Kununu Company Reviews & Salary Scraper

Discover more ➤	Handelsregister API	Similarweb Scraper	Glassdoor Jobs & Company Scraper	Wellfound Jobs & Company Scraper

The Kununu Company Score Scraper on Apify provides powerful, structured insights into employer reputation, employee satisfaction, and salary transparency — all directly sourced from Kununu.

This fast and intelligent scraper extracts company ratings, employee and candidate reviews, salary benchmarks, and sentiment summaries for thousands of organizations. It supports multiple input modes, from direct Kununu URLs, company slugs, or even any company website using AI-powered web search to automatically resolve the right Kununu profile.

Whether you’re in HR, recruitment, employer branding, or market research, this scraper delivers clean, structured data that helps you understand how employees and candidates truly perceive a company — ready for export in JSON, CSV, or XLSX formats.

❶ Key Features

• Flexible Input Methods ✅

  • Direct Kununu company page URLs for instant score extraction
  • Kununu company slugs for streamlined batch processing
  • Company names with intelligent matching
  • AI Web Search Integration Input any company website URL and automatically resolve to the corresponding Kununu company profile

• Comprehensive Score & Review Extraction ✅

  • Retrieves overall company ratings, employee and candidate scores, and industry benchmarks
  • Extracts historical rating trends and satisfaction data over time
  • Collects recommendation rates, review counts, and key company metadata with timestamps

• Salary Insights & Benchmarking ✅

  • Access average, median, minimum, and maximum salary data per job title
  • Compare compensation against industry averages and satisfaction scores
  • Perfect for salary benchmarking, pay equity analysis, and HR strategy

• Authentic Review Summaries ✅

  • Extracts full, unaltered employee and candidate review texts directly from Kununu
  • Captures pros, cons, and suggestions sections for genuine sentiment analysis
  • Ideal for natural language processing and HR research use cases

• Built for Performance ✅

  • Optimized for fast, reliable data extraction with intelligent error handling
  • Scales seamlessly using our reliable proxy infrastructure
  • Maintains consistent data integrity across high-volume workloads

• Flexible Export Options ✅

  • Download structured results as JSON, CSV, XLSX, or JSONL
  • Easy integration with Python, R, Power BI, Excel, or any analytics platform
  • Ideal for employer branding, HR analytics, and competitive research

