Kununu Scraper - Company Ratings & Employer Reviews (DACH)

What does Kununu Scraper do?

Kununu Scraper extracts structured listing data from kununu.com — including salary data, company metadata, and ratings and reviews. It supports keyword search and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them.

Key features

• Incremental mode — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline state; subsequent runs emit only new or changed records.
• Detail enrichment — full descriptions and company metadata where the source provides them.
• Individual reviews — scrape per-employee reviews with factor ratings, pros/cons, position/department, and company replies. Per-review incremental tracking filters unchanged reviews from emission.
• Culture insights — Kulturkompass profile-vs-industry compass score, culture dimensions, strengths/weaknesses, and culture-tagged review comments.
• Full salary enrichment — all salary ranges across job titles with min/max/median/average, not just the top 3 shown on the summary page.
• Compact mode — AI-agent and MCP-friendly payloads with core fields only.

What data can you extract from kununu.com?

Each result includes Core listing fields (type, slug, uuid, portalUrl, matchStatus, matchConfidence, rating, and ratingRounded, and more), detail fields when enrichment is enabled (benefits), and company metadata (companyName, queryCompanyName, isTopCompany, and topCompanyYears). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them.

Input

The main inputs are a search keyword and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• mode — Which input to use. 'keyword' paginates search results for a query. 'companyNames' looks up a list of company names. 'companyUrls' uses direct kununu URLs. 'datasetId' reads names from an existing Apify dataset. Leave blank to auto-detect from the fields you fill in. (default: "keyword")
• query — Search term for keyword mode (e.g. 'software'). Required when mode=keyword. Leave blank for other modes.
• companyNames — List of company names to look up on kununu. Best match from first search page is returned.
• companyUrls — List of kununu company URLs (e.g. https://www.kununu.com/de/bosch-gruppe). Country code and slug are parsed from each URL — URLs can mix DE/AT/CH. Skips search and matching. Incremental mode works per-slug.
• datasetId — ID of an existing Apify dataset. Actor reads company names from this dataset and enriches with kununu ratings.
• companyFieldName — Field in the dataset that contains the company name. Default: companyName. (default: "companyName")
• deduplicateField — Optional field to deduplicate by before lookup (e.g. 'companyId'). Useful when multiple jobs share the same company.
• countryCode — Kununu country: de (Germany), at (Austria), ch (Switzerland). (default: "de")
• industryId — Filter results by industry ID. Only applies in keyword search mode. Common IDs: 1=Banking, 2=Construction, 3=Consulting, 4=Education, 5=Publishing, 6=Finance, 7=Healthcare, 8=Insurance, 9=Pharma, 10=IT/Software, 11=Engineering, 12=Automotive, 13=Chemicals, 14=Transport, 15=Retail, 16=Telecom, 17=Energy, 18=Media, 19=Public sector, 20=NGO, 43=Hotels, 44=Gastronomy. Find other IDs by filtering on kununu.com and checking the URL.
• maxResults — Maximum number of results to return. 0 = no limit. (default: 100)
• maxPages — Maximum number of search result pages to scrape in keyword mode. 0 = no limit. (default: 10)
• includeDetails — Fetch the company detail page to extract recommendation rate and website. Doubles the number of requests. (default: false)
• ...and 8 more parameters

Input examples

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "software",
  "maxResults": 50
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "software",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "software-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "query": "software",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured listing records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example listing record

