountry": "de",
    "companyName": "SAP SE",
    "reviewTitle": "Die Work-Life-Balance ist gut, aber ...",
    "overallRating": 3.5,
    "recommended": true,
    "reviewDate": "2026-08-01T00:00:00.000Z",
    "employmentStatus": "employee",
    "isFormerEmployee": false,
    "department": "it",
    "location": "Walldorf",
    "pros": "Flexible Arbeitszeiten ...",
    "cons": "Hohe Arbeitsbelastung ...",
    "suggestions": "Mehr Transparenz ...",
    "categoryRatings": { "workLifeBalance": { "score": 4.0, "text": "..." } },
    "reactions": { "helpful": { "count": 3 } },
    "employerResponses": [],
    "reviewUrl": "https://www.kununu.com/de/sap/bewertung/80195042-b1aa-461d-9bed-5299f182295f"
}

Scrape Kununu Data Through AWS WAF (How It Works)

1. Submit one or more kununu company URLs or slugs. The actor resolves each one through kununu's public company search middleware to find the correct profile in the right country.
2. For each company it opens one warm session (same IP + cookies) and paginates kununu's review and profile data endpoints — 10 reviews per API page.
3. If the AWS WAF throws a JS challenge, the actor solves the WAF token for that session and retries from a fresh residential IP (up to 8 attempts). DACH residential IPs are trusted most by the WAF.
4. Results stream to the Apify dataset in seconds for small batches. Company aggregate rows are emitted first (if enabled), followed by review rows in pagination order.

Integrations & Automation

Every run is callable through the Apify API, so you can:

• Schedule daily or weekly runs in Apify Console — ideal for employer review monitoring and reputation tracking.
• Chain with webhooks — trigger workflows when a run finishes (e.g. Slack alert when your kununu Score changes).
• Connect to no-code tools — Apify's built-in integrations make the actor available in Make, Zapier and n8n.
• Consume results programmatically via the Apify client libraries for JavaScript, Python and more.

Recommended schedule: run weekly for employer brand monitoring; run on-demand for HR due-diligence research. Recurring usage also keeps your dataset fresh and strengthens Apify Store recommendations.

Frequently Asked Questions About Scraping Kununu

Does kununu have an official API?

No. Kununu does not offer a public, self-service API. Company data and reviews are only accessible through the website and the data endpoints behind it. This actor provides programmatic access to that public data without an official API.

Why use this actor instead of the official API?

There is no self-service kununu API. The closest official options (employer branding products) are partner/sales-led and do not expose review exports. This actor gives instant, pay-per-result API access to public kununu reviews, scores and company aggregates — with no partner application and no login.

Is scraping kununu legal?

Scraping publicly available employer reviews for research and analysis is generally considered acceptable, but you are responsible for complying with kununu's Terms of Service and applicable data-protection laws (e.g. GDPR for EU personal data) when using the data. See the Legal & Compliance Disclaimer below.

Kununu vs Glassdoor — which has more DACH reviews?

For German-speaking employers, kununu is the dominant review platform — kununu states 4 million+ employer reviews and 15 million+ workplace insights across Germany, Austria and Switzerland, and reviews are written in German natively. Glassdoor's coverage in DACH is thinner and its official API is a restricted partner program. If you also need US/global employer review data, combine this actor with a Glassdoor scraper (see Related Actors).

What are alternatives to this actor / this data source?

• Other Apify actors for kununu (see Related Actors below) and Glassdoor / Indeed employer review scrapers.
• Manual browsing of kununu company pages — slow and unscalable for hundreds of companies.
• SaaS "kununu API" proxies — typically priced per request with monthly fees and lower limits.

How many reviews does kununu have?

Kununu's own figures: over 15 million workplace insights, including more than 4 million employer reviews, growing by roughly 10,800 employer reviews per week (as published on kununu.com).

Can I scrape both employee and candidate reviews?

Yes. Set reviewType to all (default) to collect both, or restrict to employees or candidates. With all, the per-company budget is split between the two groups.

How much does it cost to scrape kununu?

The actor is pay-per-event: roughly $0.001 per dataset row (~$0.00097 on higher Apify plans) plus a small run-start fee (about $0.0002 per run at default 4 GB memory). Remember maxItems is your hard cost cap. Free Apify accounts get a preview of 10 reviews per company.

Can I monitor my kununu employer rating over time?

Yes. Schedule the actor daily or weekly in Apify Console and combine the company aggregate rows over time to chart the kununu Score, recommendation rate and category scores — full reputation monitoring without manual page visits.