❷ Output

Table View Output

Reviews Table 🔖

Companies Table 🏦

Salaries Table 💵

Company & Reviews Data

Requires Company Name / Slug or Kununu URL Input

{
    "data_captured_at": "2026-05-30T17:24:56.913291",
    "company_uuid": "a5dd88da-e3a9-4553-a503-49cdc624862b",
    "company_slug": "mercedes-benz-group",
    "company_name": "Mercedes-Benz Group",
    "industry": "Automobil",
    "employer_segment": "giant",
    "employee_number": null,
    "revenue": null,
    "verified": true,
    "is_top_company": true,
    "top_company_years": [2026, 2025, 2024, 2023, 2022],
    "paying_top_company_badge": false,
    "company_website": "https://www.career.daimler.com",
    "company_overall_score": 3.9,
    "company_overall_score_trend_last_24_months": 3.9,
    "company_overall_score_trend_older_than_24_months": 4.0,
    "company_overall_score_history": [
        {
            "year": 2022,
            "score": 3.8,
            "score_rounded": 4.0,
            "total_reviews": 443
        },
        {
            "year": 2023,
            "score": 3.9,
            "score_rounded": 4.0,
            "total_reviews": 593
        },
        {
            "year": 2024,
            "score": 3.9,
            "score_rounded": 4.0,
            "total_reviews": 689
        },
        {
            "year": 2025,
            "score": 3.9,
            "score_rounded": 4.0,
            "total_reviews": 752
        },
        {
            "year": 2026,
            "score": 3.9,
            "score_rounded": 4.0,
            "total_reviews": 257
        }
    ],
    "industry_average_score": 3.5,
    "employees_overall_score": 3.9,
    "employees_overall_score_rounded": 4.0,
    "candidates_overall_score": 2.7,
    "candidates_overall_score_rounded": 2.5,
    "newest_employee_review_date": "2026-05-28T00:00:00Z",
    "oldest_employee_review_date": "2018-08-17T00:00:00Z",
    "newest_candidate_review_date": "2026-04-17T00:00:00Z",
    "oldest_candidate_review_date": "2009-07-16T00:00:00Z",
    "company_recommendation_percentage": 78.0,
    "company_recommended_reviews_count": 1035,
    "company_not_recommended_reviews_count": 295,
    "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": 331,
    "salary_reviews_count": 6852,
    "salary_industry_comparison": 20.0,
    "reviews_count": 7669,
    "employee_reviews_count": 7191,
    "reviews_apprenticeship_count": 202,
    "candidate_reviews_count": 478,
    "total_reviews_with_text_count": 4437,
    "deleted_reviews_count_last_24_months": 90,
    "candidate_reviews_score_4_to_5": 142.0,
    "candidate_reviews_score_4_to_5_percentage": 30.0,
    "candidate_reviews_score_3_to_4": 57.0,
    "candidate_reviews_score_3_to_4_percentage": 12.0,
    "candidate_reviews_score_2_to_3": 72.0,
    "candidate_reviews_score_2_to_3_percentage": 15.0,
    "candidate_reviews_score_1_to_2": 207.0,
    "candidate_reviews_score_1_to_2_percentage": 43.0,
    "employee_reviews_score_4_to_5": 4318.0,
    "employee_reviews_score_4_to_5_percentage": 60.0,
    "employee_reviews_score_3_to_4": 1739.0,
    "employee_reviews_score_3_to_4_percentage": 24.0,
    "employee_reviews_score_2_to_3": 819.0,
    "employee_reviews_score_2_to_3_percentage": 11.0,
    "employee_reviews_score_1_to_2": 315.0,
    "employee_reviews_score_1_to_2_percentage": 4.0,
    "reviews_response_time_days": 7.0,
    "total_reviews_responded_percentage": 0.6,
    "total_reviews_response_count": 47,
    "total_employer_reviews_response_count": 42,
    "total_apprenticeship_reviews_response_count": 3,
    "total_application_reviews_response_count": 2,
    "reviews_ai_summary": "Bei Mercedes-Benz Group herrscht insgesamt eine positive Arbeitsatmosphäre, wie die Bewertungen zeigen. Besonders geschätzt werden die kollegiale Zusammenarbeit und die attraktiven Gehälter mit Sozialleistungen. Die Work-Life-Balance wird durch Flexibilität bei Arbeitszeiten und Home-Office-Möglichkeiten positiv bewertet. Allerdings gibt es auch Kritikpunkte: Das Führungsverhalten wird als uneinheitlich wahrgenommen, und die Kommunikation könnte transparenter sein. In jüngster Zeit haben Sparmaßnahmen und Personalabbau zu einer Verschlechterung der Stimmung in manchen Bereichen geführt. Karrieremöglichkeiten werden zunehmend als eingeschränkt empfunden, wobei Weiterbildungsangebote grundsätzlich vorhanden sind.\n\nDie Arbeitsbedingungen und das Unternehmensimage werden überwiegend positiv bewertet, wenngleich der Stern etwas an Glanz verloren hat. Das Umwelt- und Sozialbewusstsein wird als wichtiger Teil der Unternehmensphilosophie angesehen, auch wenn die Umsetzung nicht immer konsequent erfolgt. Im Bereich der Gleichberechtigung gibt es unterschiedliche Wahrnehmungen – während einige Mitarbeiter:innen von gelebter Gleichberechtigung berichten, sehen andere noch Verbesserungspotenzial.\n\nGut finden Arbeitnehmende:\n- Attraktives Gehaltsniveau mit zusätzlichen Sozialleistungen\n- Flexible Arbeitszeiten und Home-Office-Möglichkeiten\n- Kollegialer Zusammenhalt und interessante Aufgabenfelder\n\nAls verbesserungswürdig geben sie an:\n- Uneinheitliches Führungsverhalten und mangelnde Transparenz\n- Eingeschränkte Karrieremöglichkeiten durch Sparmaßnahmen\n- Zunehmender Leistungsdruck und Arbeitsintensivierung",
    "company_linkedin_url": null,
    "company_instagram_url": null,
    "company_facebook_url": null,
    "company_twitter_url": null,
    "company_youtube_url": null,
    "company_xing_url": null,
    "salaries": [
        {
            "job_company_slug": "mercedes-benz-group",
            "job_id": 24326,
            "job_role": "Entwicklungsingenieur:in",
            "job_slug": "entwicklungsingenieur-in",
            "average_salary": 89100.0,
            "median_salary": 90000.0,
            "min_salary": 48000.0,
            "max_salary": 116500.0,
            "number_of_reports": 282
        }
    ],
    "reviews": [
        {
            "uuid": "ab1d51ce-c6d0-4c66-836a-030295dfc990",
            "type": "employer",
            "created_at": "2026-05-28T00:00:00Z",
            "updated_at": "2026-05-28T00:00:00Z",
            "position": "employee",
            "title": "Sehr guter Arbeitgeber",
            "score": 5.0,
            "score_rounded": 5.0,
            "recommended": true,
            "multiple_review": false,
            "ratings": [
                {
                    "category": "atmosphere",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": "Sehr gut"
                },
                {
                    "category": "teamwork",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": "Gut"
                },
                {
                    "category": "communication",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": "Gut"
                },
                {
                    "category": "image",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "workLife",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "career",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "salary",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "environment",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "oldColleagues",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "leadership",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "workConditions",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "equality",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                },
                {
                    "category": "tasks",
                    "score": 5.0,
                    "score_rounded": 5.0,
                    "text": null
                }
            ],
            "reactions": {
                "agree_count": 0,
                "helpful_count": 0
            },
            "pros": null,
            "cons": null,
            "suggestions": null,
            "company": "Mercedes Benz",
            "review_company_slug": "mercedes-benz-group",
            "department": "operations",
            "location": "Sindelfingen",
            "response": null
        }
    ]
}