{
  "type": "company",
  "companyName": "SAP SE",
  "slug": "sap",
  "uuid": "a558284b-93ad-4015-a649-a1e152c479c8",
  "portalUrl": "https://www.kununu.com/de/sap",
  "matchStatus": "EXACT_MATCH",
  "matchConfidence": 1,
  "queryCompanyName": "SAP SE",
  "rating": 4.3,
  "ratingRounded": 4,
  "reviewCount": 4844,
  "recommendationRate": 78,
  "recommendationTotalReviews": 624,
  "recommendationRecommended": 488,
  "recommendationNotRecommended": 136,
  "industry": "6",
  "location": "Walldorf / Baden-Württemb.",
  "country": "de",
  "countryCode": "de",
  "isTopCompany": true,
  "isVerified": true,
  "profileType": "Claimed",
  "totalJobs": 0,
  "website": "https://jobs.sap.com",
  "followerCount": 2806,
  "scoreBreakdown": [
    {
      "id": "AP_CATEGORY_CAREER",
      "score": 4.3,
      "roundedScore": 4.5,
      "totalReviews": 4504,
      "factors": [
        {
          "id": "salary",
          "score": 4.2,
          "roundedScore": 4,
          "totalReviews": 4504
        },
        {
          "id": "image",
          "score": 4.5,
          "roundedScore": 4.5,
          "totalReviews": 4473
        },
        {
          "id": "career",
          "score": 4.2,
          "roundedScore": 4,
          "totalReviews": 4478
        }
      ]
    },
    {
      "id": "AP_CATEGORY_CULTURE",
      "score": 4.3,
      "roundedScore": 4.5,
      "totalReviews": 4540,
      "factors": [
        {
          "id": "atmosphere",
          "score": 4.4,
          "roundedScore": 4.5,
          "totalReviews": 4540
        },
        {
          "id": "communication",
          "score": 4.1,
          "roundedScore": 4,
          "totalReviews": 4506
        },
        {
          "id": "teamwork",
          "score": 4.5,
          "roundedScore": 4.5,
          "totalReviews": 4517
        },
        {
          "id": "workLife",
          "score": 4.1,
          "roundedScore": 4,
          "totalReviews": 4505
        },
        {
          "id": "leadership",
          "score": 4.3,
          "roundedScore": 4.5,
          "totalReviews": 4514
        },
        {
          "id": "tasks",
          "score": 4.4,
          "roundedScore": 4.5,
          "totalReviews": 4496
        }
      ]
    },
    {
      "id": "AP_CATEGORY_WORK_ENVIRONMENT",
      "score": 4.5,
      "roundedScore": 4.5,
      "totalReviews": 4494,
      "factors": [
        {
          "id": "workConditions",
          "score": 4.5,
          "roundedScore": 4.5,
          "totalReviews": 4494
        },
        {
          "id": "environment",
          "score": 4.5,
          "roundedScore": 4.5,
          "totalReviews": 4449
        }
      ]
    },
    {
      "id": "AP_CATEGORY_DIVERSITY",
      "score": 4.4,
      "roundedScore": 4.5,
      "totalReviews": 4455,
      "factors": [
        {
          "id": "equality",
          "score": 4.5,
          "roundedScore": 4.5,
          "totalReviews": 4455
        },
        {
          "id": "oldColleagues",
          "score": 4.4,
          "roundedScore": 4.5,
          "totalReviews": 4397
        }
      ]
    }
  ],
  "benefits": [
    {
      "id": "flexWorkingHours",
      "total": 3805,
      "percentage": 83
    },
    {
      "id": "homeOffice",
      "total": 3639,
      "percentage": 79
    },
    {
      "id": "internet",
      "total": 3378,
      "percentage": 74
    },
    {
      "id": "cantine",
      "total": 3325,
      "percentage": 72
    },
    {
      "id": "pensionPlan",
      "total": 3290,
      "percentage": 72
    },
    {
      "id": "car",
      "total": 3278,
      "percentage": 71
    },
    {
      "id": "events",
      "total": 3277,
      "percentage": 71
    },
    {
      "id": "parking",
      "total": 3265,
      "percentage": 71
    },
    {
      "id": "meals",
      "total": 3227,
      "percentage": 70
    },
    {
      "id": "mobilePhone",
      "total": 3192,
      "percentage": 70
    },
    {
      "id": "healthProgram",
      "total": 3114,
      "percentage": 68
    },
    {
      "id": "stockOptions",
      "total": 3060,
      "percentage": 67
    },
    {
      "id": "coaching",
      "total": 2948,
      "percentage": 64
    },
    {
      "id": "discounts",
      "total": 2922,
      "percentage": 64
    },
    {
      "id": "doctor",
      "total": 2816,
      "percentage": 61
    },
    {
      "id": "accessibility",
      "total": 2597,
      "percentage": 57
    },
    {
      "id": "reachability",
      "total": 2420,
      "percentage": 53
    },
    {
      "id": "daycare",
      "total": 2105,
      "percentage": 46
    },
    {
      "id": "dogs",
      "total": 268,
      "percentage": 6
    }
  ],
  "salaryRanges": [
    {
      "jobRoleTitleId": 15019,
      "jobRoleTitle": "Softwareentwickler:in",
      "jobRoleTitleSlug": "softwareentwickler-in",
      "profileRangeMin": 43500,
      "profileRangeMax": 109400,
      "profileMedian": 70000,
      "profileAverage": 71500,
      "profileNumberOfEntries": 415
    },
    {
      "jobRoleTitleId": 19397,
      "jobRoleTitle": "Werkstudent:in",
      "jobRoleTitleSlug": "werkstudent-in",
      "profileRangeMin": 22100,
      "profileRangeMax": 48800,
      "profileMedian": 26400,
      "profileAverage": 27800,
