This dataset simulates data for a retail business, designed for Business Intelligence (BI) analysis, data visualization, and machine learning applications. The data covers multiple aspects of a retail environment, including sales, customer behavior, employee performance, inventory management, marketing campaigns, and operational costs.

It is ideal for exploring topics like sales forecasting, customer segmentation, inventory optimization, campaign ROI analysis, and performance evaluation.

Features: The dataset is structured into multiple tables, each representing a key entity in the retail business:

Lojas (Stores):

Loja_ID: Unique identifier for the store. Nome: Name of the store. Regiao: Region where the store is located. Cidade: City where the store is located. Tipo: Type of store (e.g., physical, online). Produtos (Products):

Produto_ID: Unique identifier for the product. Nome: Name of the product. Categoria: Category of the product. Preco: Price of the product. Custo_Aquisicao: Acquisition cost. Clientes (Customers):

Cliente_ID: Unique identifier for the customer. Nome: Name of the customer. Idade: Age of the customer. Genero: Gender. Cidade: City of residence. Canal_Compra: Preferred purchase channel. Total_Compras: Total spending. Vendas (Sales):

Venda_ID: Unique identifier for the sale. Loja_ID: Store where the sale occurred. Produto_ID: Product sold. Cliente_ID: Customer making the purchase. Colaborador_ID: Employee involved in the sale. Quantidade: Quantity sold. Preco_Unitario: Price per unit. Data: Date of sale. Canal: Sales channel (e.g., online, in-store). Colaboradores (Employees):

Colaborador_ID: Unique identifier for the employee. Loja_ID: Store where the employee works. Nome: Employee's name. Funcao: Job role. Horas_Trabalhadas_Semanais: Weekly working hours. Avaliacao_Desempenho: Performance rating. Vendas_Realizadas: Sales completed by the employee. Naturalidade: Place of origin. Campanhas (Marketing Campaigns):

Campanha_ID: Unique identifier for the campaign. Nome: Campaign name. Canal: Marketing channel. Investimento: Investment made in the campaign. Vendas_Geradas: Sales generated by the campaign. Data_Inicio: Start date. Data_Fim: End date. Stock (Inventory):

Produto_ID: Product identifier. Quantidade: Current stock level. Max: Maximum stock level. Min: Minimum stock level. Tempo_Entrega: Delivery time. Devolucoes (Returns):

Devolucao_ID: Unique identifier for the return. Venda_ID: Sale associated with the return. Produto_ID: Product being returned. Cliente_ID: Customer making the return. Quantidade: Quantity returned. Motivo_Devolucao: Reason for return. Data_Devolucao: Return date. Custos_Operacionais (Operational Costs):

Custo_ID: Unique identifier for the cost. Loja_ID: Store associated with the cost. Tipo_Custo: Type of cost (e.g., rent, utilities). Valor_Mensal: Monthly cost amount. Data: Cost recording date. Product Reviews:

Review_ID: Unique review identifier. Produto_ID: Reviewed product. Avaliacao: Rating (e.g., 1-5 stars). Comentario: Customer comment. Data: Date of the review. Use Cases: Data Visualization: Create dashboards for tracking sales, inventory, and employee performance. Machine Learning: Build models for predicting sales, identifying customer churn, or optimizing stock levels. Statistical Analysis: Analyze customer demographics, product performance, or campaign ROI. Scenario Simulation: Explore the impact of marketing campaigns or inventory changes on sales. Data Format: All tables are provided as CSV files. Each table is normalized to reflect relational database structures, with foreign keys linking related tables. Additional Notes: All data is synthetic and generated using Python scripts with libraries like Faker and pandas. The dataset does not represent real-world entities or behaviors but is modeled to closely mimic actual retail operations.

The extent to which individual businesses in Great Britain experienced actual changes in their sales.

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
   ...

