This comprehensive retail point-of-interest (POI) dataset provides a detailed map of retail establishments across the United States and Canada. Retail strategists, market researchers, and business developers can leverage precise store location data to analyze market distribution, identify emerging trends, and develop targeted expansion strategies.

Point of Interest (POI) data, also known as places data, provides the exact location of buildings, stores, or specific places. It has become essential for businesses to make smarter, geography-driven decisions in today's competitive retail landscape of location intelligence.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive retail store data database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including: -Retail store locations -Restaurants -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping centers and malls, and more

Why Choose LocationsXYZ for Your Retail POI Data Needs? At LocationsXYZ, we: -Deliver POI data with 95% accuracy for reliable store location data -Refresh POIs every 30, 60, or 90 days to ensure the most recent retail location information -Create on-demand POI datasets tailored to your specific retail data requirements -Handcraft boundaries (geofences) for shopping center locations to enhance accuracy -Provide retail POI data and polygon data in multiple file formats

Unlock the Power of Retail Location Intelligence With our point-of-interest data for retail stores, you can: -Perform thorough market analyses using comprehensive store location data -Identify the best locations for new retail stores -Gain insights into consumer behavior and shopping patterns -Achieve an edge with competitive intelligence in retail markets

LocationsXYZ has empowered businesses with geospatial insights and retail location data, helping them scale and make informed decisions. Join our growing list of satisfied customers and unlock your business's potential with our cutting-edge retail POI data and shopping center location intelligence.

This core point of interest dataset consists of 1M location information of retail stores in the US and Canada. The POI database includes electronic stores, supermarkets and groceries, specialty retailers, home improvement and convenience stores, and apparel and accessories shops.

This dataset was originally created in 2012 by the Office of the Chief Technology Officer. OCTO staff used the Alcoholic Beverage and Cannabis Administration’s (ABCA) definition of Full-Service Grocery Stores which outlines criteria for a business to obtain licenses to sell beer, wine, and spirits. Visit abca.dc.gov for full definition.OCTO staff then reviewed the Office of Planning DC Food Policy’s 2018 Food System Assessment listing grocery stores in Appendix D, and comparing these to the ABCA definition. This led to additional locations that meet, or come very close to, the full-service grocery store criteria. The criteria in section one of ABCA’s full-service grocery store determined the initial locations included in this dataset. View the full assessment at dcfoodpolicycouncil.org.Since the initial creation of this dataset, OCTO and the Deputy Mayor for Planning and Economic Development (DMPED) staff confirm grocery store operations by comparing datasets from DLCP, media outlets, commercially licensed datasets, and onsite visits.Please review supplemental metadata for more details.

SafeGraph Places provides baseline information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

SafeGraph provides clean and accurate geospatial datasets on 52M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation.

Fresh POI dataset: 1 M+ verified retail locations across US & Canada with 95% accuracy. Updated every 30-90 days. Covers electronics, supermarkets, home improvement, and apparel stores. Perfect for site selection, market analysis & competitive intelligence. Get actionable retail insights instantly.

Leverage advanced location data from high-quality geospatial data covering patterns, behaviours, and trends across diverse industries. With accurate insights from multiple sources, our solutions empower businesses in retail, logistics, real estate, finance, and urban planning to optimize operations, enhance decision-making, and drive strategic growth.

Key use cases where Location Data has helped businesses : 1. Optimize Logistics & Route Planning : Streamline delivery routes, reduce transit times, and enhance operational efficiency with precise location intelligence. 2. Enhance Market Positioning & Competitor Insights : Identify high-traffic zones, analyse competitor locations, and fine-tune business strategies to maximize market presence. 3. Transform Navigation & EV Infrastructure : Power navigation systems, real-time travel recommendations, and EV charging station mapping for seamless location-based services. 4. Enhance Urban & Retail Site Selection : Identify optimal locations for stores, warehouses, and infrastructure investments with in-depth spatial data and demographic insights. 5. Strengthen Spatial Analysis & Risk Management : Leverage advanced geospatial insights for disaster preparedness, public health initiatives, and land-use optimization.

A listing of all retail food stores which are licensed by the Department of Agriculture and Markets.

Apple Retail Stores are a chain of retail stores owned by Apple Inc., specializing in the sale of Apple products and accessories. These stores are known for their sleek design, knowledgeable staff, and focus on providing a unique customer experience. Apple's retail business model is centered around creating a premium shopping environment and offering exceptional customer service. Apple also offers various in-store services, such as Genius Bar support for technical issues and personal setup assistance. You can download the complete list of key information about Apple Retail Stores locations, contact details, services offered, and geographical coordinates, beneficial for various applications like store locators, business analysis, and targeted marketing. The Apple Retail Stores data you can download includes:

Identification & Location:


  store_number, store_name

  address, address_line_2, city, state, zip_code, country, country_code, county, latitude, longitude, geo_accuracy


Contact Information:


  phone_number, website_address


Operational Details & Services:


  store_hours

GapMaps curates up-to-date and high-quality POI datasets tracking store openings and closures for leading retail brands in Indonesia across 16 categories. Get the insights you need to make more accurate and informed business decisions or incorporate POI data into your location services applications.

Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

Massive POI database covering 6 million locations across 11 industries in the US and Canada. Includes 40+ rich data attributes for each location. Empowers data-driven decision-making across various sectors, from retail to healthcare, with high-quality, diverse location intelligence.

Xverum’s Store Location Data offers unmatched global coverage of retail, restaurant, and business locations - spanning 230M+ verified POIs across 5000+ commercial categories in over 249 countries.

Whether you're launching a new retail concept, mapping competitor presence, or enriching your analytics platform with real-world business locations - our bulk dataset helps you unlock rich geospatial context.

