{"product_id":"denmark-ok-ev","title":"OK EV Charging Station Locations Dataset – Denmark","description":"\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\/\",\n  \"@type\": \"Dataset\",\n  \"name\": \"OK EV Charging Station Locations Dataset – Denmark\",\n  \"description\": \"Download a geocoded dataset containing 921 OK ev charging station locations across Denmark. Includes addresses, administrative areas, and WGS84 latitude\/longitude coordinates in CSV format for GIS, market research, logistics, site selection, and location intelligence applications. Updated: 15 July 2026.\",\n  \"url\": \"https:\/\/geolocet.com\/products\/denmark-ok-ev\",\n  \"isAccessibleForFree\": false,\n  \"creator\": {\n    \"@type\": \"Organization\",\n    \"sameAs\": \"https:\/\/geolocet.com\",\n    \"name\": \"Geolocet\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Geolocet\",\n    \"sameAs\": \"https:\/\/geolocet.com\",\n    \"url\": \"https:\/\/geolocet.com\"\n  },\n  \"dateModified\": \"2026-07-15\",\n  \"lastVerified\": \"2026-07-15\",\n  \"spatialCoverage\": {\n    \"@type\": \"Place\",\n    \"name\": \"Denmark\"\n  },\n  \"size\": \"921 locations\",\n  \"measurementTechnique\": \"Web scraping, geocoding, validation, and standardization\",\n  \"license\": \"https:\/\/geolocet.com\/pages\/terms-of-use\",\n  \"distribution\": {\n    \"@type\": \"DataDownload\",\n    \"encodingFormat\": \"text\/csv\"\n  },\n  \"hasPart\": {\n    \"@type\": \"Dataset\",\n    \"name\": \"Free Sample: OK EV Charging Stations Locations Dataset – Denmark\",\n    \"description\": \"A subset of the full dataset demonstrating data structure, geospatial precision, and column headers.\",\n    \"isAccessibleForFree\": true,\n    \"distribution\": {\n      \"@type\": \"DataDownload\",\n      \"encodingFormat\": \"text\/csv\",\n      \"contentUrl\": \"https:\/\/geolocet.com\/products\/denmark-ok-ev\"\n    }\n  },\n  \"variableMeasured\": [\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"GUID\",\n      \"description\": \"Unique global identifier for the location record.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Title\",\n      \"description\": \"The official name, brand, or title of the store\/location.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Latitude\",\n      \"description\": \"Precise WGS84 latitude coordinate.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Longitude\",\n      \"description\": \"Precise WGS84 longitude coordinate.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Street No\",\n      \"description\": \"The specific building or street number.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Street\",\n      \"description\": \"The street name where the location is situated, excluding the building number.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"City\",\n      \"description\": \"City, municipality, or primary settlement area.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Kommune\",\n      \"description\": \"Specific data attribute detailing the kommune of the location.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Region\",\n      \"description\": \"Macro-administrative boundary, such as a large geographic region, state, or province.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Population\",\n      \"description\": \"Specific data attribute detailing the population of the location.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Postal Code\",\n      \"description\": \"Zip code or postal routing code for the region.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Address\",\n      \"description\": \"Full, standardized street address of the location.\"\n    }\n  ],\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"price\": \"72.00\",\n    \"priceCurrency\": \"EUR\",\n    \"seller\": {\n      \"@type\": \"Organization\",\n      \"sameAs\": \"https:\/\/geolocet.com\",\n      \"name\": \"Geolocet\"\n    },\n    \"description\": \"Full dataset. Digital product for instant download. No shipping required.