      "profileNumberOfEntries": 180
    },
    {
      "jobRoleTitleId": 17844,
      "jobRoleTitle": "SAP-Berater:in",
      "jobRoleTitleSlug": "sap-berater-in",
      "profileRangeMin": 46800,
      "profileRangeMax": 123600,
      "profileMedian": 75000,
      "profileAverage": 78600,
      "profileNumberOfEntries": 148
    }
  ],
  "competitors": [
    {
      "slug": "efficon1",
      "name": "EffiCon GmbH & Co. KG",
      "uuid": "e7b4578a-ba31-4262-91cd-6ceabefa83a6",
      "countryCode": "de",
      "score": 4.8,
      "roundedScore": 5,
      "industryId": 35
    },
    {
      "slug": "realtech",
      "name": "REALTECH AG",
      "uuid": "f6c1ef8a-f704-47f4-84ab-e5a4e03a7369",
      "countryCode": "de",
      "score": 3.3,
      "roundedScore": 3.5,
      "industryId": 6
    },
    {
      "slug": "mindsquare",
      "name": "mindsquare AG",
      "uuid": "fe884cb0-9d8b-4f33-93b0-461cbb49dab6",
      "countryCode": "de",
      "score": 4.4,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "consenso-consulting",
      "name": "consenso Consulting GmbH",
      "uuid": "e923ce89-e193-4f01-aadd-fb4b29d6e317",
      "countryCode": "de",
      "score": 4.2,
      "roundedScore": 4,
      "industryId": 3
    },
    {
      "slug": "dataport",
      "name": "Dataport AöR",
      "uuid": "78f4a217-1b2e-43e4-91c8-8a33be3c7495",
      "countryCode": "de",
      "score": 4.2,
      "roundedScore": 4,
      "industryId": 6
    },
    {
      "slug": "smk-versicherungsmakler2",
      "name": "SMK Versicherungsmakler AG",
      "uuid": "54255dd3-51a3-491d-b83d-2463276fb5a7",
      "countryCode": "de",
      "score": 4.3,
      "roundedScore": 4.5,
      "industryId": 37
    },
    {
      "slug": "solvin-information-management1",
      "name": "SOLVIN information management GmbH",
      "uuid": "28f8f60e-66d3-4896-b434-6ba347a69959",
      "countryCode": "de",
      "score": 3.7,
      "roundedScore": 3.5,
      "industryId": 3
    },
    {
      "slug": "kuehne-nagel-ag",
      "name": "Kühne + Nagel",
      "uuid": "3363911b-ee74-4b6e-b46f-94438884af58",
      "countryCode": "de",
      "score": 3.3,
      "roundedScore": 3.5,
      "industryId": 28
    },
    {
      "slug": "grayoak-management-technology-consulting1",
      "name": "GRAYOAK Management & Technology Consulting GmbH",
      "uuid": "faa48bdd-10c5-4e1a-98bf-e8c26977a46c",
      "countryCode": "de",
      "score": 4.9,
      "roundedScore": 5,
      "industryId": 3
    },
    {
      "slug": "adexpartners",
      "name": "AdEx Beratungs GmbH",
      "uuid": "c92b0ac4-3e6a-43c8-940f-a2d45ff4c693",
      "countryCode": "de",
      "score": 4.7,
      "roundedScore": 4.5,
      "industryId": 3
    },
    {
      "slug": "soft-consult-haege",
      "name": "SOFT-CONSULT Häge GmbH",
      "uuid": "28c14089-58d6-4a33-9c60-e03bc074593c",
      "countryCode": "de",
      "score": 4.4,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "amperecloud",
      "name": "Amperecloud GmbH",
      "uuid": "0d85976a-fcb4-41a5-994a-88008e324891",
      "countryCode": "de",
      "score": 4.3,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "enmore-consulting",
      "name": "enmore consulting ag",
      "uuid": "d808300f-e88b-444b-b2ae-22a89e30ee02",
      "countryCode": "de",
      "score": 3.8,
      "roundedScore": 4,
      "industryId": 6
    },
    {
      "slug": "team7",
      "name": "TEAM GmbH",
      "uuid": "db75232c-bcf8-41ca-8ef7-cf7714d808af",
      "countryCode": "de",
      "score": 4.4,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "cosys-ident",
      "name": "Cosys Ident GmbH",
      "uuid": "10ecffe8-0e85-4230-8c24-4266028e4dab",
      "countryCode": "de",
      "score": 3.1,
      "roundedScore": 3,
      "industryId": 6
    },
    {
      "slug": "rechenzentrum-hartmann1",
      "name": "Rechenzentrum Hartmann GmbH & Co. K.G.",
      "uuid": "80df0e86-508d-4add-b534-4f7b24727ff1",
      "countryCode": "de",
      "score": 4.6,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "seclous4",
      "name": "SECLOUS GmbH",
      "uuid": "ab907d5b-ed9c-441a-a120-22eba256ab2c",
      "countryCode": "de",
      "score": 4.1,
      "roundedScore": 4,
      "industryId": 6
    },
    {
      "slug": "qunis2",
      "name": "QUNIS GmbH",
      "uuid": "17e67b71-8ca8-447a-bd6c-6c9c72be5265",
      "countryCode": "de",
      "score": 4.7,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "assystem5",
      "name": "AS-SYSTEME",
      "uuid": "794ca459-b60d-4da0-9c39-bb96f7bb5929",
      "countryCode": "de",
      "score": 4.3,
      "roundedScore": 4.5,
      "industryId": 6
    },
    {
      "slug": "preyer2",
      "name": "Preyer GmbH",
      "uuid": "e0367635-5111-4bb1-8212-04a1ab9d4660",
      "countryCode": "de",
      "score": 4.4,
      "roundedScore": 4.5,
      "industryId": 6
    }
  ],
  "topCompanyYears": [
    2026,
    2025,
    2024,
    2023,
    2022
  ],
  "salarySatisfaction": {
    "score": null,
    "roundedScore": null,
    "percentage": null,
    "totalReviews": 4504
  },
  "kulturKompass": null,
  "searchQuery": "",
  "scrapedAt": "2026-04-17T13:35:15.195Z",
  "contentHash": "11c59cbd1d9c98043722282c3c86f600c81679955700eb793d30e5e98fdcbe46",
  "changeType": "NEW"
}