Review Data

Requires Company Name / Slug or Kununu URL Input

{
    "uuid": "ab1d51ce-c6d0-4c66-836a-030295dfc990",
    "type": "employer",
    "created_at": "2026-05-28T00:00:00Z",
    "updated_at": "2026-05-28T00:00:00Z",
    "position": "employee",
    "title": "Sehr guter Arbeitgeber",
    "score": 5.0,
    "score_rounded": 5.0,
    "recommended": true,
    "multiple_review": false,
    "ratings": [
        {
            "category": "atmosphere",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": "Sehr gut"
        },
        {
            "category": "teamwork",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": "Gut"
        },
        {
            "category": "communication",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": "Gut"
        },
        {
            "category": "image",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "workLife",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "career",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "salary",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "environment",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "oldColleagues",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "leadership",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "workConditions",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "equality",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        },
        {
            "category": "tasks",
            "score": 5.0,
            "score_rounded": 5.0,
            "text": null
        }
    ],
    "reactions": {
        "agree_count": 0,
        "helpful_count": 0
    },
    "pros": null,
    "cons": null,
    "suggestions": null,
    "company": "Mercedes Benz",
    "review_company_slug": "mercedes-benz-group",
    "department": "operations",
    "location": "Sindelfingen",
    "response": null
}

Salary Data

Requires Company Name / Slug or Kununu URL Input

{
    "job_company_slug": "mercedes-benz-group",
    "job_id": 24326,
    "job_role": "Entwicklungsingenieur:in",
    "job_slug": "entwicklungsingenieur-in",
    "average_salary": 89100.0,
    "median_salary": 90000.0,
    "min_salary": 48000.0,
    "max_salary": 116500.0,
    "number_of_reports": 282
}