\"\n  },\n  \"keywords\": [\n    \"OK\",\n    \"Denmark\",\n    \"EV Charging Stations\",\n    \"geospatial data\",\n    \"location data\",\n    \"spatial retail analytics\",\n    \"retail site selection\",\n    \"forecourt geospatial dataset\",\n    \"GIS-ready retail location data\",\n    \"geocoded retail locations\"\n  ],\n  \"alternateName\": [\n    \"OK Denmark geospatial dataset\",\n    \"OK EV Charging Station locations Denmark\",\n    \"Geocoded OK locations - Denmark CSV\",\n    \"OK EV Charging Station Denmark address list\"\n  ],\n  \"temporalCoverage\": \"2026-07-15\",\n  \"mentions\": {\n    \"@type\": \"Organization\",\n    \"name\": \"OK\",\n    \"url\": \"https:\/\/www.ok.dk\",\n    \"alternateName\": \"OK a.m.b.a.\"\n  }\n}\n\u003c\/script\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"BreadcrumbList\",\n  \"itemListElement\": [\n    {\n      \"@type\": \"ListItem\",\n      \"position\": 1,\n      \"name\": \"Home\",\n      \"item\": \"https:\/\/geolocet.com\"\n    },\n    {\n      \"@type\": \"ListItem\",\n      \"position\": 2,\n      \"name\": \"Brands Locations\",\n      \"item\": \"https:\/\/geolocet.com\/collections\/brands-locations\"\n    },\n    {\n      \"@type\": \"ListItem\",\n      \"position\": 3,\n      \"name\": \"Denmark\",\n      \"item\": \"https:\/\/geolocet.com\/pages\/denmark\"\n    },\n    {\n      \"@type\": \"ListItem\",\n      \"position\": 4,\n      \"name\": \"OK EV Charging Stations Dataset\",\n      \"item\": \"https:\/\/geolocet.com\/products\/denmark-ok-ev\"\n    }\n  ]\n}\n\u003c\/script\u003e\n\u003cnav aria-label=\"Page sections\" style=\"background:#f8f9fa; border:1px solid #ddd; border-radius:4px; padding:10px 14px; margin-bottom:18px;\"\u003e\u003cstrong style=\"font-size:0.85em; margin-right:10px;\"\u003eQuick links:\u003c\/strong\u003e\u003cul style=\"display:inline; list-style:none; margin:0; padding:0;\"\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#dataset-summary\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eDataset Summary\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#methodology\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eMethodology\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#download\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eDownload\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#regional-distribution\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eRegional Distribution\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#brand-bundle\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eBrand Bundle\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#related-datasets\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eRelated Datasets\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#use-cases\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eUse Cases\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#faq\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eFAQ\u003c\/a\u003e\u003c\/li\u003e\n\u003cli style=\"display:inline; margin-right:12px;\"\u003e\u003ca href=\"#ai-prompts\" style=\"font-size:0.85em; color:#2c6fad; text-decoration:none;\"\u003eAnalyze with AI\u003c\/a\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003c\/nav\u003e\u003cp\u003e OK a.m.b.a. is a Danish consumer-owned cooperative that sells fuel, heating oil and other energy products through filling stations across Denmark. It has expanded into EV charging, installing fast and ultra-fast chargers at many of its stations alongside roaming access to partner networks via its app.\u003c\/p\u003e\u003cp\u003eThere are \u003cstrong\u003e921 OK EV Charging Stations\u003c\/strong\u003e as of \u003cstrong\u003e15 July 2026\u003c\/strong\u003e in Denmark. This dataset is compiled and maintained by \u003ca href=\"https:\/\/geolocet.com\" rel=\"noopener noreferrer\"\u003eGeolocet\u003c\/a\u003e and provides a complete, geocoded list of all OK locations, including full address details, administrative divisions, and precise WGS84 latitude\/longitude coordinates - structured for GIS, retail analytics, mapping, and AI\/RAG workflows.