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Krak.dk Business Scraper: Extract Danish Business Data for Lead Generation & Market Research

Introduction

Krak.dk stands as Denmark's premier online business directory, serving as a comprehensive resource for locating companies, contact information, and business services throughout Denmark. As one of the country's most trusted and widely-used business directories, Krak.dk maintains millions of business listings with detailed information including company names, phone numbers, addresses, organization numbers, and service categories.

For businesses engaged in B2B sales, market research, or competitive analysis in the Danish market, accessing this structured business data is invaluable. However, manually collecting business information from Krak.dk is extremely time-consuming and inefficient, especially when dealing with large-scale research projects requiring hundreds or thousands of business records.

The Krak.dk Business Scraper solves this challenge by automating the data extraction process. Whether you're building a lead database for Danish market entry, analyzing competitor presence in specific regions, or conducting comprehensive market research across multiple business categories, this scraper enables systematic data collection that would otherwise require countless hours of manual effort.

Scraper Overview

The Krak.dk Business Scraper is a sophisticated data extraction tool designed to systematically collect business information from Denmark's leading business directory platform. This scraper leverages advanced web automation techniques to navigate through search results and extract detailed business profiles efficiently and reliably.

The tool offers several key advantages including residential proxy support for reliable data collection, configurable retry mechanisms for handling network issues, and flexible extraction controls through both URL-based and filter-based search methods. It's particularly valuable for international companies entering the Danish market, B2B sales professionals targeting Danish businesses, market researchers analyzing Danish industry landscapes, and competitive intelligence analysts tracking business presence across Denmark.

The scraper is designed to handle various search parameters and can process multiple business listing pages simultaneously. It maintains high data accuracy while respecting rate limits and implementing best practices for ethical web scraping. Users can customize extraction parameters to focus on specific business types, geographic regions, or other criteria relevant to their research objectives.

Input and Output Details

Example url 1: https://www.krak.dk/a/firmaer

Example url 2: https://www.krak.dk/res/firmaer

Example url 3: https://www.krak.dk/account/firmaer

Example Screenshot of bussiness list by query page:

Input Format

The scraper accepts a JSON configuration that allows precise control over the data extraction process. The input structure includes several critical parameters that determine how the scraping operation will be executed.

Scrape with URLs:

{
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "DK"
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [
    "https://www.krak.dk/a/firmaer",
    "https://www.krak.dk/res/firmaer",
    "https://www.krak.dk/account/firmaer"
  ]
}

The urls parameter: Add the URLs of the business list pages you want to scrape from Krak.dk. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. This is ideal when you have specific search result pages you want to extract. Navigate to Krak.dk, perform your desired search using their filters, then copy the resulting URL.

The ignore_url_failures parameter: If set to true, the scraper will continue running even if some URLs fail to be scraped after the maximum number of retries is reached. This ensures that one problematic URL doesn't stop your entire scraping job, which is crucial for large-scale data collection projects.

When you provide a list of URLs for scraping, all options in the "Scrape with search filters" section will be disabled. The system will only collect data from the URLs you specified.

Scrape with Search Filters:

{
  "keyword": "restauranter",
  "page": 1,
  "max_items_per_url": 20,
  "max_retries_per_url": 2,
  "proxy": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "DK"
  }
}

The keyword parameter: Enter the search keyword to find businesses. Use Danish-language terms that match common business categories (e.g., "restauranter", "advokater", "tandlæger", "frisører", "ejendomsmæglere"). This allows you to automatically search for specific business types without manually constructing URLs.

The page parameter: Enter the page number to scrape from search results. This enables systematic pagination through search results, allowing you to start from any page position and extract data progressively.

When using search filters for scraping, you need to leave the urls field empty in the "Scrape with URLs" configuration.

General Options:

The max_items_per_url parameter: Limit the number of items per URL or search filters you want to scrape. The default value is 20, providing a manageable batch size while allowing for comprehensive data collection. Adjust this based on your specific needs and available resources.

