Context

The Customer Shopping Preferences Dataset offers valuable insights into consumer behavior and purchasing patterns. Understanding customer preferences and trends is critical for businesses to tailor their products, marketing strategies, and overall customer experience. This dataset captures a wide range of customer attributes including age, gender, purchase history, preferred payment methods, frequency of purchases, and more. Analyzing this data can help businesses make informed decisions, optimize product offerings, and enhance customer satisfaction. The dataset stands as a valuable resource for businesses aiming to align their strategies with customer needs and preferences. It's important to note that this dataset is a Synthetic Dataset Created for Beginners to learn more about Data Analysis and Machine Learning.

Content

This dataset encompasses various features related to customer shopping preferences, gathering essential information for businesses seeking to enhance their understanding of their customer base. The features include customer age, gender, purchase amount, preferred payment methods, frequency of purchases, and feedback ratings. Additionally, data on the type of items purchased, shopping frequency, preferred shopping seasons, and interactions with promotional offers is included. With a collection of 3900 records, this dataset serves as a foundation for businesses looking to apply data-driven insights for better decision-making and customer-centric strategies.

Dataset Glossary (Column-wise)

• Customer ID - Unique identifier for each customer
• Age - Age of the customer
• Gender - Gender of the customer (Male/Female)
• Item Purchased - The item purchased by the customer
• Category - Category of the item purchased
• Purchase Amount (USD) - The amount of the purchase in USD
• Location - Location where the purchase was made
• Size - Size of the purchased item
• Color - Color of the purchased item
• Season - Season during which the purchase was made
• Review Rating - Rating given by the customer for the purchased item
• Subscription Status - Indicates if the customer has a subscription (Yes/No)
• Shipping Type - Type of shipping chosen by the customer
• Discount Applied - Indicates if a discount was applied to the purchase (Yes/No)
• Promo Code Used - Indicates if a promo code was used for the purchase (Yes/No)
• Previous Purchases - The total count of transactions concluded by the customer at the store, excluding the ongoing transaction
• Payment Method - Customer's most preferred payment method
• Frequency of Purchases - Frequency at which the customer makes purchases (e.g., Weekly, Fortnightly, Monthly)

Structure of the Dataset

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Acknowledgement

This dataset is a synthetic creation generated using ChatGPT to simulate a realistic customer shopping experience. Its purpose is to provide a platform for beginners and data enthusiasts, allowing them to create, enjoy, practice, and learn from a dataset that mirrors real-world customer shopping behavior. The aim is to foster learning and experimentation in a simulated environment, encouraging a deeper understanding of data analysis and interpretation in the context of consumer preferences and retail scenarios.

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Thumbnail by: Clothing icons created by Flat Icons - Flaticon

Bodegas & Grocery Stores Receiving Recognition from Borough President's Office Each year, bodegas and grocery stores located in and around Action Center catchment areas participate in the Shop Healthy NYC program's Retail Challenge to increase (1) availability of healthier foods, such as low-sodium canned goods, healthier snacks and deli options; (2) promotion of healthier foods by posting Shop Healthy marketing materials for healthier foods and removing unhealthy advertising from the front door; and (3) visibility of healthier foods by placing them in more prominent locations, such as placing produce at the checkout counter or near the front entrance of the store, and water and other low-calorie drinks at eye-level. Stores that have implemented all of the program’s criteria at the conclusion of the Retail Challenge, and maintain them for at least one month, receive a recognition award from the Borough President's Office to acknowledge their efforts and dedication to make the healthy choice, the easier choice for their communities. This is a manually compiled list of stores, which is based on data collected through implementation checklists; these are forms completed by Shop Healthy staff as part of store observations that track whether each criteria has been met. At this time, the program does not have processes in place to ensure that stores maintain the changes past one-month.

