{"product_id":"denmark-norlys-ev","title":"Norlys EV Charging Station Locations Dataset – Denmark","description":"\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\/\",\n  \"@type\": \"Dataset\",\n  \"name\": \"Norlys EV Charging Station Locations Dataset – Denmark\",\n  \"description\": \"Download a geocoded dataset containing 1236 Norlys 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-norlys-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\": \"1236 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: Norlys 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-norlys-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\": \"80.00\",\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    \"Norlys\",\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    \"Norlys EV Charging Station locations Denmark\",\n    \"Geocoded Norlys locations - Denmark CSV\",\n    \"Norlys EV Charging Station Denmark address list\",\n    \"Norlys Denmark geospatial dataset\"\n  ],\n  \"temporalCoverage\": \"2026-07-15\",\n  \"mentions\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Norlys\",\n    \"url\": \"https:\/\/www.norlys.dk\",\n    \"alternateName\": \"Norlys Holding A\/S \/ Norlys Charging\",\n    \"sameAs\": \"https:\/\/en.wikipedia.org\/wiki\/Norlys\"\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\": \"Norlys EV Charging Stations Dataset\",\n      \"item\": \"https:\/\/geolocet.com\/products\/denmark-norlys-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 Norlys Holding A\/S is a Danish, member-owned energy and telecommunications group formed in 2020 from the merger of SE and Eniig, and Denmark's largest integrated energy and telecom provider. Its EV charging service, branded Norlys Charging, is built on Monta's software platform and forms one of the country's largest public charging networks.\u003c\/p\u003e\u003cp\u003eThere are \u003cstrong\u003e1,236 Norlys 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 Norlys 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 1,236 Norlys 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_Norlys_EV_Charging_Stations_Locations_Map.png\" alt=\"Map showing the geographical distribution of Norlys 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 Norlys 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\u003e9eb687f...\u003c\/td\u003e\n\u003ctd\u003eNorlys Charging Station\u003c\/td\u003e\n\u003ctd\u003e55.540383\u003c\/td\u003e\n\u003ctd\u003e9.769025\u003c\/td\u003e\n\u003ctd\u003e5500\u003c\/td\u003e\n\u003ctd\u003e9 Idrætsvej, Strib, 5500, Denmark\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ef8e088b...\u003c\/td\u003e\n\u003ctd\u003eNorlys Charging Station\u003c\/td\u003e\n\u003ctd\u003e55.865192\u003c\/td\u003e\n\u003ctd\u003e12.383492\u003c\/td\u003e\n\u003ctd\u003e3450\u003c\/td\u003e\n\u003ctd\u003e20 Sortemosevej, Blovstrød, 3450, Den...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ec23b6ad...\u003c\/td\u003e\n\u003ctd\u003eNorlys Charging Station\u003c\/td\u003e\n\u003ctd\u003e56.184337\u003c\/td\u003e\n\u003ctd\u003e10.098945\u003c\/td\u003e\n\u003ctd\u003e8381\u003c\/td\u003e\n\u003ctd\u003e38A Anelystparken, Aarhus, 8381, Denmark\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e3cab3df...\u003c\/td\u003e\n\u003ctd\u003eNorlys Charging Station\u003c\/td\u003e\n\u003ctd\u003e55.794847\u003c\/td\u003e\n\u003ctd\u003e12.504624\u003c\/td\u003e\n\u003ctd\u003e2800\u003c\/td\u003e\n\u003ctd\u003e2 Mølleåparken, Kongens Lyngby, 2800,...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e15fd459...\u003c\/td\u003e\n\u003ctd\u003eNorlys Charging Station\u003c\/td\u003e\n\u003ctd\u003e56.971934\u003c\/td\u003e\n\u003ctd\u003e9.831941\u003c\/td\u003e\n\u003ctd\u003e9230\u003c\/td\u003e\n\u003ctd\u003e25 Bautastenen, Svenstrup J, 9230, De...\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 Norlys locations in Denmark is found in \u003cstrong\u003eRegion Midtjylland\u003c\/strong\u003e (372 sites, equivalent to \u003cstrong\u003e26.96 Norlys ev charging stations per 100,000 residents\u003c\/strong\u003e). This is followed by \u003cstrong\u003eRegion Hovedstaden\u003c\/strong\u003e (278 sites; 14.33 per 100,000) and \u003cstrong\u003eRegion Syddanmark\u003c\/strong\u003e (262 sites; 21.13 per 100,000). From a market-penetration perspective, \u003cstrong\u003eRegion Nordjylland\u003c\/strong\u003e has the highest brand density at \u003cstrong\u003e36.61 locations per 100,000 people\u003c\/strong\u003e (population: 590,000), making it the most saturated region for Norlys in Denmark. By contrast, \u003cstrong\u003eRegion Sjælland\u003c\/strong\u003e records only 12.63 locations per 100,000 residents (population: 855,000), 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 Norlys 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 Norlys 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\u003eSupply Chain Strategy:\u003c\/strong\u003e Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMobility Analysis:\u003c\/strong\u003e Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.\u003c\/li\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\u003eCatchment Area Analysis:\u003c\/strong\u003e Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.\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\u003eTerritory Management:\u003c\/strong\u003e Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTrade Area Marketing:\u003c\/strong\u003e Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.\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\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: Can I combine this dataset with administrative boundaries?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.\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 support territory optimization?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.\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: What coordinate reference system is used?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).\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: Can this data be combined with demographics datasets?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.\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 recent is this dataset?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: This dataset was last updated on 15 July 2026 and is periodically refreshed through automated collection and validation workflows.\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 the dataset immediately downloadable after purchase?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The full dataset becomes available for instant digital download immediately after purchase.\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 the dataset standardized for analytics workflows?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.\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\": \"Can I combine this dataset with administrative boundaries?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can this dataset support territory optimization?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What coordinate reference system is used?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).\"\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\": \"Can this data be combined with demographics datasets?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How recent is this dataset?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This dataset was last updated on 15 July 2026 and is periodically refreshed through automated collection and validation workflows.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Is the dataset immediately downloadable after purchase?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The full dataset becomes available for instant digital download immediately after purchase.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Is the dataset standardized for analytics workflows?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.\"\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 Norlys 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\"Identify locations where multiple Norlys sites compete within overlapping catchment areas in Denmark.\"\u003c\/code\u003e\u003c\/li\u003e\n\u003cli class=\"ai-prompt-item\"\u003e\u003ccode\u003e\"Identify potential regional logistics bottlenecks caused by uneven geographic distribution of Norlys locations 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":60213550252366,"sku":"denmark-norlys-ev-full","price":66.67,"currency_code":"EUR","in_stock":true},{"title":"Free sample","offer_id":60213550285134,"sku":"denmark-norlys-ev-sample","price":0.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0727\/3853\/7806\/files\/Locations_Norlys.png?v=1784102523","url":"https:\/\/geolocet.com\/products\/denmark-norlys-ev","provider":"Geolocet","version":"1.0","type":"link"}