\u003c\/p\u003e\n        \u003cdiv class=\"dataset-summary\"\u003e\n            \u003ch2 id=\"dataset-summary\"\u003eDataset Summary\u003c\/h2\u003e\n            \u003cul\u003e\n            \u003cli\u003e\n\u003cstrong\u003eDataset Coverage:\u003c\/strong\u003e 921 OK ev charging stations in Denmark\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eContents:\u003c\/strong\u003e Coordinates, addresses, postal codes, and administrative divisions\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eFile Format:\u003c\/strong\u003e Fully geocoded CSV dataset (UTF-8)\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eFree Sample:\u003c\/strong\u003e Instantly accessible dataset to verify structure and data quality\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eUse Cases:\u003c\/strong\u003e Suitable for GIS, retail analytics, site selection, and AI\/RAG workflows\u003c\/li\u003e\n            \u003cli\u003e\n\u003cstrong\u003eLast Updated:\u003c\/strong\u003e 15 July 2026\u003c\/li\u003e\n        \u003c\/ul\u003e\n    \u003c\/div\u003e\n    \u003ch2 id=\"methodology\"\u003eDataset Methodology:\u003c\/h2\u003e\u003cp\u003e This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.\u003c\/p\u003e\u003cp\u003eIt is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.\u003c\/p\u003e\u003cdiv style=\"overflow: auto;\"\u003e\n\u003cdiv style=\"float: right; margin: 0 0 15px 20px; width: 45%; max-width: 560px;\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0727\/3853\/7806\/files\/Denmark_OK_EV_Charging_Stations_Locations_Map.png\" alt=\"Map showing the geographical distribution of OK locations in Denmark\" style=\"width: 100%; height: 100%; object-fit: contain;\"\u003e\u003c\/div\u003e\n\u003ch3\u003eDataset fields included in the CSV:\u003c\/h3\u003e\n\u003cul style=\"columns: 150px 2; margin-left: 20px;\"\u003e\n\u003cli\u003eGUID\u003c\/li\u003e\n\u003cli\u003eTitle\u003c\/li\u003e\n\u003cli\u003eLatitude\u003c\/li\u003e\n\u003cli\u003eLongitude\u003c\/li\u003e\n\u003cli\u003eStreet No\u003c\/li\u003e\n\u003cli\u003eStreet\u003c\/li\u003e\n\u003cli\u003eCity\u003c\/li\u003e\n\u003cli\u003eKommune\u003c\/li\u003e\n\u003cli\u003eRegion\u003c\/li\u003e\n\u003cli\u003ePopulation\u003c\/li\u003e\n\u003cli\u003ePostal Code\u003c\/li\u003e\n\u003cli\u003eAddress\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp style=\"margin-top: 15px;\"\u003e\u003cem\u003eRequire additional attributes such as charging points, charger types, or charging speed? \u003ca href=\"\/pages\/contact-us\"\u003eContact us\u003c\/a\u003e to request a custom data enrichment.\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003ch2\u003eData Preview: Sample geospatial records from the OK dataset in Denmark\u003c\/h2\u003e\n\u003ctable class=\"data-preview-table\" aria-describedby=\"table-note\"\u003e\n\u003cthead\u003e\u003ctr\u003e\n\u003cth scope=\"col\"\u003eID\u003c\/th\u003e\n\u003cth scope=\"col\"\u003eLocation Title\u003c\/th\u003e\n\u003cth scope=\"col\"\u003eLatitude\u003c\/th\u003e\n\u003cth scope=\"col\"\u003eLongitude\u003c\/th\u003e\n\u003cth scope=\"col\"\u003ePostal Code\u003c\/th\u003e\n\u003cth scope=\"col\"\u003eFull Address\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e0835b41...\u003c\/td\u003e\n\u003ctd\u003eOK (Skive)\u003c\/td\u003e\n\u003ctd\u003e56.644796\u003c\/td\u003e\n\u003ctd\u003e8.983926\u003c\/td\u003e\n\u003ctd\u003e7800\u003c\/td\u003e\n\u003ctd\u003e26 Kåstrupvej, Skive, 7800, Denmark\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e6bbef4c...\u003c\/td\u003e\n\u003ctd\u003eOK (Støvring)\u003c\/td\u003e\n\u003ctd\u003e56.879065\u003c\/td\u003e\n\u003ctd\u003e9.807586\u003c\/td\u003e\n\u003ctd\u003e9530\u003c\/td\u003e\n\u003ctd\u003e30 Juelstrupparken, Støvring, 9530, D...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eb06144c...\u003c\/td\u003e\n\u003ctd\u003eOK (Nykøbing Falster)\u003c\/td\u003e\n\u003ctd\u003e54.764039\u003c\/td\u003e\n\u003ctd\u003e11.873088\u003c\/td\u003e\n\u003ctd\u003e4800\u003c\/td\u003e\n\u003ctd\u003e4 Højbrogade, Nykøbing Falster, 4800,...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003edc92e2a...