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.

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The data set contains information on retail market spot check audit purchases of tuna in airtight containers. Data are available from May 2001 to present with new data appended annually. Information includes the date, location, product type, store information where random spot check purchases were made throughout the United States and Puerto Rico. Information on purchased product allows the manufacturer, distributor or importer to track the tuna back to harvest and verify the dolphin-safe status of the tuna product.

Dataset

This dataset was created by Zulkifli Yasin

Released under Database: Open Database, Contents: © Original Authors

Contents

NoSQL Database Market was valued at $9.38 Billion in 2023, and is projected to reach $USD 86.48 Billion by 2032, at a CAGR of 28% from 2023 to 2032.

Retail Sales of Consumer Goods: Year to Date: Zhejiang data was reported at 3,070.000 RMB bn in Nov 2024. This records an increase from the previous number of 2,750.000 RMB bn for Oct 2024. Retail Sales of Consumer Goods: Year to Date: Zhejiang data is updated monthly, averaging 657.264 RMB bn from Jan 2003 (Median) to Nov 2024, with 230 observations. The data reached an all-time high of 3,255.019 RMB bn in Dec 2023 and a record low of 26.993 RMB bn in Jan 2003. Retail Sales of Consumer Goods: Year to Date: Zhejiang data remains active status in CEIC and is reported by Zhejiang Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Retail Sales of Consumer Goods: Provincial and Municipal Statistical Bureau.

The Relational Database Software Market size was estimated at USD 21.97 Billion in 2024 and is projected to reach USD 45.23 Billion by 2031, growing at a CAGR of 9.4 % from 2024 to 2031

Global Relational Database Software Market Drivers

Rising Demand for Efficient Data Management: Organizations across industries are generating and collecting ever-increasing volumes of data. This necessitates efficient and secure data management solutions. Relational databases, with their structured format and robust querying capabilities, offer a valuable tool to organize, manage, and analyze this data, leading to increased demand for this software.

Cloud Adoption and Scalability: The proliferation of cloud computing has significantly impacted the relational database market. Cloud-based database solutions offer scalability, flexibility, and reduced IT infrastructure burden for businesses. This makes them particularly attractive for small and medium-sized enterprises (SMEs) and facilitates easier data access for geographically dispersed teams.

Growing Importance of Data Security and Compliance: Data breaches and cyberattacks pose significant threats to businesses. Relational database software vendors are constantly innovating to enhance security features like encryption and access controls. Additionally, stringent data privacy regulations like GDPR and CCPA are driving the need for compliant data storage and management solutions, further propelling the market for secure relational databases.

Gain exclusive access to verified Shopify store owners with our premium Shopify Users Email List. This database includes essential data fields such as Store Name, Website, Contact Name, Email Address, Phone Number, Physical Address, Revenue Size, Employee Size, and more on demand. Leverage real-time, accurate data to enhance your marketing efforts and connect with high-value Shopify merchants. Whether you're targeting small businesses or enterprise-level Shopify stores, our database ensures precision and reliability for optimized lead generation and outreach strategies. Key Highlights: ✅ 3.9M+ Shopify Stores ✅ Direct Contact Info of Shopify Store Owners ✅ 40+ Data Points ✅ Lifetime Access ✅ 10+ Data Segmentations ✅ FREE Sample Data

This service offers Esri's Retail MarketPlace database for the United States which measures retail market supply and demand. The data is modeled from the Census of Retail Trade by the US Census Bureau, Infogroup business data, and statistics from the US Bureau of Labor Statistics.

All attributes are available at all geography levels: country, state, county, tract, block group, ZIP code, place, county subdivision, congressional district, core-based statistical area (CBSA), and designated market area (DMA).

Over 2,300 attributes measuring likely demand for a wide variety of products and services in retail categories including food and drink, automotive, electronics, appliances, health, and personal care. The database provides a direct comparison between retail sales and consumer spending by industry and measures the gap between supply and demand.

To view ArcGIS Online items using this service, including the terms of use, visit http://goto.arcgisonline.com/demographics9/USA_Retail_Marketplace_2019.

United States Retail Sales: sa: Department stores ex Leased Departments (DS) data was reported at 12.360 USD bn in Sep 2018. This records a decrease from the previous number of 12.454 USD bn for Aug 2018. United States Retail Sales: sa: Department stores ex Leased Departments (DS) data is updated monthly, averaging 16.813 USD bn from Jan 1992 (Median) to Sep 2018, with 321 observations. The data reached an all-time high of 19.904 USD bn in Jan 2001 and a record low of 12.325 USD bn in Nov 2016. United States Retail Sales: sa: Department stores ex Leased Departments (DS) data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H001: Retail Sales: By NAIC System. All estimates for department stores exclude leased departments.

Global In-memory database market is expected to revenue of around USD 36.21 billion by 2032, growing at a CAGR of 19.2% between 2024 and 2032.

Dataset

This dataset was created by Bishoy Nagy 2020

Released under Database: Open Database, Contents: Database Contents

Contents

Global Non-Native Database Management System market will reach USD 1,231 million by 2025, at a CAGR of 10.8% between 2019 and 2025. The large-scale usage of non-native database management systems in BFSI, as well as IT & telecom sectors, is set to drive the growth of the market over the forecast timeline.

