{"product_id":"poland-kaufland-ev","title":"Kaufland EV Charging Station Locations Dataset – Poland","description":"\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\/\",\n  \"@type\": \"Dataset\",\n  \"name\": \"Kaufland EV Charging Station Locations Dataset – Poland\",\n  \"description\": \"Download a geocoded dataset containing 204 Kaufland ev charging station locations across Poland. Includes addresses, administrative areas, and WGS84 latitude\/longitude coordinates in CSV format for GIS, market research, logistics, site selection, and location intelligence applications. Updated: 2 June 2026.\",\n  \"url\": \"https:\/\/geolocet.com\/products\/poland-kaufland-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\": \"2026-06-02\",\n  \"lastVerified\": \"2026-06-02\",\n  \"spatialCoverage\": {\n    \"@type\": \"Place\",\n    \"name\": \"Poland\"\n  },\n  \"size\": \"204 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: Kaufland EV Charging Stations Locations Dataset – Poland\",\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\/poland-kaufland-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\": \"Admin_level_1\",\n      \"description\": \"Specific data attribute detailing the admin_level_1 of the location.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Admin_level_2\",\n      \"description\": \"Specific data attribute detailing the admin_level_2 of the location.\"\n    },\n    {\n      \"@type\": \"PropertyValue\",\n      \"name\": \"Municipality\",\n      \"description\": \"Municipality.\"\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\": \"36.00\",\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    \"Kaufland\",\n    \"Poland\",\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    \"Kaufland Poland geospatial dataset\",\n    \"Kaufland EV Charging Station Poland address list\",\n    \"Kaufland EV Charging Station locations Poland\",\n    \"Geocoded Kaufland locations - Poland CSV\"\n  ],\n  \"temporalCoverage\": \"2026-06-02\",\n  \"mentions\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Kaufland\",\n    \"url\": \"https:\/\/www.kaufland.pl\",\n    \"alternateName\": \"Kaufland Polska\",\n    \"sameAs\": \"https:\/\/en.wikipedia.org\/wiki\/Kaufland\"\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\": \"Poland\",\n      \"item\": \"https:\/\/geolocet.com\/pages\/poland\"\n    },\n    {\n      \"@type\": \"ListItem\",\n      \"position\": 4,\n      \"name\": \"Kaufland EV Charging Stations Dataset\",\n      \"item\": \"https:\/\/geolocet.com\/products\/poland-kaufland-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 Kaufland is a major hypermarket chain operating widely across Poland, offering a vast assortment of groceries and household goods. To support sustainable practices, many of its retail locations are equipped with electric vehicle charging stations for customer convenience.\u003c\/p\u003e\u003cp\u003eThere are \u003cstrong\u003e204 Kaufland EV Charging Stations\u003c\/strong\u003e as of \u003cstrong\u003e2 June 2026\u003c\/strong\u003e in Poland. 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 Kaufland 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 204 Kaufland ev charging stations in Poland\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 2 June 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\/Poland_Kaufland_EV_Charging_Stations_Locations_Map.png\" alt=\"Map showing the geographical distribution of Kaufland locations in Poland\" 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\u003eAdmin_level_1\u003c\/li\u003e\n\u003cli\u003eAdmin_level_2\u003c\/li\u003e\n\u003cli\u003eMunicipality\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 Kaufland dataset in Poland\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\u003e745af72...\u003c\/td\u003e\n\u003ctd\u003eKaufland Charging Station\u003c\/td\u003e\n\u003ctd\u003e54.183397\u003c\/td\u003e\n\u003ctd\u003e17.494493\u003c\/td\u003e\n\u003ctd\u003e77-100\u003c\/td\u003e\n\u003ctd\u003e15 Generała Józefa Wybickiego, Bytów,...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ebf7460f...\u003c\/td\u003e\n\u003ctd\u003eKaufland Charging Station\u003c\/td\u003e\n\u003ctd\u003e52.629710\u003c\/td\u003e\n\u003ctd\u003e20.381787\u003c\/td\u003e\n\u003ctd\u003e09-100\u003c\/td\u003e\n\u003ctd\u003e16 Żołnierzy Wyklętych, Płońsk, 09-10...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ec3daf7e...\u003c\/td\u003e\n\u003ctd\u003eKaufland Charging Station\u003c\/td\u003e\n\u003ctd\u003e52.740916\u003c\/td\u003e\n\u003ctd\u003e23.587162\u003c\/td\u003e\n\u003ctd\u003e17-200\u003c\/td\u003e\n\u003ctd\u003e18 Stefana Batorego, Hajnówka, 17-200...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ea4d2515...\u003c\/td\u003e\n\u003ctd\u003eKaufland Charging Station\u003c\/td\u003e\n\u003ctd\u003e51.213192\u003c\/td\u003e\n\u003ctd\u003e22.712218\u003c\/td\u003e\n\u003ctd\u003e21-040\u003c\/td\u003e\n\u003ctd\u003e3 Krępiecka, Świdnik, 21-040, Powiat ...\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003efc9948f...\u003c\/td\u003e\n\u003ctd\u003eKaufland Charging Station\u003c\/td\u003e\n\u003ctd\u003e52.538437\u003c\/td\u003e\n\u003ctd\u003e17.611766\u003c\/td\u003e\n\u003ctd\u003e62-200\u003c\/td\u003e\n\u003ctd\u003e46 Franklina Roosevelta, Gniezno, 62-...