Although consumers visit physical stores more frequently, the number of people that shop online each week is not to be discredited: in the United Kingdom (UK), for example, approximately half of surveyed consumers said they shopped online each week in 2023. More than 75 percent UK shoppers visited physical stores on a weekly basis. About the same number of Australians stated they had been shopping digitally and physically each week.

Retail Sales in the United States decreased 0.90 percent in May of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

A comprehensive dataset providing key insights into the eCommerce industry, including global retail online sales projections, number of eCommerce stores, digital buyer statistics, revenue growth in the United States, sector-wise revenue details with a focus on consumer electronics, average conversion rates, and mobile commerce sales forecasts.

This dataset provides insights into eCommerce shopping preferences and trends among UK adults in 2024. The findings are derived from data collected from a sample of 2,017 UK adults regarding their shopping habits and influencing factors.Furthermore, hundreds of thousands online searches were analysed to collate the most up-to-date statistics.

In 2020, a total of over ** percent of consumers across the globe shopped online: reaching nearly ** percent each, the leading regions that year were South America and Asia. North America had the lowest share with just over ***** in **** consumers buying items on the internet. The online store that was used most frequently by shoppers worldwide was Amazon.com.

Favorite online stores in the U.S. As of November 2020, an estimated ** percent of U.S. consumers stated that their online shop of choice was Amazon, making it by far the favorite e-commerce shop among online shoppers. With less than ** percent, Walmart’s web shop ranked second. Both male and female consumers in the country had a clear preference for Amazon, however, certain online stores were more popular among specific genders. For instance, more men liked visiting eBay, while a higher percentage of women had a preference for Target.

Why do consumers like Amazon? There were various reasons why U.S. shoppers used Amazon to buy products in 2020, the leading reason being the fast and free shipping services provided. Other key factors consumers mentioned, included Amazon’s broad selection, the easy return process, and the platform having some of the lowest prices.

To this day, the Geodatindustry database is the world's most complete and accurate in the retail, commercial and industry area, with 25 years of experience and a qualified teams.

Geodatindustry Database is the perfect tool to lead your decision making, market analytics, strategy building, prospecting, advertizing compaigns, etc.

By purchasing this dataset, you gain access to more than 18,000 shopping malls all over the World, hosting millions of stores and welcoming millions of visitors each year.

Included Points of Interest in this dataset : -Shopping Malls and Centers -Outlets -Big Supermakets and Hypermarkets.

Information (if known) : shopping mall's name, physical address, number of shops, x,y coordinates, annual visitors counts (in millions), owner and managers, global area and GLA (in ranges), the website.

Global area and GLA Ranges : A = 0-2 500 m² B = 2 500-5 000 m² C = 5 000-10 000 m² D = 10 000-25 000 m²
E = 25 000-50 000 m² F = 50 000-75 000 m² G = 75 000-100 000 m² H = 100 000-1M m² I = 1M-10M m² J = 10M m² and +

Prices depend on the amount of Shopping Malls for each country. It goes from 59€ to 3990€ per country.

Success.ai’s Retail Data for the Retail Sector in North America offers a comprehensive dataset designed to connect businesses with key players across the diverse retail industry. Covering everything from department stores and supermarkets to specialty shops and e-commerce platforms, this dataset provides verified contact details, business locations, and leadership profiles for retail companies in the United States, Canada, and Mexico.

With access to over 170 million verified professional profiles and 30 million company profiles, Success.ai ensures your outreach, marketing, and business development efforts are powered by accurate, continuously updated, and AI-validated data.

Backed by our Best Price Guarantee, this solution empowers businesses to thrive in North America’s competitive retail landscape.

Why Choose Success.ai’s Retail Data for North America?

1. Verified Contact Data for Precision Outreach

   • Access verified phone numbers, work emails, and LinkedIn profiles of retail executives, store managers, and decision-makers.
   • AI-driven validation ensures 99% accuracy, enabling confident communication and efficient campaign execution.

2. Comprehensive Coverage Across Retail Segments

   • Includes profiles of retail businesses across major markets, from large department stores and grocery chains to boutique retailers and online platforms.
   • Gain insights into the operational dynamics of retail hubs in cities such as New York, Los Angeles, Toronto, and Mexico City.

3. Continuously Updated Datasets

   • Real-time updates reflect leadership changes, new store openings, market expansions, and shifts in consumer preferences.
   • Stay aligned with evolving industry trends and emerging opportunities in the North American retail sector.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other privacy regulations, ensuring responsible and lawful use of data in your campaigns.