Use our TikTok Shop dataset to extract detailed e-commerce insights, including product names, prices, discounts, seller details, product descriptions, categories, customer ratings, and reviews. You may purchase the entire dataset or a customized subset tailored to your needs. Popular use cases include trend analysis, pricing optimization, customer behavior studies, and marketing strategy refinement. The TikTok Shop dataset includes key data points: product performance metrics, user engagement, customer reviews, and more. Unlock the potential of TikTok's shopping platform today with our comprehensive dataset!

Insipiration

I wanted to take this opportunity to give back to the community by sharing my own real-life dataset. I have always been on the receiving end of uplifting feedback and encouragement from this wonderful Data Science community, so I decided to share my very own sales data from my own e-commerce shop as my way of giving back to the community.

About Data

The data contain all sales recorded from June to September 2022. Information such as the customers' personal information wasn't included for privacy and confidentiality. Other irrelevant features were also removed to make the dataset simpler and more user-friendly.

Contents

This dataset contains the following columns along with their descriptions: - order_id: unique identifier for each order placed - order_date: date and time of order - sku: a number used by retailer to assign their products - color: color of the product - size: size of the product, treat missing values as ( One Size ) - unit_price: unit price of the product - quantity: quantity ordered for that particular product - revenue: unit_price * quantity

Some Questions

For those who are looking a place to start, here are some questions that you can answer. 1. What are the best and worst-selling SKU items? by color? by size? 2. What is the average order value? 3. What are the peak days or time periods with the highest sales? Do sales follow a trend or a seasonality?

1. Advanced: Predict sales in the next months.

Revolutionize Customer Engagement with Our Comprehensive Ecommerce Data

Our Ecommerce Data is designed to elevate your customer engagement strategies, providing you with unparalleled insights and precision targeting capabilities. With over 61 million global contacts, this dataset goes beyond conventional data, offering a unique blend of shopping cart links, business emails, phone numbers, and LinkedIn profiles. This comprehensive approach ensures that your marketing strategies are not just effective but also highly personalized, enabling you to connect with your audience on a deeper level.

What Makes Our Ecommerce Data Stand Out?

• Unique Features for Enhanced Targeting
  Our Ecommerce Data is distinguished by its depth and precision. Unlike many other datasets, it includes shopping cart links—a rare and valuable feature that provides you with direct insights into consumer behavior and purchasing intent. This information allows you to tailor your marketing efforts with unprecedented accuracy. Additionally, the integration of business emails, phone numbers, and LinkedIn profiles adds multiple layers to traditional contact data, enriching your understanding of clients and enabling more personalized engagement.

• Robust and Reliable Data Sourcing
  We pride ourselves on our dual-sourcing strategy that ensures the highest levels of data accuracy and relevance:

  • Real-Time Information from 10 Active Publication Sites: Our databases are continuously updated with the latest information, sourced from ten active publication sites that provide real-time data.
  • Dedicated Contact Discovery Team: Complementing our automated sources, our dedicated Contact Discovery Team conducts thorough research and investigations, ensuring that every piece of data is accurate and reliable. This two-pronged approach guarantees that our Ecommerce Data is both up-to-date and relevant, providing you with a solid foundation for your business strategies.

  Primary Use Cases Across Industries

Our Ecommerce Data is versatile and can be leveraged across various industries for multiple applications: - Precision Targeting in Marketing: Create personalized marketing campaigns based on detailed shopping cart activities, ensuring that your outreach resonates with individual customer preferences. - Sales Enrichment: Sales teams can benefit from enriched client profiles that include comprehensive contact information, enabling them to connect with key decision-makers more effectively. - Market Research and Analytics: Research and analytics departments can use this data for in-depth market studies and trend analyses, gaining valuable insights into consumer behavior and market dynamics.