China Wholesale & Retail Inventory: Total data was reported at 4,211.718 RMB bn in 2018. This records a decrease from the previous number of 4,339.700 RMB bn for 2017. China Wholesale & Retail Inventory: Total data is updated yearly, averaging 1,536.815 RMB bn from Dec 1998 (Median) to 2018, with 21 observations. The data reached an all-time high of 4,339.700 RMB bn in 2017 and a record low of 352.760 RMB bn in 2004. China Wholesale & Retail Inventory: Total data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Wholesale and Retail Inventory: Above Designated Size Enterprise.

[198+ Pages Report] Global graph database market size & share estimated to be worth USD 5.2 Billion in the year 2026, growing at a CAGR value of 21.7% during the forecast period of 2021-2026.

Database Market Report is Segmented by Deployment (Cloud, On-Premises), Enterprise (SMEs, Large Enterprises), End-User Verticals (BFSI, Retail and E-Commerce, Logistics and Transportation, Media and Entertainment, Healthcare, IT and Telecom, Other End-User Verticals), Geography (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

The Cloud Database and DBaaS Market Report is Segmented by Component (Solution, Services), by Type (NoSQL, Relational Database), by Deployment (Public, Private, Hybrid), by Enterprise Size (SMEs, Large Enterprises), by End-User (BFSI, IT and Telecom, Retail, Healthcare, Government, Other End-Users), by Geography (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Knowledge Graph Market size was valued at USD 7.19 Billion in 2024 and is expected to reach USD 4.1 Billion by 2032, growing at a CAGR of 18.1% from 2025 to 2032.

Knowledge Graph Market Drivers

Enhanced Data Integration and Analysis:
Knowledge graphs excel at integrating and analyzing data from diverse sources, including structured, semi-structured, and unstructured data. This enables organizations to gain a holistic view of information and make more informed decisions.
Improved Search and Information Retrieval:
Knowledge graphs provide a more semantic understanding of information, enabling more accurate and relevant search results.
Instead of just keyword matching, knowledge graphs understand the relationships between entities and provide more contextually relevant information.
Personalized Experiences:
Knowledge graphs can be used to personalize user experiences by understanding individual preferences, interests, and behaviors.
This is crucial for applications like personalized recommendations, targeted advertising, and customer service.
AI and Machine Learning:
Knowledge graphs are essential for powering AI and machine learning applications, such as chatbots, recommendation systems, and fraud detection.
They provide a structured representation of knowledge that AI/ML models can easily understand and utilize.
Business Intelligence and Decision Making:
Knowledge graphs can help businesses gain deeper insights into their customers, markets, and operations.
They can be used to identify trends, predict future outcomes, and make more informed business decisions.

Food Intakes Converted to Retail Commodities Databases (FICRCD) provide data for foods consumed in the United States national dietary intake surveys at the retail commodity level. The survey foods are converted into 65 retail-level commodities. The commodities are grouped into eight major categories: Dairy Products; Fats and Oils; Fruits; Grains; Meat, Poultry, Fish and Eggs; Nuts; Caloric Sweeteners; and Vegetables, Dry Beans and Legumes. The Food Intakes Converted to Retail Commodities Databases were jointly developed by USDA's Agricultural Research Service (ARS) and Economic Research Service (ERS) for the following six surveys: Continuing Survey of Food Intakes by Individuals 1994-1996 and 1998. National Health and Nutrition Examination Survey 1999-2000. What We Eat in America, National Health and Nutrition Examination Survey 2001-2002. What We Eat in America, National Health and Nutrition Examination Survey 2003-2004. What We Eat in America, National Health and Nutrition Examination Survey 2005-2006. What We Eat in America, National Health and Nutrition Examination Survey 2007-2008. Resources in this dataset:Resource Title: Food Intakes Converted to Retail Commodities Databases (FICRCD). File Name: Web Page, url: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/ficrcd-overview/ Web site of the Food Intakes Converted to Retail Commodities Databases (FICRCD), which provide data for foods consumed in the national dietary intake surveys at the retail commodity level. Provides links to Data Tables, Methodology and User Guide, and Factsheets.

China Chain Retail: Sales: Retail data was reported at 2,986.450 RMB bn in 2022. This records a decrease from the previous number of 3,020.070 RMB bn for 2021. China Chain Retail: Sales: Retail data is updated yearly, averaging 2,510.138 RMB bn from Dec 2003 (Median) to 2022, with 20 observations. The data reached an all-time high of 3,020.070 RMB bn in 2021 and a record low of 289.035 RMB bn in 2003. China Chain Retail: Sales: Retail data remains active status in CEIC and is reported by Ministry of Commerce, China General Chamber of Commerce. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.CRAA: Chain Retail.

The Managed Database Service Market Report is Segmented by Service (Data Administration, Database Backup & Recovery, Database Disaster Recovery, Database Security, and Database Optimization), by Application (Customer Relationship Management, Enterprise Resource Planning. Supply Chain Management, Web Applications, and Big Data Analytics), by Industry Vertical (BFSI, Healthcare, IT & Telecom, Retail, Manufacturing and Other Industries) and by Geography (North America, Europe, Asia Pacific, South America, Middle East, and Africa). The Market Size and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.