Data Highlights:

• 170M+ Verified Professional Profiles: Engage with executives, marketing directors, and operations managers across the North American retail sector.
• 30M Company Profiles: Access firmographic data, including revenue ranges, store counts, and geographic footprints.
• Store Location Data: Pinpoint retail outlets, regional offices, and distribution centers to refine supply chain and marketing strategies.
• Leadership Contact Details: Connect with CEOs, CMOs, and procurement officers influencing retail operations and vendor selections.

Key Features of the Dataset:

1. Retail Decision-Maker Profiles

   • Identify and engage with store owners, category managers, and marketing directors shaping customer experiences and product strategies.
   • Target professionals responsible for inventory planning, vendor contracts, and store performance.

2. Advanced Filters for Precision Targeting

   • Filter companies by industry segment (luxury, grocery, e-commerce), geographic location, company size, or revenue range.
   • Tailor outreach to align with regional market trends, customer demographics, and operational priorities.

3. Market Trends and Operational Insights

   • Analyze trends such as online shopping growth, sustainability practices, and supply chain optimization.
   • Leverage insights to refine product offerings, identify partnership opportunities, and design effective campaigns.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and enhance engagement outcomes.

Strategic Use Cases:

1. Sales and Lead Generation

   • Present products, services, or technology solutions to retail procurement teams, marketing departments, and operations managers.
   • Build relationships with retailers seeking innovative tools, efficient supply chain solutions, or unique product offerings.

2. Market Research and Consumer Insights

   • Analyze retail trends, customer behaviors, and seasonal demands to inform marketing strategies and product launches.
   • Benchmark against competitors to identify gaps, emerging niches, and growth opportunities.

3. E-Commerce and Digital Strategy Development

   • Target e-commerce managers and digital transformation teams driving online retail initiatives and omnichannel integration.
   • Offer solutions to enhance online shopping experiences, logistics, and customer loyalty programs.

4. Recruitment and Workforce Solutions

   • Engage HR professionals and hiring managers in recruiting talent for store operations, customer service, or marketing roles.
   • Provide workforce optimization tools, training platforms, or staffing services tailored to retail environments.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality retail data at competitive prices, ensuring strong ROI for your marketing and outreach efforts in North America.

2. Seamless Integration
   ...

A detailed dataset exploring the retail industry in 2025, including market size, store counts, revenue trends, AI integration, and consumer behavior across the US and globally.

This statistic shows a trend in total retail sales including food services in the United States from January 2017 to March 2025. In March 2025, U.S. retail sales had amounted to an estimated ************* U.S. dollars (not adjusted), which is an increase of *** compared to the same month one year earlier.

Expected to reach 12 billion U.S. dollars, Cyber Monday is the shopping day with the highest e-commerce sales revenue in the United States in 2023. Black Friday ranks second, with over nine billion dollars in online revenue according to the latest forecasts.

Success.ai’s Ecommerce Store Data for the APAC E-commerce Sector provides a reliable and accurate dataset tailored for businesses aiming to connect with e-commerce professionals and organizations across the Asia-Pacific region. Covering roles and businesses involved in online retail, marketplace management, logistics, and digital commerce, this dataset includes verified business profiles, decision-maker contact details, and actionable insights.

With access to continuously updated, AI-validated data and over 700 million global profiles, Success.ai ensures your outreach, market analysis, and partnership strategies are effective and data-driven. Backed by our Best Price Guarantee, this solution helps you excel in one of the world’s fastest-growing e-commerce markets.

Why Choose Success.ai’s Ecommerce Store Data?

1. Verified Profiles for Precision Engagement

   • Access verified profiles, business locations, employee counts, and decision-maker details for e-commerce businesses across APAC.
   • AI-driven validation ensures 99% accuracy, improving engagement rates and reducing outreach inefficiencies.

2. Comprehensive Coverage of the APAC E-commerce Sector

   • Includes businesses from major e-commerce hubs such as China, India, Japan, South Korea, Australia, and Southeast Asia.
   • Gain insights into regional e-commerce trends, digital transformation efforts, and logistics innovations.

3. Continuously Updated Datasets

   • Real-time updates ensure that business profiles, employee roles, and operational insights remain accurate and relevant.
   • Stay aligned with dynamic market conditions and emerging opportunities in the APAC region.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Access business profiles for e-commerce professionals and organizations across APAC.
• Firmographic Insights: Gain detailed information, including business locations, employee counts, and operational details.
• Decision-maker Profiles: Connect with key e-commerce leaders, managers, and strategists driving online retail innovation.
• Industry Trends: Understand emerging e-commerce trends, consumer behavior, and market dynamics in the APAC region.

Key Features of the Dataset:

1. Comprehensive E-commerce Business Profiles

   • Identify and connect with businesses specializing in online retail, marketplace management, and digital commerce logistics.
   • Target decision-makers involved in supply chain optimization, digital marketing, and platform development.