Incremental fields

When incremental: true, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.

How to scrape kununu.com

1. Go to Kununu Scraper in Apify Console.
2. Enter a search keyword.
3. Set maxResults to control how many results you need.
4. Enable includeDetails if you need full descriptions, contact info, or company data.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract listing data from kununu.com for market research and competitive analysis.
• Track salary trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Research company hiring patterns, employer profiles, and industry distribution.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.
• Collect ratings and reviews for reputation monitoring and benchmarking.

How much does it cost to scrape kununu.com?

Kununu Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.005 per run
• Per result: $0.001 per listing record

Example costs:

• 10 results: $0.01
• 100 results: $0.11
• 500 results: $0.51

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Numbers below are for the primary Company profile event. Other events (Review extracted) are billed separately when they fire and follow the same incremental logic — when the underlying record has not changed, no charge is emitted.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.26	$0.02	$0.24 (93%)	$0.53
15% — moderate broad query	$0.26	$0.04	$0.21 (83%)	$1.27
30% — high-volume aggregator	$0.26	$0.08	$0.17 (69%)	$2.40

Full re-scrape monthly cost at daily polling: $7.65. First month with incremental costs $0.76 / $1.49 / $2.57 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same.

FAQ

How many results can I get from kununu.com?

The number of results depends on the search query and available listings on kununu.com. Use the maxResults parameter to control how many results are returned per run.

Does Kununu Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Kununu Scraper with other apps?

Yes. Kununu Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Kununu Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Kununu Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape kununu.com?

This actor extracts publicly available data from kununu.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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