\u003c\/td\u003e\n\u003ctd\u003eOK (Ikast)\u003c\/td\u003e\n\u003ctd\u003e56.148683\u003c\/td\u003e\n\u003ctd\u003e9.138946\u003c\/td\u003e\n\u003ctd\u003e7430\u003c\/td\u003e\n\u003ctd\u003e31 Hagelskærvej, Ikast, 7430, Denmark\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e230a672...\u003c\/td\u003e\n\u003ctd\u003eOK (Hørning)\u003c\/td\u003e\n\u003ctd\u003e56.091446\u003c\/td\u003e\n\u003ctd\u003e10.048286\u003c\/td\u003e\n\u003ctd\u003e8362\u003c\/td\u003e\n\u003ctd\u003e17 Nydamsvej, Hørning, 8362, Denmark\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp id=\"table-note\" class=\"data-preview-note\" style=\"font-style: italic; font-size: 0.9em;\"\u003eNote: Only a subset of the full dataset fields are displayed here. Download the \u003cstrong\u003efree sample\u003c\/strong\u003e (option above) to view all fields and verify the data structure.\u003c\/p\u003e\u003cdiv style=\"background:#f8fff8; border:1px solid #c3e6cb; border-radius:6px; padding:16px 20px; margin:24px 0;\"\u003e\n\u003cp style=\"margin:0 0 10px 0; font-weight:bold; font-size:1em;\"\u003eWhy download from Geolocet?\u003c\/p\u003e\n\u003cul style=\"margin:0; padding-left:18px; font-size:0.95em; line-height:1.8;\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eInstant download\u003c\/strong\u003e - full dataset available immediately after purchase, no waiting, no manual fulfilment\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFree sample first\u003c\/strong\u003e - verify structure, fields, and coordinate precision before you commit\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAnalysis-ready CSV\u003c\/strong\u003e - clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRegularly updated\u003c\/strong\u003e - last updated \u003cstrong\u003e15 July 2026\u003c\/strong\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\u003cp style=\"text-align:center; margin:16px 0; font-size:0.95em;\"\u003e✅ Data looks right? \u003ca href=\"#\" onclick=\"window.scrollTo({top:0,behavior:'smooth'});return false;\" style=\"color:#2c6fad; font-weight:bold;\"\u003eAdd to cart ↑\u003c\/a\u003e - or download the \u003cstrong\u003efree sample\u003c\/strong\u003e first.\u003c\/p\u003e\u003ch2 id=\"regional-distribution\"\u003eRegional Distribution Breakdown\u003c\/h2\u003e\u003cp\u003eLooking at the geographic distribution, the highest concentration of OK locations in Denmark is found in \u003cstrong\u003eRegion Syddanmark\u003c\/strong\u003e (271 sites, equivalent to \u003cstrong\u003e21.85 OK ev charging stations per 100,000 residents\u003c\/strong\u003e). This is followed by \u003cstrong\u003eRegion Hovedstaden\u003c\/strong\u003e (216 sites; 11.13 per 100,000) and \u003cstrong\u003eRegion Midtjylland\u003c\/strong\u003e (165 sites; 11.96 per 100,000). From a market-penetration perspective, \u003cstrong\u003eRegion Syddanmark\u003c\/strong\u003e has the highest brand density at \u003cstrong\u003e21.85 locations per 100,000 people\u003c\/strong\u003e (population: 1,240,000), making it the most saturated region for OK in Denmark. By contrast, \u003cstrong\u003eRegion Hovedstaden\u003c\/strong\u003e records only 11.13 locations per 100,000 residents (population: 1,940,000), indicating a potential white-space opportunity for network expansion or competitor analysis.\u003c\/p\u003e\u003ch2 id=\"brand-bundle\" style=\"margin-bottom:12px;\"\u003eAlso available for Denmark\u003c\/h2\u003e\u003cdiv style=\"border:1px solid #2c6fad; border-left:4px solid #2c6fad; border-radius:0 6px 6px 0; padding:16px 20px; margin-bottom:12px; background:#f5f9ff;\"\u003e\n\u003cp style=\"margin:0 0 4px 0; font-size:0.8em; text-transform:uppercase; letter-spacing:0.05em; color:#2c6fad; font-weight:bold;\"\u003eBrand bundle\u003c\/p\u003e\n\u003cp style=\"margin:0 0 8px 0; font-weight:bold; font-size:1.05em;\"\u003eTop 14 EV Charging Stations Brands in Denmark - €380\u003c\/p\u003e\n\u003cp style=\"margin:0 0 12px 0; font-size:0.9em; color:#444;\"\u003eAll major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.