Data Overview

• Scale: All sales figures are reported in millions of dollars.
• Size: The dataset contains 40,479 rows and 5 columns.
• Time Frame: January 1992 - September 2024.
• Industries Covered: Over 60 industries, including food, clothing, footwear, office supplies, automobiles, electronics, books, beverages, furniture, grocery and many more.
• Attributes:
  • naics_code
  • kind_of_business
  • sales_month
  • sales
  • estimate_type
• Source: This dataset was sourced from the publicly available U.S. Census Bureau retail sales data.

Cleaning & Preprocessing

• Missing Values:
  Some entries contained (NA) and (S) values, which were converted to null values.
  • (S): Estimate does not meet publication standards due to high sampling variability (coefficient of variation greater than 30%) or poor response quality (low total quantity response rate).
• Formatting:
  The downloaded data included headings, subheadings, and notes embedded within the tables. These extraneous elements were removed to ensure a clean and consistent dataset.
• Data Compilation:
  The original dataset was spread across multiple sheets, with each sheet containing data for a specific year. These sheets were consolidated into a single, unified table.
• Feature Engineering:
  A new column was created to provide both seasonally adjusted and non-seasonally adjusted sales values, enabling more nuanced analysis. Estimates are adjusted for seasonal variations, as well as holiday and trading-day differences, but not for price changes.

Use Cases

This dataset can be applied to a variety of analytical and machine learning tasks, including:

• Data Cleaning: Practice handling missing values, stray entries, and working with datetime data.
• Time Series Analysis: Perform trend analysis, seasonality detection, and forecasting.
• Exploratory Data Analysis (EDA): Gain insights into industry-specific trends and patterns.
• Machine Learning: Use it for predictive modeling and classification tasks.
• Market Research: Analyze industry performance to inform business strategies.

Retail Sales in the United States increased 0.20 percent in September 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.

Retail Sales in the United States increased 4.30 percent in September of 2025 over the same month in the previous year. This dataset provides - United States Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Success.ai’s Retail Data for Retail Professionals in APAC offers a comprehensive and accurate dataset tailored for businesses and organizations aiming to connect with key players in the retail industry across the Asia-Pacific region. Covering roles such as retail managers, merchandisers, supply chain specialists, and executives, this dataset provides verified LinkedIn profiles, work emails, and professional histories.

With access to over 700 million verified global profiles, Success.ai ensures your outreach, marketing, and collaboration strategies are powered by continuously updated, AI-validated data. Backed by our Best Price Guarantee, this solution empowers you to excel in the dynamic and competitive APAC retail market.

Why Choose Success.ai’s Retail Data?

1. Verified Contact Data for Precision Outreach

   • Access verified work emails, phone numbers, and LinkedIn profiles of retail professionals across APAC.
   • AI-driven validation ensures 99% accuracy, reducing inefficiencies and boosting engagement outcomes.

2. Comprehensive Coverage of APAC’s Retail Sector

   • Includes professionals from key retail hubs such as China, Japan, South Korea, India, Australia, and Southeast Asia.
   • Gain insights into market trends, consumer behavior, and retail innovations unique to the APAC region.

3. Continuously Updated Datasets

   • Real-time updates capture changes in roles, organizations, and industry dynamics.
   • Stay aligned with evolving trends and capitalize on emerging opportunities in the retail sector.

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 detailed retail data for professionals and organizations across the APAC region.
• Verified Contact Details: Gain work emails, phone numbers, and LinkedIn profiles for precise targeting.
• Professional Histories: Understand career trajectories, areas of expertise, and contributions to the retail sector.
• Regional Insights: Leverage actionable data on consumer preferences, supply chain challenges, and market trends.

Key Features of the Dataset:

1. Comprehensive Retail Professional Profiles

   • Identify and connect with professionals managing retail operations, merchandising, supply chains, and customer engagement strategies.
   • Target decision-makers involved in e-commerce, brick-and-mortar retail, and omnichannel strategies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (fashion, electronics, grocery), geographic location, or job function.
   • Tailor campaigns to align with specific business needs, such as technology adoption, marketing strategies, or vendor partnerships.