Field Reference

Field	Type	Description
data_captured_at	string (ISO datetime)	Timestamp when the dataset was captured.
company_uuid	string (UUID)	Unique identifier of the company record.
company_slug	string	URL-friendly company identifier.
company_name	string	Displayed company name.
industry	string	Industry category associated with the company.
employer_segment	string	Employer size or segment classification.
employee_number	number or null	Number of employees, if available.
revenue	number or null	Company revenue, if available.
verified	boolean	Indicates whether the company profile is verified.
is_top_company	boolean	Indicates whether the company is marked as a top company.
top_company_years	array of numbers	Years in which the company received top company status.
paying_top_company_badge	boolean	Indicates whether the top company badge is paid.
company_website	string (URL)	Company careers or website URL.
company_overall_score	number	Displayed overall company rating score.
company_overall_score_trend_last_24_months	number	Overall score based on reviews from the last 24 months.
company_overall_score_trend_older_than_24_months	number	Overall score based on reviews older than 24 months.
company_overall_score_history	array of objects	Historical yearly company scores and review counts.
company_overall_score_history[].year	number	Year represented by the historical score entry.
company_overall_score_history[].score	number	Average company score for the year.
company_overall_score_history[].score_rounded	number	Rounded average company score for the year.
company_overall_score_history[].total_reviews	number	Total number of reviews included for the year.
industry_average_score	number	Average rating score for the company’s industry.
employees_overall_score	number	Overall rating score from employee reviews.
employees_overall_score_rounded	number	Rounded employee overall rating score.
candidates_overall_score	number	Overall rating score from candidate/application reviews.
candidates_overall_score_rounded	number	Rounded candidate overall rating score.
newest_employee_review_date	string (ISO datetime)	Date of the newest employee review.
oldest_employee_review_date	string (ISO datetime)	Date of the oldest employee review.
newest_candidate_review_date	string (ISO datetime)	Date of the newest candidate review.
oldest_candidate_review_date	string (ISO datetime)	Date of the oldest candidate review.
company_recommendation_percentage	number	Percentage of reviewers who recommend the company.
company_recommended_reviews_count	number	Number of reviews recommending the company.
company_not_recommended_reviews_count	number	Number of reviews not recommending the company.
salary_reviews_score	number	Overall salary satisfaction score.
salary_reviews_score_rounded	number	Rounded salary satisfaction score.
salary_statisfaction_positive_percentage	number	Percentage of positive salary satisfaction ratings.
salary_statisfaction_negative_percentage	number	Percentage of negative salary satisfaction ratings.
salary_statisfaction_neutral_percentage	number	Percentage of neutral salary satisfaction ratings.
salary_roles_count	number	Number of salary-related roles represented in the dataset.
salary_reviews_count	number	Number of salary reviews.
salary_industry_comparison	number	Salary comparison value relative to the industry benchmark.
reviews_count	number	Total number of reviews.
employee_reviews_count	number	Total number of employee reviews.
reviews_apprenticeship_count	number	Total number of apprenticeship reviews.
candidate_reviews_count	number	Total number of candidate/application reviews.
total_reviews_with_text_count	number	Number of reviews containing written text.
deleted_reviews_count_last_24_months	number	Number of reviews deleted within the last 24 months.
candidate_reviews_score_4_to_5	number	Number of candidate reviews with scores from 4 to 5.
candidate_reviews_score_4_to_5_percentage	number	Percentage of candidate reviews with scores from 4 to 5.
candidate_reviews_score_3_to_4	number	Number of candidate reviews with scores from 3 to 4.
candidate_reviews_score_3_to_4_percentage	number	Percentage of candidate reviews with scores from 3 to 4.
candidate_reviews_score_2_to_3	number	Number of candidate reviews with scores from 2 to 3.
candidate_reviews_score_2_to_3_percentage	number	Percentage of candidate reviews with scores from 2 to 3.
candidate_reviews_score_1_to_2	number	Number of candidate reviews with scores from 1 to 2.
candidate_reviews_score_1_to_2_percentage	number	Percentage of candidate reviews with scores from 1 to 2.
employee_reviews_score_4_to_5	number	Number of employee reviews with scores from 4 to 5.