The max_retries_per_url parameter: Limit the number of retries for each URL or search filters if the scrape is detected as a bot or the page fails to load. The default value is 2, providing a good balance between thoroughness and efficiency.

The proxy parameter: Proxy configuration is essential for maintaining anonymity and avoiding detection. Select proxies to be used by your scraper. For best results with Krak.dk, consider using Danish residential proxies (apifyProxyCountry: "DK") to ensure optimal access and reduce the likelihood of being blocked.

Output Format

Example output

[
  {
  "eniro_id": "304009910",
  "name": "Berlin Re Investments Fmba",
  "phones": [
    {
      "number": "22 70 55 05",
      "text": null
    }
  ],
  "addresses": [
    {
      "street_name": "Bloksbjerget",
      "street_number": "17",
      "postal_code": "2930",
      "postal_area": "Klampenborg",
      "municipality": "Gentofte",
      "region": "Hovedstaden",
      "province": "Sjælland",
      "urban_area": null,
      "borough": null,
      "neighborhood": null,
      "community": null,
      "metropolitan_subarea": null,
      "coordinates": [
        {
          "lon": 12.5798559,
          "lat": 55.771286,
          "type": "map"
        },
        {
          "lon": 12.5798559,
          "lat": 55.771286,
          "type": "route"
        }
      ],
      "co_name": null,
      "place_name": null,
      "house_name": "Mads Walin"
    }
  ],
  "organisation_number": "46086775",
  "customer_number": "ECO304009910",
  "categories": [
    {
      "name": "Fast ejendom",
      "code": "568000"
    }
  ],
  "districts": [],
  "products": [
    {
      "name": "email",
      "link": "madsboegh@gmail.com"
    },
    {
      "name": "financial_data",
      "orgnr": "46086775",
      "company_name": "Berlin Re Investments Fmba"
    },
    {
      "name": "customer_icon",
      "link_text": "Reklamebeskyttet",
      "image": "https://images.eniro.com/dk/ip_images/common/adds_protection.gif",
      "url": "https://datacvr.virk.dk/data/cvr-hj%C3%A6lp/f%C3%A5-hj%C3%A6lp-til-cvr/reklamebeskyttelse"
    }
  ],
  "customers_nearby": [],
  "keywords": [],
  "customer": false,
  "ranking": 0,
  "bought_district": false,
  "statistic_code": "AB",
  "hit_type": "popularName",
  "tracestamps": {
    "cluster_write": "2025-12-10T01:02:01.579236997Z"
  },
  "from_url": "https://www.krak.dk/res/firmaer/2"
}
]

The scraper returns structured business data with each field serving specific purposes for business intelligence and lead generation:

• Eniro ID: Unique business identifier within the Krak.dk/Eniro system. Critical for database management, duplicate detection, and tracking businesses over time in your CRM.

• Name: Official business name as registered in the directory. Essential for lead identification, outreach personalization, and accurate record-keeping.

• Phones: Business phone numbers including landlines and mobile numbers. Primary contact channel for direct sales outreach, phone-based lead qualification, and immediate business communication.

• Addresses: Physical business location addresses. Essential for geographic targeting, local market analysis, territory planning, and field sales routing. Enables location-based segmentation.

• Organisation Number: Danish CVR (Central Business Register) number. Official business registration identifier used for verification, company research, financial analysis, and legal due diligence.

• Customer Number: Internal Krak.dk customer identifier. Useful for tracking premium listings and identifying businesses with enhanced directory presence.

• Categories: Business category or industry classifications. Critical for market segmentation, competitive analysis, and filtering relevant prospects by industry vertical or service type.

• Districts: Geographic districts or regions where the business operates. Enables regional market analysis, territory planning, and understanding of service coverage areas.

• Products: Products or services offered by the business. Provides detailed insight into business offerings, helps with lead qualification, and enables product-based targeting strategies.

• Customers Nearby: Related or nearby customer information. Useful for understanding business clusters, identifying industry concentrations, and analyzing competitive landscapes in specific areas.

