TheLook is a fictitious eCommerce clothing site developed by the Looker team. The dataset contains information about customers, products, orders, logistics, web events and digital marketing campaigns. The contents of this dataset are synthetic, and are provided to industry practitioners for the purpose of product discovery, testing, and evaluation. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets.What is BigQuery .

Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants

  Overview

This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset.

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...

Ecommerce FAQ Chatbot Dataset Overview The Ecommerce FAQ Chatbot Dataset is a valuable collection of questions and corresponding answers, meticulously curated for training and evaluating chatbot models in the context of an Ecommerce environment. This dataset is designed to assist developers, researchers, and data scientists in building effective chatbots that can handle customer inquiries related to an Ecommerce platform. Contents The dataset comprises a total of 79 question-answer pairs… See the full description on the dataset page: https://huggingface.co/datasets/Andyrasika/Ecommerce_FAQ.

There are currently 3.8 million live websites that use WooCommerce on WordPress to power their online storefronts while they are over 4 million ecommerce stores powered by Shopify.

I'll show you how the pandemic has changed the way people shop and give you some accurate ecommerce statistics to prove it.

Use of information and communication technology (ICT) and e-commerce activity by UK businesses. Annual data on e-commerce sales and how businesses are using the internet.

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.

Graph and download economic data for E-Commerce Retail Sales as a Percent of Total Sales (ECOMPCTNSA) from Q4 1999 to Q1 2025 about e-commerce, retail trade, percent, sales, retail, and USA.

As of 2025, there are about 24 million eCommerce sites worldwide—a drop from the previous high of 27 million but still far above the 9.2 million recorded in 2019. The United States alone accounts for nearly 12 million online stores, underlining the global shift to digital commerce.

In 2024, global retail e-commerce sales reached an estimated ************ U.S. dollars. Projections indicate a ** percent growth in this figure over the coming years, with expectations to come close to ************** dollars by 2028. World players Among the key players on the world stage, the American marketplace giant Amazon holds the title of the largest e-commerce player globally, with a gross merchandise value of nearly *********** U.S. dollars in 2024. Amazon was also the most valuable retail brand globally, followed by mostly American competitors such as Walmart and the Home Depot. Leading e-tailing regions E-commerce is a dormant channel globally, but nowhere has it been as successful as in Asia. In 2024, the e-commerce revenue in that continent alone was measured at nearly ************ U.S. dollars, outperforming the Americas and Europe. That year, the up-and-coming e-commerce markets also centered around Asia. The Philippines and India stood out as the swiftest-growing e-commerce markets based on online sales, anticipating a growth rate surpassing ** percent.

Discover the latest eCommerce statistics in Mexico 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 Mexico, uncovering the distribution of stores across categories and platforms.

The revenue in the e-commerce market in the United States was forecast to continuously increase between 2025 and 2029 by in total 498.2 billion U.S. dollars (+37.16 percent). After the tenth consecutive increasing year, the revenue is estimated to reach 1.8 trillion U.S. dollars and therefore a new peak in 2029. Notably, the revenue of the e-commerce market was continuously increasing over the past years.Find other key market indicators concerning the average revenue per user (ARPU) and number of users. The Statista Market Insights cover a broad range of additional markets.

Unlock the door to business expansion by investing in our real-time eCommerce leads list. Gain direct access to store owners and make informed decisions with data fields including Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.

Ensure a lifetime of access for continuous growth and tailor your campaigns with accurate and reliable information, initiating targeted efforts that align with your marketing goals. Whether you're targeting specific industries or global locations, our database provides up-to-date and valuable insights to support your business journey.

• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data

Wajdii98/Ecommerce dataset hosted on Hugging Face and contributed by the HF Datasets community

Amazon.com is the most popular shopping platform in the world, with 3,161.64 million visitors every month - followed by ebay.com and walmart.com.