employee_reviews_score_4_to_5_percentage	number	Percentage of employee reviews with scores from 4 to 5.
employee_reviews_score_3_to_4	number	Number of employee reviews with scores from 3 to 4.
employee_reviews_score_3_to_4_percentage	number	Percentage of employee reviews with scores from 3 to 4.
employee_reviews_score_2_to_3	number	Number of employee reviews with scores from 2 to 3.
employee_reviews_score_2_to_3_percentage	number	Percentage of employee reviews with scores from 2 to 3.
employee_reviews_score_1_to_2	number	Number of employee reviews with scores from 1 to 2.
employee_reviews_score_1_to_2_percentage	number	Percentage of employee reviews with scores from 1 to 2.
reviews_response_time_days	number	Average number of days taken to respond to reviews.
total_reviews_responded_percentage	number	Percentage of total reviews that received a response.
total_reviews_response_count	number	Total number of review responses.
total_employer_reviews_response_count	number	Number of responses to employer reviews.
total_apprenticeship_reviews_response_count	number	Number of responses to apprenticeship reviews.
total_application_reviews_response_count	number	Number of responses to application/candidate reviews.
reviews_ai_summary	string	AI-generated summary of review sentiment, strengths, and improvement areas.
company_linkedin_url	string (URL) or null	LinkedIn profile URL of the company, if available.
company_instagram_url	string (URL) or null	Instagram profile URL of the company, if available.
company_facebook_url	string (URL) or null	Facebook profile URL of the company, if available.
company_twitter_url	string (URL) or null	Twitter/X profile URL of the company, if available.
company_youtube_url	string (URL) or null	YouTube profile URL of the company, if available.
company_xing_url	string (URL) or null	XING profile URL of the company, if available.
salaries	array of objects	Individual records for a single job-role salary.
salaries[].job_company_slug	string	Company slug associated with the salary record.
salaries[].job_id	number	Unique identifier of the job role.
salaries[].job_role	string	Display name of the job role.
salaries[].job_slug	string	URL-friendly identifier of the job role.
salaries[].average_salary	number	Average salary reported for the job role.
salaries[].median_salary	number	Median salary reported for the job role.
salaries[].min_salary	number	Minimum reported salary for the job role.
salaries[].max_salary	number	Maximum reported salary for the job role.
salaries[].number_of_reports	number	Number of salary reports used for the salary benchmark.
reviews	array of objects	Individual employee, employer, apprenticeship, or candidate review records.
reviews[].uuid	string (UUID)	Unique identifier of the review.
reviews[].type	string	Review type, such as employer or candidate review.
reviews[].created_at	string (ISO datetime)	Timestamp when the review was created.
reviews[].updated_at	string (ISO datetime)	Timestamp when the review was last updated.
reviews[].position	string	Reviewer position or relationship to the company.
reviews[].title	string	Review title.
reviews[].score	number	Review score.
reviews[].score_rounded	number	Rounded review score.
reviews[].recommended	boolean	Indicates whether the reviewer recommends the company.
reviews[].multiple_review	boolean	Indicates whether the review is part of multiple reviews by the same reviewer.
reviews[].ratings	array of objects	Category-level rating breakdown for the review.
reviews[].reactions	object	User reaction counts associated with the review.
reviews[].pros	string or null	Positive feedback provided by the reviewer.
reviews[].cons	string or null	Negative feedback provided by the reviewer.
reviews[].suggestions	string or null	Improvement suggestions provided by the reviewer.
reviews[].company	string	Company name as stated in the review.
reviews[].review_company_slug	string	Company slug associated with the review.
reviews[].department	string or null	Department associated with the reviewer.
reviews[].location	string or null	Location associated with the review.
reviews[].response	object or null	Employer response to the review, if available.
reviews[].ratings[].category	string	Rating category, such as atmosphere, teamwork, salary, or leadership.
reviews[].ratings[].score	number	Score for the specific rating category.
reviews[].ratings[].score_rounded	number	Rounded score for the specific rating category.
reviews[].ratings[].text	string or null	Optional written comment for the rating category.
reviews[].reactions.agree_count	number	Number of users who agreed with the review.
reviews[].reactions.helpful_count	number	Number of users who marked the review as helpful.