3. Regional and Industry-specific Insights

   • Leverage data on APAC’s retail trends, consumer purchasing patterns, and logistics challenges.
   • Refine strategies to align with unique market dynamics and customer expectations.

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 retail technology solutions, marketing tools, or supply chain services to retail professionals in the APAC region.
   • Use verified contact data for multi-channel outreach, including email, phone, and LinkedIn campaigns.

2. Partnership Development and Collaboration

   • Build relationships with retail chains, e-commerce platforms, and logistics providers seeking strategic partnerships.
   • Foster collaborations that enhance customer experiences, expand distribution networks, or improve operational efficiencies.

3. Market Research and Competitive Analysis

   • Analyze regional retail trends, consumer behavior, and supply chain innovations 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 retail industry recruiting for roles in merchandising, operations, and digital transformation.
   • Provide workforce optimization platforms or training solutions tailored to the retail sector.

Why Choose Success.ai?

1. Best Price Guarantee

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

2. Seamless Integration

   • Integrate verified retail data into CRM systems, analytics platforms, or marketing tools via APIs or downloadable formats, streamlining workflows and enhancing productivity.

3. Data Accuracy with AI Validation

   • Trust in 99% accuracy to guide data-driven decisions, refine targeting, and boost conv...

Success.ai’s Retail Data for the Retail Sector in Asia enables businesses to navigate dynamic consumer markets, evolving retail landscapes, and rapidly changing consumer behavior across the region. Leveraging over 170 million verified professional profiles and 30 million company profiles, this dataset delivers comprehensive firmographic details, verified contact information, and decision-maker insights for retailers ranging from boutique shops and e-commerce platforms to large department store chains and multinational franchises.

Whether you’re launching new products, entering emerging markets, or optimizing supply chain strategies, Success.ai’s continuously updated and AI-validated data ensures you engage the right stakeholders at the right time, all backed by our Best Price Guarantee.

Why Choose Success.ai’s Retail Data in Asia?

1. Comprehensive Company Information

   • Access verified work emails, phone numbers, and LinkedIn profiles of retail decision-makers, buyers, and merchandising managers across Asia.
   • AI-driven validation ensures 99% accuracy, enabling confident communication and minimizing wasted outreach efforts.

2. Regional Focus on Asian Markets

   • Includes profiles of small specialty retailers, large department stores, convenience chains, online marketplaces, and luxury brands spanning regions like East Asia, Southeast Asia, and South Asia.
   • Understand region-specific consumer preferences, product trends, and competitive dynamics to guide targeted campaigns and market entries.

3. Continuously Updated Datasets

   • Real-time updates reflect leadership changes, store expansions, new franchise agreements, and shifts in inventory sourcing.
   • Stay aligned with evolving market conditions, shopper behaviors, and regulatory environments impacting the Asian retail sector.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and global privacy regulations, ensuring that your data usage remains compliant and your outreach respects personal boundaries.

Data Highlights:

• 170M+ Verified Professional Profiles: Engage with executives, buyers, store managers, and e-commerce directors shaping retail landscapes in Asia.
• 30M Company Profiles: Gain insights into brand portfolios, store counts, revenue ranges, and distribution networks.
• Firmographic & Demographic Data: Understand retail categories, merchandising strategies, supply chain partners, and consumer demographics influencing local markets.
• Verified Decision-Maker Contacts: Connect directly with key stakeholders responsible for purchasing decisions, vendor selection, category management, and brand partnerships.

Key Features of the Dataset:

1. Retail Decision-Maker Profiles
   • Identify and connect with CEOs, CFOs, category buyers, inventory planners, marketing directors, and store operations leaders.

2. Target professionals who determine product assortments, vendor negotiations, store layouts, pricing strategies, and promotional campaigns.