Global Coverage for Comprehensive Engagement

Our Ecommerce Data spans across the globe, providing you with extensive reach and the ability to engage with customers in diverse regions: - North America: United States, Canada, Mexico - Europe: United Kingdom, Germany, France, Italy, Spain, Netherlands, Sweden, and more - Asia: China, Japan, India, South Korea, Singapore, Malaysia, and more - South America: Brazil, Argentina, Chile, Colombia, and more - Africa: South Africa, Nigeria, Kenya, Egypt, and more - Australia and Oceania: Australia, New Zealand - Middle East: United Arab Emirates, Saudi Arabia, Israel, Qatar, and more

Comprehensive Employee and Revenue Size Information

Our dataset also includes detailed information on: - Employee Size: Whether you’re targeting small businesses or large corporations, our data covers all employee sizes, from startups to global enterprises. - Revenue Size: Gain insights into companies across various revenue brackets, enabling you to segment the market more effectively and target your efforts where they will have the most impact.

Seamless Integration into Broader Data Offerings

Our Ecommerce Data is not just a standalone product; it is a critical piece of our broader data ecosystem. It seamlessly integrates with our comprehensive suite of business and consumer datasets, offering you a holistic approach to data-driven decision-making: - Tailored Packages: Choose customized data packages that meet your specific business needs, combining Ecommerce Data with other relevant datasets for a complete view of your market. - Holistic Insights: Whether you are looking for industry-specific details or a broader market overview, our integrated data solutions provide you with the insights necessary to stay ahead of the competition and make informed business decisions.

Elevate Your Business Decisions with Our Ecommerce Data

In essence, our Ecommerce Data is more than just a collection of contacts—it’s a strategic tool designed to give you a competitive edge in understanding and engaging your target audience. By leveraging the power of this comprehensive dataset, you can elevate your business decisions, enhance customer interactions, and navigate the digital landscape with confi...

The dataset contain a sales data for different region . if you are beginner you can work . it is a different data set in which you can able to understand many new concept . take this as challenge and work on it .

Dataset Card for Datashop Science QA

  Dataset Details





  Dataset Description

This science-focused dataset was curated by applying model-based filtering to the DCLM Baseline dataset, extracting around 40B Llama-3 tokens of data, which were later rewritten into QA pairs format by Llama-3.1-8B-Instruct. It yields strong out of the box performance for improving MMLU scores, particularly the MMLU STEM subset. We observe +4 point increase in the MMLU STEM subset… See the full description on the dataset page: https://huggingface.co/datasets/marin-community/datashop-science-qa.

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

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

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

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

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

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

Management Information data store for reporting on electronic service usages.

Context

E-commerce has become a new channel to support businesses development. Through e-commerce, businesses can get access and establish a wider market presence by providing cheaper and more efficient distribution channels for their products or services. E-commerce has also changed the way people shop and consume products and services. Many people are turning to their computers or smart devices to order goods, which can easily be delivered to their homes.

Content

This is a sales transaction data set of UK-based e-commerce (online retail) for one year. This London-based shop has been selling gifts and homewares for adults and children through the website since 2007. Their customers come from all over the world and usually make direct purchases for themselves. There are also small businesses that buy in bulk and sell to other customers through retail outlet channels.

The data set contains 500K rows and 8 columns. The following is the description of each column. 1. TransactionNo (categorical): a six-digit unique number that defines each transaction. The letter “C” in the code indicates a cancellation. 2. Date (numeric): the date when each transaction was generated. 3. ProductNo (categorical): a five or six-digit unique character used to identify a specific product. 4. Product (categorical): product/item name. 5. Price (numeric): the price of each product per unit in pound sterling (£). 6. Quantity (numeric): the quantity of each product per transaction. Negative values related to cancelled transactions. 7. CustomerNo (categorical): a five-digit unique number that defines each customer. 8. Country (categorical): name of the country where the customer resides.

There is a small percentage of order cancellation in the data set. Most of these cancellations were due to out-of-stock conditions on some products. Under this situation, customers tend to cancel an order as they want all products delivered all at once.

Inspiration

Information is a main asset of businesses nowadays. The success of a business in a competitive environment depends on its ability to acquire, store, and utilize information. Data is one of the main sources of information. Therefore, data analysis is an important activity for acquiring new and useful information. Analyze this dataset and try to answer the following questions. 1. How was the sales trend over the months? 2. What are the most frequently purchased products? 3. How many products does the customer purchase in each transaction? 4. What are the most profitable segment customers? 5. Based on your findings, what strategy could you recommend to the business to gain more profit?