❸ Input

Parameter	Type	Default	Description
companies	array (string)	["https://www.kununu.com/de/mercedes-benz-group","sap","Bundesagentur für Arbeit"]	One or more company profile URLs or company slugs to scrape. Supports bulk input via multiple links or slugs.
reviewType	selection (string)	All	Review types to scrape. Options include All, Employee, or Candidate.
review_posted	string	1 year	Time range filter specifying how many days from today reviews should be retrieved.
max_reviews	string	10	Maximum number of reviews per review type per company. Supports up to 50,000 reviews per run.
max_salaries	string	20	Maximum number of salary reports per company to retrieve.
include_reviews	boolean	true	Includes review data in the output. If disabled, only company data and optionally salary data are returned.
include_salaries	boolean	true	Includes salary data in the output. If disabled, only company data and optionally review data are returned.
format	boolean	formatted	Output format selection. formatted is optimized for CSV/Excel/Sheets, while raw is better suited for programmatic processing.
external_dataset_id	string	None	Include an existing dataset by id into the output

Supported URL Formats

URL format	Supported
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

• 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"
}

❹ Use Cases

• HR & Employer Branding Teams: Benchmark company reputation, identify sentiment drivers, and track brand perception over time.

• Recruiters & Talent Acquisition: Understand candidate experiences and feedback to optimize the hiring process.

• Employer Branding Agencies: Compare and monitor company ratings to guide brand reputation improvement strategies.

• Data Analysts & Researchers: Collect structured review data for sentiment analysis, trend modeling, and retention insights.

• Competitor Intelligence & Market Research: Analyze public perception and salary positioning across industries and competitors.

• Universities & Labor Market Experts: Study employee satisfaction, salary fairness, and organizational culture trends at scale.

❺ Usage Limits

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

User Type	Companies per Run	Reviews per Company	Review History	Salaries per Company	Monthly Runs	Reset Period
Free	Max 3 companies	Latest 100 reviews	Last 365 days	First 20 salaries	25 run(s)	30 days
Paid	Unlimited	Up to 10,000 reviews	Last 10 years	Up to 10,000 salaries	Unlimited runs	N/A

How Limits Work

Free Users:

• Maximum 3 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).

❻ FAQ

What data can you get from the Kununu Scraper?

The Kununu Scraper can extract a wide range of data including company reviews, ratings, salary information, and company metadata. This includes overall company scores, employee and candidate reviews, salary benchmarks, and more.

How do I use the Kununu Scraper?

You can use the Kununu Scraper by providing it with either direct Kununu company page URLs, company slugs, or even company names. The scraper will then extract the relevant data based on your input and output it in a structured format.

How long does it take to scrape data for a company?

The time it takes to scrape data for a company can vary based on the number of reviews and salaries available for that company. Usually it can take anywhere from a few seconds to several minutes per company for thousands of reviews.

❼ 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.

❽ Legality of web scraping

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

Our services are ethical and do not extract any private user data. They only extract what individuals or companies chose to share publicly. We therefore believe that our services, when used for ethical purposes by our users, are safe to use. 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. For more information you can read this blog post from Apify for more information on the legality of web scraping

❾ 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 general help on issues or integrations at suppport@radeance.com.
For custom projects, general suggestions or new use cases feel free to reach out to us at business@radeance.com