3. Advanced Filters for Precision Targeting

   • Filter by retail segment (fashion, electronics, groceries, cosmetics), country of operation, store format, or omnichannel strategies.
   • Tailor campaigns to align with unique cultural preferences, local consumer spending habits, and regulatory frameworks.

4. AI-Driven Enrichment

   • Profiles are enriched with actionable data, enabling personalized messaging, highlighting market-entry value propositions, and improving engagement outcomes in diverse Asian markets.

Strategic Use Cases:

1. Market Entry & Expansion

   • Identify suitable partners, franchisees, or distribution channels when entering new Asian markets.
   • Benchmark against established players, adapt offerings to local tastes, and secure placements in prime retail locations.

2. Supplier and Vendor Relations

3. Connect with procurement managers and inventory planners evaluating new suppliers or seeking innovative products.

4. Present packaging solutions, POS technology, or loyalty programs to retailers aiming to enhance the shopping experience.

5. Omnichannel and E-Commerce Growth

   • Engage e-commerce managers and digital marketing teams embracing online retail, click-and-collect services, and mobile payment integrations.
   • Align technology solutions with growing demand for contactless shopping, personalized recommendations, and seamless customer journeys.

6. Seasonal and Cultural Campaigns

   • Leverage local holidays, shopping festivals, and cultural events by reaching marketing directors and store managers who coordinate merchandise rotations, promotional deals, and experiential activations.
   • Adapt messaging to align with regional festivities and peak shopping periods.

Why Choose Success.ai?

1. Best Price Guarantee

2. Access top-quality verified data at competitive prices, ensuring strong ROI for product launches, brand expansions, and supply chain optimizations.

3. Sea...

MealMe provides comprehensive grocery and retail SKU-level product data, including real-time pricing, from the top 100 retailers in the USA and Canada. Our proprietary technology ensures accurate and up-to-date insights, empowering businesses to excel in competitive intelligence, pricing strategies, and market analysis.

Retailers Covered: MealMe’s database includes detailed SKU-level data and pricing from leading grocery and retail chains such as Walmart, Target, Costco, Kroger, Safeway, Publix, Whole Foods, Aldi, ShopRite, BJ’s Wholesale Club, Sprouts Farmers Market, Albertsons, Ralphs, Pavilions, Gelson’s, Vons, Shaw’s, Metro, and many more. Our coverage spans the most influential retailers across North America, ensuring businesses have the insights needed to stay competitive in dynamic markets.

Key Features: SKU-Level Granularity: Access detailed product-level data, including product descriptions, categories, brands, and variations. Real-Time Pricing: Monitor current pricing trends across major retailers for comprehensive market comparisons. Regional Insights: Analyze geographic price variations and inventory availability to identify trends and opportunities. Customizable Solutions: Tailored data delivery options to meet the specific needs of your business or industry. Use Cases: Competitive Intelligence: Gain visibility into pricing, product availability, and assortment strategies of top retailers like Walmart, Costco, and Target. Pricing Optimization: Use real-time data to create dynamic pricing models that respond to market conditions. Market Research: Identify trends, gaps, and consumer preferences by analyzing SKU-level data across leading retailers. Inventory Management: Streamline operations with accurate, real-time inventory availability. Retail Execution: Ensure on-shelf product availability and compliance with merchandising strategies. Industries Benefiting from Our Data CPG (Consumer Packaged Goods): Optimize product positioning, pricing, and distribution strategies. E-commerce Platforms: Enhance online catalogs with precise pricing and inventory information. Market Research Firms: Conduct detailed analyses to uncover industry trends and opportunities. Retailers: Benchmark against competitors like Kroger and Aldi to refine assortments and pricing. AI & Analytics Companies: Fuel predictive models and business intelligence with reliable SKU-level data. Data Delivery and Integration MealMe offers flexible integration options, including APIs and custom data exports, for seamless access to real-time data. Whether you need large-scale analysis or continuous updates, our solutions scale with your business needs.