The US e-commerce market, a significant segment of the global landscape, exhibits robust growth, driven by increasing internet penetration, smartphone adoption, and a shift in consumer preferences towards online shopping convenience. The market's Compound Annual Growth Rate (CAGR) of 14.70% suggests a substantial expansion, with a projected market value significantly exceeding its 2025 valuation within the forecast period (2025-2033). Key drivers include the rise of mobile commerce, the expansion of logistics and delivery infrastructure, and the increasing adoption of digital payment methods. Furthermore, the diversification of e-commerce offerings across various segments like beauty & personal care, consumer electronics, fashion & apparel, and food & beverage fuels this growth. The presence of major players like Amazon, Walmart, and Target underscores the market's competitiveness and maturity. However, challenges such as cybersecurity concerns, rising logistics costs, and the need for effective customer service strategies remain. The market segmentation reveals significant opportunities within specific categories; for instance, the beauty & personal care sector is expected to witness strong growth due to increasing demand for convenient online purchasing and personalized experiences. The US e-commerce market is geographically concentrated, with North America holding a substantial market share. However, regional variations exist, influenced by factors like consumer spending habits, digital infrastructure, and regulatory frameworks. Growth in regions beyond the core North American market will likely contribute significantly to the overall CAGR. The B2B e-commerce segment is also experiencing substantial growth, driven by businesses seeking streamlined procurement processes and improved supply chain efficiency. While precise figures for specific segments and regions are unavailable from the given information, it's evident that the overall market trajectory is positive, with promising prospects for both established and emerging players across diverse product categories. The future success within this dynamic landscape will depend on factors such as adapting to evolving consumer expectations, leveraging innovative technologies, and effectively navigating the complexities of the digital marketplace. Comprehensive Coverage USA Ecommerce Market Report (2019-2033) This in-depth report provides a comprehensive analysis of the USA ecommerce market, covering the period from 2019 to 2033. With a focus on the B2C ecommerce market size (GMV) and B2B ecommerce market size, this study delves into key market segments like Beauty & Personal Care, Consumer Electronics, Fashion & Apparel, Food & Beverage, Furniture & Home, and Others (Toys, DIY, Media, etc.). We analyze market trends, growth drivers, challenges, and emerging opportunities, providing valuable insights for businesses operating in or planning to enter this dynamic market. The report uses 2025 as the base year and forecasts the market's trajectory until 2033, incorporating data from the historical period (2019-2024). Recent developments include: May 2022- Home Depot announced the formation of Home Depot Ventures, a venture capital fund to promote early-stage startups that improve customer experience and home renovation. Furthermore, the $150 million funds will evaluate investments in businesses at various stages of development, emphasizing early and growth-stage startups that assist Home Depot customers and can scale., April 2022- In the United States, Apple finally offers the tools and accessories needed for self-servicing select iPhones. The company is now selling parts and components for the iPhone 12 series, iPhone 13 series, and the newly released 3rd Generation iPhone SE 2022 smartphones., April 2022- Amazon announced on Wednesday that it will build a solar park in Kent County as one of 37 new renewable energy projects worldwide to use renewable energy to power all of its activities by 2025, five years ahead of schedule., April 2022- Walmart honored Igloo's ancient legacy and commitment to "Made in the USA" with elected officials and prominent executives from both companies in attendance. In honor of this praise, Igloo designed the new Overland Series of coolers exclusively for Walmart, made in the United States., March 2022- Walmart Inc plans to hire more than 5,000 new associates for its tech hubs worldwide during the current fiscal year. Walmart Global Tech, the company's technology division, would be hiring for positions such as cybersecurity professional, product manager, and data scientist., June 2020- Apple's announcements and developments enhance the Apple platform and product experience. From macOS Big Sur, which boasts the most significant design overhaul since the launch of Mac OS X, to watchOS 7, iOS 14's new App Library, and iPadOS 14's expanded handwriting capabilities with Apple Pencil.. Key drivers for this market are: Growing Demand from Apparel and Footwear Industry., Rising Adoption of technologies (IOT,ML); Penetration of Internet and Smartphone Usage. Potential restraints include: Operational Compatibility Due to Growing Brand Value. Notable trends are: Increasing adoption of technologies.