\u003c\/p\u003e\n\u003ca href=\"https:\/\/geolocet.com\/products\/denmark-ev-brands\" style=\"display:inline-block; background:#2c6fad; color:#fff; padding:7px 14px; border-radius:4px; text-decoration:none; font-size:0.88em; font-weight:bold;\"\u003eView Top Brands dataset →\u003c\/a\u003e\n\u003c\/div\u003e\u003cdiv style=\"border:1px solid #6c757d; border-left:4px solid #6c757d; border-radius:0 6px 6px 0; padding:16px 20px; margin-bottom:12px; background:#f9f9f9;\"\u003e\n\u003cp style=\"margin:0 0 4px 0; font-size:0.8em; text-transform:uppercase; letter-spacing:0.05em; color:#6c757d; font-weight:bold;\"\u003eFull market coverage\u003c\/p\u003e\n\u003cp style=\"margin:0 0 8px 0; font-weight:bold; font-size:1.05em;\"\u003eAll EV Charging Stations Locations in Denmark - complete POI dataset\u003c\/p\u003e\n\u003cp style=\"margin:0 0 12px 0; font-size:0.9em; color:#444;\"\u003eIncludes everything in the brand bundle \u003cem\u003eplus\u003c\/em\u003e independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.\u003c\/p\u003e\n\u003ca href=\"https:\/\/geolocet.com\/products\/denmark-ev-charging-stations-poi-data\" style=\"display:inline-block; background:#6c757d; color:#fff; padding:7px 14px; border-radius:4px; text-decoration:none; font-size:0.88em; font-weight:bold;\"\u003eView full POI dataset →\u003c\/a\u003e\n\u003c\/div\u003e\u003ch2 id=\"related-datasets\"\u003eRelated geospatial datasets\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/products\/denmark-all-available-administrative-boundaries\" rel=\"noopener noreferrer\"\u003eAdministrative boundaries and full polygon dataset for Denmark\u003c\/a\u003e: Map these OK locations against highly precise administrative polygons for territory analysis and spatial structuring.\u003c\/li\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/products\/denmark-geodemographics-dataset-with-boundaries\" rel=\"noopener noreferrer\"\u003eDemographics dataset for Denmark\u003c\/a\u003e: Overlay demographic indicators to deeply understand the population structures and household types surrounding these OK locations.\u003c\/li\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/pages\/denmark#DemographicsData\" rel=\"noopener noreferrer\"\u003eExplore demographics data insights for Denmark\u003c\/a\u003e: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.\u003c\/li\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/products\/denmark-income-indicators-parish\" rel=\"noopener noreferrer\" title=\"Download small-area income dataset for Denmark: income distribution, household earnings, socio-economic segmentation indicators.\"\u003eIncome indicators dataset for Denmark (small-area income analysis)\u003c\/a\u003e: Download an analysis-ready dataset on income distribution across small geographic units - ideal for segmentation, customer analytics, location planning, and socio-economic scoring.\u003c\/li\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/blogs\/news\/income-distribution-across-danish-parishes\" rel=\"noopener noreferrer\" title=\"Read an expert analysis of income distribution and socio-economic patterns in Denmark, including practical use cases for location intelligence.\"\u003eIncome distribution and socio-economic patterns in Denmark - expert analysis\u003c\/a\u003e: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.\u003c\/li\u003e\n\u003cli\u003eExplore a rich library of Denmark-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. \u003ca href=\"https:\/\/geolocet.com\/pages\/denmark\" rel=\"noopener noreferrer\"\u003eView demographics, retail POI, and administrative boundary datasets for Denmark\u003c\/a\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2 id=\"formats\"\u003eNeed the data in another format?\u003c\/h2\u003e\u003cp\u003eWe can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at \u003ca href=\"mailto:contact@geolocet.com\"\u003econtact@geolocet.com\u003c\/a\u003e.\u003c\/p\u003e\u003ch2 id=\"use-cases\"\u003eWho uses this data?\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eSmart City Research:\u003c\/strong\u003e Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEconomic Development:\u003c\/strong\u003e Agencies identifying underserved neighborhoods or \"retail deserts\" for targeted commercial investment.