2. Advanced Filters for Precision Campaigns

   • Filter businesses and professionals by industry focus (fashion, electronics, grocery), geographic location, or employee size.
   • Tailor campaigns to address specific goals, such as promoting technology adoption, enhancing customer engagement, or expanding supply chains.

3. Regional and Sector-specific Insights

   • Leverage data on APAC’s fast-growing e-commerce markets, consumer purchasing trends, and regional challenges.
   • Refine your marketing strategies and outreach efforts to align with market priorities.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Outreach

   • Promote e-commerce solutions, logistics services, or digital commerce tools to businesses and professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and social media campaigns.

2. Partnership Development and Vendor Collaboration

   • Build relationships with e-commerce marketplaces, logistics providers, and payment solution companies seeking strategic partnerships.
   • Foster collaborations that drive operational efficiency, enhance customer experiences, or expand market reach.

3. Market Research and Competitive Analysis

   • Analyze regional e-commerce trends, consumer preferences, and logistics challenges to refine product offerings and business strategies.
   • Benchmark against competitors to identify growth opportunities and high-demand solutions.

4. Recruitment and Talent Acquisition

   • Target HR professionals and hiring managers in the e-commerce industry recruiting for roles in operations, logistics, and digital marketing.
   • Provide workforce optimization platforms or training solutions tailored to the digital commerce sector.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality e-commerce store data at competitive prices, ensuring strong ROI for your marketing, sales, and strategic initiatives.

2. Seamless Integration

   • Integrate verified e-commerce data into CRM systems, analytics platforms, or market...

According to a survey carried out in 2024 in the United States, some ** percent of baby boomers were shopping for groceries once a week. Among millennials, the share of those shopping weekly for groceries was lower, at ** percent. On the other hand, ** percent of millennials were shopping for groceries daily, while baby boomers were only ******percent. Find this and more survey data in our Consumer Insights tool. Filter by countless demographics, drill down to your own, hand-tailored target audience, and compare results across countries worldwide.

Parcel boundaries represent properties on which retail shops were found during the City of Greater Geelong's most recent retail district inspections, 2011.

Although all due care has been taken to ensure that these data are correct, no warranty is expressed or implied by the City of Greater Geelong in their use.

Explanation of Attributes

• UID_1: Unique ID
• CENTRENAME: Centre or Shop Name
• Address: Location or Address
• Suburb: Suburb
• MelwaysPag: Melways Page Number
• MelwaysRef: Melways Reference
• CentreType: Centre Type
• LastAudite: Date of Last Inspection
• PavDesignT: Pavement Surface Material
• Vacancies: Number of Vacancies
• NumbComml: Number of Commercial Properties
• NumbRetail: Number of Retail Properties
• Benches: Number of Benches
• RubbishBin: Number of Rubbish Bins
• StreetTree: Number of Street Trees
• Plantings: Number of Plantings
• BikeRacks: Number of Bicycle Parking Racks
• PhoneBox: Number of Phone Boxes
• LetterBox: Number of Letter Boxes
• OnStreetPa: Number of On-Street Parking Spaces and/or Type
• OffStreetP: Number of Off-Street Parking Spaces and/or Type
• NoticeBoar: Number of Notice Boards
• PublicTran: Number of Public Transportation Shelters
• PublicToil: Number of Public Toilets
• CapitalExp: Capital Expenditures
• CharityBin: Number of Charity Bins
• CentreSign: Presence or Type of Signage
• BuildingHe: Building Height

Discover the latest eCommerce statistics in Netherlands for 2025, including store count by category and platform, estimated sales amount by platform and category, products sold by platform and category, and total app spend by platform and category. Gain valuable insights into the retail landscape in Netherlands, uncovering the distribution of stores across categories and platforms.

United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Value: E-Commerce & Shopping: E-Commerce & Shopping data was reported at 0.000 % in 12 May 2025. This stayed constant from the previous number of 0.000 % for 05 May 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Value: E-Commerce & Shopping: E-Commerce & Shopping data is updated weekly, averaging 0.000 % from Feb 2020 (Median) to 12 May 2025, with 274 observations. The data reached an all-time high of 0.735 % in 12 Apr 2021 and a record low of 0.000 % in 12 May 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Value: E-Commerce & Shopping: E-Commerce & Shopping data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Retail Sales.

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

this graph was created in R and Canva :

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The dataset offers a comprehensive view of grocery inventory, covering 990 products across multiple categories such as Grains & Pulses, Beverages, Fruits & Vegetables, and more. It includes crucial details about each product, such as its unique identifier (Product_ID), name, category, and supplier information, including Supplier_ID and Supplier_Name. This dataset is particularly valuable for businesses aiming to optimize inventory management, sales tracking, and supply chain efficiency.