Why Choose MealMe? Comprehensive Coverage: Data from the top 100 grocery and retail chains in North America, including Walmart, Target, and Costco. Real-Time Accuracy: Up-to-date pricing and product information ensures competitive edge. Customizable Insights: Tailored datasets align with your specific business objectives. Proven Expertise: Trusted by diverse industries for delivering actionable insights. MealMe empowers businesses to unlock their full potential with real-time, high-quality grocery and retail data. For more information or to schedule a demo, contact us today!

The Robust Retail grant, administered by the Department of Small and Local Business Development, is intended to provide direct assistance to small and local storefront businesses. These funds have been leveraged for a wide range of purposes to include façade improvement, expansion, and purchasing inventory and have resulted in increase of sales, customer acquisition and job creation.

E-commerce and retail datasets provide valuable insights into consumer behavior, market trends, and business performance. These datasets help companies optimize pricing, enhance marketing strategies, improve inventory management, and increase sales conversions. By leveraging data-driven decision-making, businesses can stay competitive and meet evolving customer demands. Benefits and Impact: Enhanced predictive accuracy for demand forecasting and price […]

Value and volume of retail sales broken down by size of business

This dataset is about companies. It has 251 rows and is filtered where the industry is Broadline Retail. It features 6 columns including city, country, revenues, and industry.

All restaurants and food stores selling perishable items are required to apply for a Retail Food License (RFL). This metric tracks the average number of days the Department of Business Affairs and Consumer Protection (BACP) takes to issue RFLs. The target response time for processing is within 15 days.

Standard error reference tables for the Retail Sales Index in Great Britain.

Context

This dataset contains lot of historical sales data. It was extracted from a Brazilian top retailer and has many SKUs and many stores. The data was transformed to protect the identity of the retailer.

Content

[TBD]

Acknowledgements

This data would not be available without the full collaboration from our customers who understand that sharing their core and strategical information has more advantages than possible hazards. They also support our continuos development of innovative ML systems across their value chain.

Inspiration

Every retail business in the world faces a fundamental question: how much inventory should I carry? In one hand to mush inventory means working capital costs, operational costs and a complex operation. On the other hand lack of inventory leads to lost sales, unhappy customers and a damaged brand.

Current inventory management models have many solutions to place the correct order, but they are all based in a single unknown factor: the demand for the next periods.

This is why short-term forecasting is so important in retail and consumer goods industry.

We encourage you to seek for the best demand forecasting model for the next 2-3 weeks. This valuable insight can help many supply chain practitioners to correctly manage their inventory levels.

Success.ai delivers unparalleled access to Retail Store Data for Asia’s retail and e-commerce sectors, encompassing subcategories such as ecommerce data, ecommerce merchant data, ecommerce market data, and company data. Whether you’re targeting emerging markets or established players, our solutions provide the tools to connect with decision-makers, analyze market trends, and drive strategic growth. With continuously updated datasets and AI-validated accuracy, Success.ai ensures your data is always relevant and reliable.

Key Features of Success.ai's Retail Store Data for Retail & E-commerce in Asia:

Extensive Business Profiles: Access detailed profiles for 70M+ companies across Asia’s retail and e-commerce sectors. Profiles include firmographic data, revenue insights, employee counts, and operational scope.

Ecommerce Data: Gain insights into online marketplaces, customer demographics, and digital transaction patterns to refine your strategies.

Ecommerce Merchant Data: Understand vendor performance, supply chain metrics, and operational details to optimize partnerships.

Ecommerce Market Data: Analyze purchasing trends, regional preferences, and market demands to identify growth opportunities.

Contact Data for Decision-Makers: Reach key stakeholders, such as CEOs, marketing executives, and procurement managers. Verified contact details include work emails, phone numbers, and business addresses.

Real-Time Accuracy: AI-powered validation ensures a 99% accuracy rate, keeping your outreach efforts efficient and impactful.