Photo by CardMapr on Unsplash

This dataset contains detailed sales transactions from a coffee shop, providing insights into customer purchasing behavior, revenue trends, and product popularity. It is ideal for sales forecasting, demand analysis, and business intelligence applications.

Supports management information reports for end users (DDS). DIODS stores detailed case information from NDDSS and creates subtotals and summaries on cases for reports.

Global Shop Floor Data Collection Software Market Report 2022 comes with the extensive industry analysis of development components, patterns, flows and sizes. The report also calculates present and past market values to forecast potential market management through the forecast period between 2022-2028. The report may be the best of what is a geographic area which expands the competitive landscape and industry perspective of the market.

Explore the Meijer Grocery Store Dataset, a comprehensive collection of data on products available at Meijer, a leading American grocery store chain. This dataset includes detailed information on a wide variety of grocery items such as fresh produce, dairy, meat, beverages, household essentials, and more. Each product entry provides essential details, including product names, categories, prices, brands, descriptions, and availability, offering valuable insights for researchers, data analysts, and retail professionals.

Key Features:

• Extensive Product Range: Contains a wide array of grocery items from Meijer, covering multiple categories like fresh produce, dairy, meat, beverages, household essentials, and more.
• Detailed Product Information: Each entry includes key details such as product name, category, price, brand, description, and availability, allowing for in-depth analysis of retail trends and consumer preferences.
• Ideal for Market Analysis: Perfect for researchers, data scientists, and retail professionals interested in analyzing consumer behavior, studying grocery market trends, or optimizing inventory strategies in the retail sector.
• Rich Source of Retail Data: Provides a comprehensive overview of the grocery market at Meijer, helping professionals stay updated on the latest trends, popular products, and pricing strategies.

Whether you're analyzing market trends in the grocery sector, researching consumer behavior, or developing new retail strategies, the Meijer Grocery Store Dataset is an invaluable resource that provides detailed insights and extensive coverage of products available at Meijer.

Based on over 5 million syncing email accounts, we can parse all transactional data in TikTok shop (and other e-commerce names) to see what individuals in each country are purchasing exactly on an SKU level. Average order value, discounts used, items bought, frequency of purchase, seller name, email ID, geolocation data all included.

The world's largest operators, financial institutions, consultancies and market research firms license our datasets for added granular insights. Contact michelle@measurable.ai to learn more or for some samples for backtesting.

United States JR: Same-Store Sales: HI: Tile Shop data was reported at 2.100 % in Oct 2018. This records an increase from the previous number of -1.800 % for Jul 2018. United States JR: Same-Store Sales: HI: Tile Shop data is updated quarterly, averaging 4.500 % from Apr 2013 (Median) to Oct 2018, with 23 observations. The data reached an all-time high of 14.800 % in Oct 2013 and a record low of -6.800 % in Apr 2018. United States JR: Same-Store Sales: HI: Tile Shop data remains active status in CEIC and is reported by Redbook Research Inc.. The data is categorized under Global Database’s United States – Table US.H014: Johnson Redbook Same-Store Sales Index: Quarterly: YoY%.

Shop Your Way is a leading digital platform that offers a wide range of products and services to consumers. As a major player in the e-commerce industry, the company has established itself as a go-to destination for customers seeking a diverse range of goods and services. Shop Your Way's extensive product catalog includes items such as fashion apparel, home goods, electronics, and more.

With a strong presence in the market, Shop Your Way has built a reputation for providing high-quality products and services to its customers. The company's commitment to excellence has earned it a loyal customer base, and its website receives a significant amount of traffic daily.

Comprehensive dataset of 5,046 Quilt shops in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset contains a list of sales and movement data by item and department appended monthly. Update Frequency : Monthly

All 311 Service Requests from 2010 to present. This information is automatically updated daily.