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConsumer Behavior Analytics:\u003c\/strong\u003e Researchers correlating local demographics, foot traffic data, and proximity to physical stores.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eGeofencing \u0026amp; Targeted Advertising:\u003c\/strong\u003e Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eB2B Telemarketing \u0026amp; Outreach:\u003c\/strong\u003e Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVendor Distribution:\u003c\/strong\u003e FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCommercial Brokerage:\u003c\/strong\u003e Real estate brokers validating commercial property valuations based on proximity to major retail anchors.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSupply Chain Strategy:\u003c\/strong\u003e Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2 id=\"faq\" style=\"margin-top: 30px;\"\u003eFrequently Asked Questions\u003c\/h2\u003e\u003cdiv class=\"faq-section\"\u003e\n\u003cdiv style=\"border-bottom:1px solid #eee; padding:12px 0;\"\u003e\n\u003cp style=\"font-weight:bold; margin:0 0 6px 0;\"\u003eQ: Is this dataset useful for accessibility studies?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"border-bottom:1px solid #eee; padding:12px 0;\"\u003e\n\u003cp style=\"font-weight:bold; margin:0 0 6px 0;\"\u003eQ: Can this dataset be used for academic or research purposes?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"border-bottom:1px solid #eee; padding:12px 0;\"\u003e\n\u003cp style=\"font-weight:bold; margin:0 0 6px 0;\"\u003eQ: How are addresses standardized?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"border-bottom:1px solid #eee; padding:12px 0;\"\u003e\n\u003cp style=\"font-weight:bold; margin:0 0 6px 0;\"\u003eQ: Can I analyze this dataset with AI tools?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"border-bottom:1px solid #eee; padding:12px 0;\"\u003e\n\u003cp style=\"font-weight:bold; margin:0 0 6px 0;\"\u003eQ: Is this dataset useful for franchise analysis?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Is this dataset useful for accessibility studies?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can this dataset be used for academic or research purposes?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How are addresses standardized?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I analyze this dataset with AI tools?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Is this dataset useful for franchise analysis?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.\"\n      }\n    }\n  ]\n}\n\u003c\/script\u003e\u003ch2 id=\"ai-prompts\"\u003eAnalyze this data with AI\u003c\/h2\u003e\u003cp\u003eUse these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:\u003c\/p\u003e\u003cul style=\"margin-left: 20px;\"\u003e\n\u003cli class=\"ai-prompt-item\"\u003e\u003ccode\u003e\"Analyze this OK dataset to identify underserved regions in Denmark for potential market expansion.\"\u003c\/code\u003e\u003c\/li\u003e\n\u003cli class=\"ai-prompt-item\"\u003e\u003ccode\u003e\"Generate regional density heatmaps showing where OK has the strongest and weakest retail presence in Denmark.\"\u003c\/code\u003e\u003c\/li\u003e\n\u003cli class=\"ai-prompt-item\"\u003e\u003ccode\u003e\"Compare the spatial distribution of OK locations against major competitor clusters to identify overlap and whitespace opportunities in Denmark.\"\u003c\/code\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp style=\"font-size: 0.8em; color: #888; margin-top: 20px; border-top: 1px solid #eee; padding-top: 10px;\"\u003e\u003cem\u003e\u003cstrong\u003eDisclaimer:\u003c\/strong\u003e All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.\u003c\/em\u003e\u003c\/p\u003e","brand":"Denmark","offers":[{"title":"Full dataset","offer_id":60213550481742,"sku":"denmark-ok-ev-full","price":60.0,"currency_code":"EUR","in_stock":true},{"title":"Free sample","offer_id":60213550514510,"sku":"denmark-ok-ev-sample","price":0.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0727\/3853\/7806\/files\/Locations_OK.png?v=1784102523","url":"https:\/\/geolocet.com\/products\/denmark-ok-ev","provider":"Geolocet","version":"1.0","type":"link"}