Compliance and Ethics: All data is ethically sourced and fully compliant with GDPR and other regional data protection regulations.

Why Choose Success.ai for Retail Store Data?

Best Price Guarantee: We deliver industry-leading value with the most competitive pricing for comprehensive retail store data.

Customizable Solutions: Tailor your data to meet specific needs, such as targeting particular regions, industries, or company sizes.

Scalable Access: Our data solutions are built to grow with your business, supporting small startups to large-scale enterprises.

Seamless Integration: Effortlessly incorporate our data into your existing CRM, marketing, or analytics platforms.

Comprehensive Use Cases for Retail Store Data:

1. Market Entry and Expansion:

Identify potential partners, distributors, and clients to expand your footprint in Asia’s dynamic retail and e-commerce markets. Use detailed profiles to assess market opportunities and risks.

1. Personalized Marketing Campaigns:

Leverage ecommerce data and consumer insights to craft highly targeted campaigns. Connect directly with decision-makers for precise and effective communication.

1. Competitive Benchmarking:

Analyze competitors’ operations, market positioning, and consumer strategies to refine your business plans and gain a competitive edge.

1. Supplier and Vendor Selection:

Evaluate potential suppliers or vendors using ecommerce merchant data, including financial health, operational details, and contact data.

1. Customer Engagement and Retention:

Enhance customer loyalty programs and retention strategies by leveraging ecommerce market data and purchasing trends.

APIs to Amplify Your Results:

Enrichment API: Keep your CRM and analytics platforms up-to-date with real-time data enrichment, ensuring accurate and actionable company profiles.

Lead Generation API: Maximize your outreach with verified contact data for retail and e-commerce decision-makers. Ideal for driving targeted marketing and sales efforts.

Tailored Solutions for Industry Professionals:

Retailers: Expand your supply chain, identify new markets, and connect with key partners in the e-commerce ecosystem.

E-commerce Platforms: Optimize your vendor and partner selection with verified profiles and operational insights.

Marketing Agencies: Deliver highly personalized campaigns by leveraging detailed consumer data and decision-maker contacts.

Consultants: Provide data-driven recommendations to clients with access to comprehensive company data and market trends.

What Sets Success.ai Apart?

70M+ Business Profiles: Access an extensive and detailed database of companies across Asia’s retail and e-commerce sectors.

Global Compliance: All data is sourced ethically and adheres to international data privacy standards, including GDPR.

Real-Time Updates: Ensure your data remains accurate and relevant with our continuously updated datasets.

Dedicated Support: Our team of experts is available to help you maximize the value of our data solutions.

Empower Your Business with Success.ai:

Success.ai’s Retail Store Data for the retail and e-commerce sectors in Asia provides the insights and connections needed to thrive in this competitive market. Whether you’re entering a new region, launching a targeted campaign, or analyzing market trends, our data solutions ensure measurable success.

...

The U.S. Census Bureau.s economic indicator surveys provide monthly and quarterly data that are timely, reliable, and offer comprehensive measures of the U.S. economy. These surveys produce a variety of statistics covering construction, housing, international trade, retail trade, wholesale trade, services and manufacturing. The survey data provide measures of economic activity that allow analysis of economic performance and inform business investment and policy decisions. Other data included, which are not considered principal economic indicators, are the Quarterly Summary of State & Local Taxes, Quarterly Survey of Public Pensions, and the Manufactured Homes Survey. For information on the reliability and use of the data, including important notes on estimation and sampling variance, seasonal adjustment, measures of sampling variability, and other information pertinent to the economic indicators, visit the individual programs' webpages - http://www.census.gov/cgi-bin/briefroom/BriefRm.

This dataset is about companies. It has 251 rows and is filtered where the industry is Broadline Retail. It features 3 columns: employees, and foundation year.

This dataset is about companies. It has 585 rows and is filtered where the industry is Consumer Staples Distribution & Retail. It features 30 columns including city, country, employees, and employee type.