What countries does this kununu scraper cover?

Germany (de), Austria (at) and Switzerland (ch). You can mix countries in a single run, e.g. https://www.kununu.com/de/sap and https://www.kununu.com/at/red-bull.

Related Actors

• Glassdoor Reviews & Jobs · No 200-Cap · AI Employer Intel — the largest employer-review actor on Apify; covers Glassdoor reviews, jobs and salaries.
• Glassdoor Reviews Scraper — extracts authentic Glassdoor employee reviews for company culture, compensation and work-life balance research.
• Kununu.com Companies Scraper — another kununu company/review data actor for cross-checking DACH employer data.
• Kununu Scraper · DACH Employer Reviews, Salaries & Jobs — kununu data with salary tables, job postings and contact-email enrichment.
• Indeed Employer Intelligence — Indeed employer reviews, interview Q&A and company dossiers for a broader reviews dataset.

Competitive Positioning

Verified against the kununu actors currently listed on the Apify Store (BRONZE-tier prices from their public pricing pages):

Capability	Other kununu actors on Apify	This actor
Price per review/row	$0.0038 – $0.0167 (e.g. automation-lab $0.0038364, data_api $0.00466, kawsar $0.01667)	~$0.001 (FREE tier), $0.00097+ on higher plans
Free preview plan	Varies	Capped preview: 10 reviews per company
DACH country coverage	Several actors cover DE/AT/CH	DE, AT, CH — mixed in one run
Technical approach	Browser/HTML parsing in most cases	kununu's JSON data endpoints + automatic AWS WAF token handling

SEO Keywords

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For AI Agents & LLM Apps

This actor is callable via the Apify MCP server and the Apify REST API by other agents.

Purpose: Given one or more kununu company URLs/slugs, returns structured company aggregate + review rows (ratings, pros/cons, reviewer metadata, category scores) for DACH employers.

Minimal working input:

{ "companyUrls": ["https://www.kununu.com/de/sap"], "maxItems": 100 }

Variant inputs:

{ "companyUrls": ["sap"], "reviewType": "candidates", "maxReviewsPerCompany": 30, "includeCompanyAggregates": false, "maxItems": 90 }

Output fields (dataset rows): type, reviewId, companySlug, companyCountry, companyName, reviewTitle, overallRating, recommended, reviewDate, employmentStatus, isFormerEmployee, department, location, pros, cons, suggestions, categoryRatings, reactions, employerResponses, reviewUrl (review rows); profileUrl, companyId, overallScore, totalReviews, recommendationRate, recommendedTotalReviews, notRecommendedTotalReviews, scoreRanges, factorScores, categoryScores (company rows).

Behaviors an agent should know:

• maxItems is a hard cap on total dataset rows — always set it to bound cost. Unset it and the default (200) still applies.
• With reviewType: "all" (default), the per-company review budget is split roughly evenly between employee and candidate reviews.
• Free Apify accounts are limited to 10 reviews per company regardless of maxReviewsPerCompany; set it explicitly for predictability.
• proxyConfiguration defaults to Apify Proxy + RESIDENTIAL + country DE. Keep residential proxies on — kununu blocks datacenter IPs via AWS WAF.
• Company aggregate rows are only emitted when includeCompanyAggregates is true (default).
• Input accepts full URLs, country-prefixed slugs (at/red-bull) and bare slugs (sap); bare slugs are treated as Germany (de).
• Each company runs in one warm IP session; blocked requests are retried automatically with fresh residential IPs (up to 8 attempts).

Billing: pay-per-event. ~$0.001 per dataset row (less on higher Apify plans; $0.00097 GOLD) + a small run-start fee ($0.0002 per run at 4096 MB memory). Use maxItems to cap a run's spend.

Legal & Compliance Disclaimer

Kununu Scraper is an independent tool and is not affiliated with, endorsed by, or sponsored by kununu GmbH or New Work SE.

The actor only reads publicly available kununu company profiles and the public data endpoints behind them. It does not require or use any kununu account or login, and it does not solve CAPTCHAs. It does not extract personal contact data such as email addresses or phone numbers.

You are responsible for your own compliance with kununu's Terms of Service and applicable data-protection law when using the extracted data. Since reviews may contain EU personal data (names, roles, locations), process them in line with the GDPR. Do not use review content for harassment, defamation or retaliation against individual reviewers.

If you need help staying compliant, contact us via the Issues tab — custom solutions are available.