Key inventory-related fields include Stock_Quantity, which indicates the current stock level, and Reorder_Level, which determines when a product should be reordered. The Reorder_Quantity specifies how much stock to order when inventory falls below the reorder threshold. Additionally, Unit_Price provides insight into pricing, helping businesses analyze cost trends and profitability.

To manage product flow, the dataset includes dates such as Date_Received, which tracks when the product was added to the warehouse, and Last_Order_Date, marking the most recent procurement. For perishable goods, the Expiration_Date column is critical, allowing businesses to minimize waste by monitoring shelf life. The Warehouse_Location specifies where each product is stored, facilitating efficient inventory handling.

Sales and performance metrics are also included. The Sales_Volume column records the total number of units sold, providing insights into consumer demand. Inventory_Turnover_Rate helps businesses assess how quickly a product sells and is replenished, ensuring better stock management. The dataset also tracks the Status of each product, indicating whether it is Active, Discontinued, or Backordered.

The dataset serves multiple purposes in inventory management, sales performance evaluation, supplier analysis, and product lifecycle tracking. Businesses can leverage this data to refine reorder strategies, ensuring optimal stock levels and avoiding stockouts or excessive inventory. Sales analysis can help identify high-demand products and slow-moving items, enabling better decision-making in pricing and promotions. Evaluating suppliers based on their performance, pricing, and delivery efficiency helps streamline procurement and improve overall supply chain operations.

Furthermore, the dataset can support predictive analytics by employing machine learning techniques to estimate reorder quantities, forecast demand, and optimize stock replenishment. Inventory turnover insights can aid in maintaining a balanced supply, preventing unnecessary overstocking or shortages. By tracking trends in sales, businesses can refine their marketing and distribution strategies, ensuring sustained profitability.

This dataset is designed for educational and demonstration purposes, offering fictional data under the Creative Commons Attribution 4.0 International License. Users are free to analyze, modify, and apply the data while providing proper attribution. Additionally, certain products are marked as discontinued or backordered, reflecting real-world inventory dynamics. Businesses dealing with perishable goods should closely monitor expiration and last order dates to avoid losses due to spoilage.

Overall, this dataset provides a versatile resource for those interested in inventory management, sales analysis, and supply chain optimization. By leveraging the structured data, businesses can make data-driven decisions to enhance operational efficiency and maximize profitability.

United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Volume: E-Commerce & Shopping: Tickets data was reported at 0.000 % in 12 May 2025. This stayed constant from the previous number of 0.000 % for 05 May 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Volume: E-Commerce & Shopping: Tickets data is updated weekly, averaging 0.000 % from Feb 2020 (Median) to 12 May 2025, with 274 observations. The data reached an all-time high of 8.844 % in 24 Jan 2022 and a record low of 0.000 % in 12 May 2025. United States Retail Sales Nowcast: sa: YoY: Contribution: E-Commerce: E-Commerce Transactions: Volume: E-Commerce & Shopping: Tickets data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Retail Sales.

This location dataset offers a detailed geographical representation of shopping centers across North America focusing on Canada. Retail strategists, real estate investors, and market researchers can leverage precise location information to analyze retail landscapes, identify market trends, and develop targeted strategies for shopping center markets.

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 landscape.

LocationsXYZ, the POI data product from Xtract.io, offers a comprehensive database of 6 million locations across the US, UK, and Canada, spanning 11 diverse industries, including:

-Retail -Restaurants -Healthcare -Automotive -Public utilities (e.g., ATMs, park-and-ride locations) -Shopping malls, and more

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

Unlock the Power of POI Data With our point-of-interest data, you can: -Perform thorough market analyses -Identify the best locations for new stores -Gain insights into consumer behavior -Achieve an edge with competitive intelligence

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

Retail Sales of Consumer Goods: Shanghai data was reported at 128.006 RMB bn in Mar 2025. This records a decrease from the previous number of 157.034 RMB bn for Dec 2024. Retail Sales of Consumer Goods: Shanghai data is updated monthly, averaging 73.771 RMB bn from Jan 2002 (Median) to Mar 2025, with 233 observations. The data reached an all-time high of 172.656 RMB bn in Nov 2021 and a record low of 15.589 RMB bn in Apr 2002. Retail Sales of Consumer Goods: Shanghai data remains active status in CEIC and is reported by Shanghai Municipal Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.HA: Retail Sales of Consumer Goods: Provincial and Municipal Statistical Bureau. [COVID-19-IMPACT]