What’s Included: ➡️ Store Locations & Addresses: Geocoded with latitude/longitude, city, postal code, country. ➡️ Business Metadata: Brand names, categories & subcategories (e.g., Restaurants, Grocery, Clothing). ➡️ Store Details (if available): Website, phone number, operating hours. ➡️ Structured Delivery: Available in .json via S3 bucket or other cloud storage.

🚫 No Foot Traffic or Mobility Data: Clean, static POI data for precise business intelligence use cases.

Use Cases: ✔️ Retail Site Selection & Market Expansion ✔️ Restaurant Chain Mapping & Competitive Benchmarking ✔️ POI Enrichment for Mapping Platforms & Apps ✔️ Real Estate & Urban Planning Analytics ✔️ Location-Based Targeting & Geospatial Analysis

Why Choose Xverum: ✅ 230M+ Store & Business POIs updated regularly ✅ Global coverage across 249+ countries ✅ 5000+ categories from retail and F&B to professional services ✅ Delivered in bulk only - ideal for enterprise data teams ✅ Privacy-compliant (GDPR/CCPA) & ethically sourced

Request your free sample today and discover how Xverum’s store location data can elevate your retail insights, POI mapping, or expansion planning.

Comprehensive dataset of 466 Map stores in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

GapMaps curates up-to-date and high-quality Point of Interest (POI) datasets tracking store openings and closures for leading retail brands across Asia and MENA. Get the insights you need to make more accurate and informed business decisions.

Data Driven Detroit created the data by selecting locations from NETS and ESRI business data with proper NAICS codes, then adding and deleting though local knowledge and confirmation with Google Streetview. These locations are Grocery stores which primarily sell food and don't include convenience stores. Visual confirmation cues included the existence of the word "grocery" in the name, or the presence of shopping carts.

The global store locator software market is experiencing robust growth, driven by the increasing need for businesses to enhance customer experience and improve omnichannel strategies. The market, estimated at $250 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rising adoption of mobile devices and location-based services empowers consumers to easily find nearby stores, increasing demand for user-friendly and feature-rich store locator solutions. Secondly, the expanding e-commerce landscape necessitates seamless integration between online and offline channels. Store locator software plays a crucial role in this integration, enabling businesses to provide accurate location information, store hours, and inventory data, thus improving customer satisfaction and driving sales. Furthermore, advanced features such as real-time inventory updates, route optimization, and integration with other business systems are enhancing the value proposition of these solutions, attracting more businesses of all sizes. However, the market also faces some challenges. The high initial investment cost for sophisticated software can be a barrier to entry for small and medium-sized enterprises (SMEs). Competition is also intensifying, with established players and new entrants vying for market share. Data security and privacy concerns related to collecting and utilizing customer location data also represent a significant restraint. Despite these challenges, the long-term growth prospects remain positive, driven by the ongoing digital transformation of retail and the increasing focus on improving customer experience. The market is segmented by software type (cloud-based, on-premise), deployment mode, enterprise size, and geography, with North America and Europe currently holding significant market shares. Leading players such as Yext, Chatmeter, and Brandify are constantly innovating to enhance their offerings and maintain their competitive edge. This involves incorporating advanced mapping technologies, AI-powered features, and improved integrations to meet the evolving needs of businesses.

To create this layer, OCTO staff used ABCA's definition of “Full-Service Grocery Stores” (https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0)– pulled from the Food System Assessment below), and using those criteria, determined locations that fulfilled the categories in section 1 of the definition.Then, staff reviewed the Office of Planning’s Food System Assessment (https://dcfoodpolicycouncilorg.files.wordpress.com/2019/06/2018-food-system-assessment-final-6.13.pdf) list in Appendix D, comparing that to the created from the ABCA definition, which led to the addition of a additional examples that meet, or come very close to, the full-service grocery store criteria. The explanation from Office of Planning regarding how the agency created their list:“To determine the number of grocery stores in the District, we analyzed existing business licenses in the Department of Consumer and Regulatory Affairs (2018) Business License Verification system (located at https://eservices.dcra.dc.gov/BBLV/Default.aspx). To distinguish grocery stores from convenience stores, we applied the Alcohol Beverage and Cannabis Administration’s (ABCA) definition of a full-service grocery store. This definition requires a store to be licensed as a grocery store, sell at least six different food categories, dedicate either 50% of the store’s total square feet or 6,000 square feet to selling food, and dedicate at least 5% of the selling area to each food category. This definition can be found at https://abca.dc.gov/page/full-service-grocery-store#gsc.tab=0. To distinguish small grocery stores from large grocery stores, we categorized large grocery stores as those 10,000 square feet or more. This analysis was conducted using data from the WDCEP’s Retail and Restaurants webpage (located at https://wdcep.com/dc-industries/retail/) and using ARCGIS Spatial Analysis tools when existing data was not available. Our final numbers differ slightly from existing reports like the DC Hunger Solutions’ Closing the Grocery Store Gap and WDCEP’s Grocery Store Opportunities Map; this difference likely comes from differences in our methodology and our exclusion of stores that have closed.”Staff also conducted a visual analysis of locations and relied on personal experience of visits to locations to determine whether they should be included in the list.

Comprehensive POI data for all malls and shopping centers in the US. Crucial for retail strategy, market analysis, and commercial real estate decisions across the country.

GapMaps curates up-to-date and high-quality Point of Interest (POI) data tracking store openings and closures for leading retail brands in India across 15 categories. Get the insights you need to make more accurate and informed retail location decisions globally.

Locations of Hardware Stores, which are deemed essential following hurricanes or other disaster scenarios.This dataset is fed from revenue with weekly updates