• Keywords: Search keywords associated with the business listing. Reveals how businesses position themselves, helps understand market terminology, and assists with SEO and competitive keyword analysis.

• Customer: Customer status or type indicator. Identifies premium vs. basic listings, suggesting business investment in marketing and potential purchasing power.

• Ranking: Business ranking or prominence score within Krak.dk. Indicates visibility and potential market leadership, useful for prioritizing high-profile prospects.

• Bought District: Districts where the business has purchased enhanced visibility. Shows businesses investing in local marketing, suggesting growth orientation and budget availability.

• Statistic Code: Statistical classification code for the business. Enables industry-standard categorization and integration with official Danish business statistics.

• Hit Type: Type of search result or listing. Helps distinguish between different listing types and quality levels.

• Tracestamps: Temporal data about listing updates or interactions. Useful for tracking when businesses update their information, indicating active management and engagement.

Each field serves specific purposes in lead generation workflows, market research analysis, competitive intelligence gathering, and business development strategies targeting the Danish market.

Usage Guide

Option 1: Scraping with URLs

To effectively use the Krak.dk scraper with URLs, start by constructing targeted search URLs on the Krak.dk platform. Navigate to the website, perform your desired search using filters for industry, location, and other parameters, then copy the resulting URL into the urls array in your input configuration.

Configure your JSON input with appropriate retry limits and proxy settings. Set reasonable limits for max_items_per_url to balance data collection speed with system stability. Enable ignore_url_failures to ensure one problematic URL doesn't stop your entire scraping job—this is especially important when scraping multiple different search result pages.

Best practices for URL-based scraping:

• Test URLs individually before batch processing to ensure they work correctly
• Monitor extraction progress for any blocked requests
• Implement delays between large extraction batches to avoid rate limiting
• Use Danish residential proxies for optimal access and performance
• Keep a backup list of working URLs as page structures may change

Common troubleshooting steps:

• Adjust proxy settings if encountering access restrictions
• Reduce retry counts if experiencing timeout issues
• Verify URL formats match current Krak.dk structure
• Check for URL parameter changes that may affect scraping

Option 2: Scraping with Search Filters

Setting Up Search Criteria

Instead of manually creating URLs, use search filters to automatically generate business searches. This method is ideal for systematic business data collection across specific categories or industries.

Step 1: Define Search Keyword

Enter a keyword parameter using Danish-language business terms:

• Professional services: "advokater" (lawyers), "revisorer" (accountants), "arkitekter" (architects), "ingeniører" (engineers)
• Restaurants & food: "restauranter" (restaurants), "caféer" (cafes), "bagerier" (bakeries), "pizzeriaer" (pizzerias)
• Retail: "butikker" (shops), "supermarkeder" (supermarkets), "apoteker" (pharmacies), "tøjbutikker" (clothing stores)
• Healthcare: "læger" (doctors), "tandlæger" (dentists), "klinikker" (clinics), "fysioterapeuter" (physiotherapists)
• Services: "frisører" (hairdressers), "ejendomsmæglere" (real estate agents), "forsikringsselskaber" (insurance companies)

Step 2: Configure Pagination

Use the page parameter to control result pagination:

• Set to 1 to start from the beginning
• Use incremental pages (2, 3, 4) for systematic data collection
• Resume interrupted scrapes by setting page to last collected position
• Plan page intervals based on max_items_per_url setting

Step 3: Set Extraction Limits

Configure max_items_per_url based on your needs:

• Start with 20 items for testing
• Increase for production runs requiring comprehensive data
• Balance between data volume and processing time

Best Practices for Filter-Based Scraping

Keyword Selection:

• Use Danish-language terms exactly as they appear on Krak.dk
• Test keywords on the actual website before scraping to ensure they return results
• Consider variations in terminology (e.g., "læge" vs "læger")
• Start with broader categories before narrowing to specific niches

Pagination Strategy:

• Track page numbers to avoid gaps in data collection
• Adjust max_items_per_url based on total results available
• Handle end-of-results gracefully when pages exceed available data
• Use consistent page increments for systematic coverage

Data Validation:

• Verify that extracted businesses match the search keyword
• Check for duplicate businesses across different pages
• Ensure all Danish-language content is properly encoded
• Cross-reference sample outputs with actual Krak.dk listings

Common Issue Resolution

Keyword Matching Problems:

• Verify Danish spelling is correct (including special characters like æ, ø, å)
• Test keywords directly on Krak.dk first
• Try alternative terms if initial searches return no results
• Consider broader categories before narrowing

Pagination Issues:

• Track page values to avoid skipping results
• Handle end-of-results when page exceeds available data
• Adjust retry settings for pages that fail to load
• Monitor for changes in results per page

Advanced Techniques:

Industry-Specific Research:

• Create keyword lists for each target industry
• Run parallel scrapes for different business categories
• Compare business presence across different sectors
• Build comprehensive industry databases

Systematic Coverage Strategy:

• Plan extraction schedules for regular data updates
• Rotate through different business categories
• Track progress across different keywords and pages
• Build complete Danish business databases for market intelligence

Proxy Configuration Best Practices

Danish Proxy Advantages:

• Use Danish residential proxies for best results (apifyProxyCountry: "DK")
• Higher success rates with local proxy addresses
• Better detection avoidance for Danish platforms
• More reliable access during high-volume scraping

Residential Proxy Benefits:

• Essential for large-scale data collection
• Reduces likelihood of being blocked
• Provides stable connections for extended scraping sessions

Benefits and Applications

The Krak.dk Business Scraper delivers significant time savings compared to manual data collection. What would traditionally require days or weeks of manual research is reduced to hours of automated extraction, enabling businesses to focus on analysis and strategic action rather than data gathering.

Primary Applications:

Lead Generation for Danish Market Entry: Sales teams can build comprehensive prospect databases of Danish businesses with complete contact information including phone numbers, addresses, and organization numbers for verification and outreach.

Market Research and Analysis: Conduct systematic analysis of Danish business landscapes, assess market size and business density by industry and location, identify market gaps and opportunities, and understand competitive dynamics through comprehensive data collection.

Competitive Intelligence: Track competitor presence across different regions and categories, analyze business positioning and service offerings, identify market leaders through ranking data, and monitor changes in competitive landscape over time.

Industry-Specific Database Building: Create targeted databases for specific sectors using keyword-based searches, segment businesses by category and location, maintain updated contact information for ongoing campaigns, and identify businesses with premium listings indicating higher budget availability.

B2B Database Building: Create enriched business contact databases for ongoing sales and marketing campaigns, segment prospects by industry, location, and business characteristics, maintain updated business information with organization numbers for verification, and integrate with CRM systems for immediate activation.

The scraper provides competitive advantages through:

• Dual extraction methods (URLs and search filters) for maximum flexibility
• Access to Denmark's most comprehensive business directory in structured format
• Official organization numbers (CVR) enabling business verification and research
• Detailed categorization and product information for precise targeting
• Pagination controls for systematic coverage of large datasets
• Automated keyword-based searches eliminating manual URL construction

The structured output integrates seamlessly with CRM systems, marketing automation platforms, and business intelligence tools, enabling immediate activation of collected data for sales outreach, market analysis, and strategic planning in the Danish market.

Conclusion

The Krak.dk Business Scraper transforms time-consuming manual research into efficient automated data collection. By providing structured access to Denmark's leading business directory through both URL-based and filter-based extraction methods, it empowers businesses to make data-driven decisions about Danish market entry, expansion, and competitive positioning.

Whether you're building lead lists for B2B sales campaigns, conducting comprehensive market research using keyword searches, or analyzing competitive landscapes across Danish industries, this scraper provides the systematic data extraction capabilities needed to accelerate your business intelligence gathering.

Ready to streamline your Danish business data collection? Start extracting valuable insights from Krak.dk today and transform your market research and lead generation capabilities.

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