ECommerce Product 3 Products

## Overview

ECommerce Product  3 Products is a dataset for object detection tasks - it contains Televisions Phones Laptops annotations for 1,017 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Discover the unparalleled potential of our comprehensive eCommerce leads database, featuring essential data fields such as Store Name, Website, Contact First Name, Contact Last Name, Email Address, Physical Address, City, State, Country, Zip Code, Phone Number, Revenue Size, Employee Size, and more on demand.

With a focus on Shopify, Amazon, eBay, and other global retail stores, this database equips you with accurate information for successful marketing campaigns. Supercharge your marketing efforts with our enriched contact and company database, providing real-time, verified data insights for strategic market assessments and effective buyer engagement across digital and traditional channels.

• 4M+ eCommerce Companies • 40M+ Worldwide eCommerce Leads • Direct Contact Info for Shop Owners • 47+ eCommerce Platforms • 40+ Data Points • Lifetime Access • 10+ Data Segmentations • Sample Data"

Context

This dataset was created from the online retail dataset found here https://www.kaggle.com/roshansharma/online-retail. This has had some processing for customer segmentation so it can be used for nice visualisation of the data.

Content

The following variables are used: | Variable | Description | | --- | --- | |**CustomerID**| This is the same CustomerID field as in the online retail dataset found in the link above and can be linked to this dataset.| |**Frequency**|This is how many times a customer purchased.| |**Recency**|This is how many days ago a customer made a purchase. This is adjusted to reference a point in time.| |**Monetary** |This is how much a customer spent in total. Their total Lifetime monetary value.| |**rankF**|This is the Frequency value divided into different ranges from 1 to 5 using the cut function in R. (5 = lots of visits, 1 = very low visits)| |**rankR**|This is the Recency value divided into different ranges from 1 to 5 using the cut function in R and then flipped. (5 = very Recent, 1 = ages ago) | |**rankM**|This is the Monetary value divided into different ranges from 1 to 5 using the cut function in R. (5 = High spender, 1 = low spender) | |**groupRFM**| The group RFM is a value combining the rankR, rankF and rankM. This uses 1 digit per rank (ie 1 rankR, 2 rankF, 5 rankM would be 125 Group)| |**Country**|This is the customer delivery country from the original online retail dataset.| |**Customer_Segment**| A customer segment is added to give a more human description of the customer and therefore can be treated differently. These segments are listed below.|

Customer Segments

The customer segments below detail the description of the customers from their details processed in the RFM analysis. | Customer Segment | Segment Description | | --- | --- | |**Champions** | Bought recently buy often and spend the most | |**Loyal Customers**|Spend good money Responsive to promotions| |**Potential Loyalist**|Recent customers spent good amount, bought more than once| |**Recent High Spender**|Recent customers not frequent but spend some| |**New Customers**|Bought more recently but not often| |**Promising**|Recent shoppers but haven’t spent much| |**Need Attention**|Above average recency frequency & monetary values| |**About To Sleep**|Below average recency frequency & monetary values| |**At Risk**|Spent big money purchased often but long time ago| |**Can’t Lose Them**|Made big purchases and often but long time ago| |**Hibernating**|Low spenders low frequency purchased long time ago| |**Lost**|Lowestrecency frequency & monetary scores|

Acknowledgements

Thank you to the owners of the online retail dataset. https://www.kaggle.com/roshansharma

Inspiration

The online retail dataset is a great set for finding anomalies and doing some interesting reports, however RFM analysis allows you to treat clusters of data in the same way which is suitable for marketing teams etc.

RFM analysis is a straight forward analytical process that can be achieved by clustering but a more manual process is good as you can adjust these figures to get more even groups. I will post my R code for this and link shortly.| | | | | --- | --- | | | | | | | --- | --- | | | |