\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\u003e2 June 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 Kaufland locations in Poland is found in \u003cstrong\u003eŚląskie\u003c\/strong\u003e (34 sites, equivalent to \u003cstrong\u003e0.79 Kaufland ev charging stations per 100,000 residents\u003c\/strong\u003e). This is followed by \u003cstrong\u003eMazowieckie\u003c\/strong\u003e (25 sites; 0.45 per 100,000) and \u003cstrong\u003eWielkopolskie\u003c\/strong\u003e (23 sites; 0.66 per 100,000). From a market-penetration perspective, \u003cstrong\u003eŚląskie\u003c\/strong\u003e has the highest brand density at \u003cstrong\u003e0.79 locations per 100,000 people\u003c\/strong\u003e (population: 4,290,000), making it the most saturated region for Kaufland in Poland. By contrast, \u003cstrong\u003eMałopolskie\u003c\/strong\u003e records only 0.2 locations per 100,000 residents (population: 3,430,000), 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 Poland\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 21 EV Charging Stations Brands in Poland - €240\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\/poland-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 Poland - 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\/poland-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\/poland-all-available-administrative-boundaries\" rel=\"noopener noreferrer\"\u003eAdministrative boundaries and full polygon dataset for Poland\u003c\/a\u003e: Map these Kaufland 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\/poland-geodemographics-dataset-with-boundaries\" rel=\"noopener noreferrer\"\u003eDemographics dataset for Poland\u003c\/a\u003e: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Kaufland locations.\u003c\/li\u003e\n\u003cli\u003e\n\u003ca href=\"https:\/\/geolocet.com\/pages\/poland#DemographicsData\" rel=\"noopener noreferrer\"\u003eExplore demographics data insights for Poland\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\/poland-income-indicators-gmina\" rel=\"noopener noreferrer\" title=\"Download small-area income dataset for Poland: income distribution, household earnings, socio-economic segmentation indicators.\"\u003eIncome indicators dataset for Poland (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\u003eExplore a rich library of Poland-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\/poland\" rel=\"noopener noreferrer\"\u003eView demographics, retail POI, and administrative boundary datasets for Poland\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\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\u003eFranchise Expansion:\u003c\/strong\u003e Network development teams assessing market saturation and mapping open territories for new franchisees.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eLast-Mile Delivery Routing:\u003c\/strong\u003e E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.\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\u003eUrban Planning:\u003c\/strong\u003e City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.\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\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\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\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\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: Are postal codes included for all locations?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Postal codes are included wherever available and validated as part of the standardization workflow.\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 accurate are the coordinates?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.\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: Are the datasets suitable for machine learning workflows?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.\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 request custom enrichment fields?\u003c\/p\u003e\n\u003cp style=\"margin:0; color:#444;\"\u003eA: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.\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\": \"Are postal codes included for all locations?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Postal codes are included wherever available and validated as part of the standardization workflow.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How accurate are the coordinates?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Are the datasets suitable for machine learning workflows?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I request custom enrichment fields?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.\"\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 Kaufland dataset to identify underserved regions in Poland 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 Kaufland has the strongest and weakest retail presence in Poland.\"\u003c\/code\u003e\u003c\/li\u003e\n\u003cli class=\"ai-prompt-item\"\u003e\u003ccode\u003e\"Evaluate how evenly Kaufland locations are distributed across provinces, districts, or municipalities in Poland.\"\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":"Poland","offers":[{"title":"Full dataset","offer_id":59938913976654,"sku":"poland-kaufland-ev-full","price":30.0,"currency_code":"EUR","in_stock":true},{"title":"Free sample","offer_id":59938914009422,"sku":"poland-kaufland-ev-sample","price":0.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0727\/3853\/7806\/files\/Locations_of_Kaufland_2025-11-29.png?v=1764441774","url":"https:\/\/geolocet.com\/products\/poland-kaufland-ev","provider":"Geolocet","version":"1.0","type":"link"}