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

This dataset was created to simulate a market basket dataset, providing insights into customer purchasing behavior and store operations. The dataset facilitates market basket analysis, customer segmentation, and other retail analytics tasks. Here's more information about the context and inspiration behind this dataset:

Context:

Retail businesses, from supermarkets to convenience stores, are constantly seeking ways to better understand their customers and improve their operations. Market basket analysis, a technique used in retail analytics, explores customer purchase patterns to uncover associations between products, identify trends, and optimize pricing and promotions. Customer segmentation allows businesses to tailor their offerings to specific groups, enhancing the customer experience.

Inspiration:

The inspiration for this dataset comes from the need for accessible and customizable market basket datasets. While real-world retail data is sensitive and often restricted, synthetic datasets offer a safe and versatile alternative. Researchers, data scientists, and analysts can use this dataset to develop and test algorithms, models, and analytical tools.

Dataset Information:

The columns provide information about the transactions, customers, products, and purchasing behavior, making the dataset suitable for various analyses, including market basket analysis and customer segmentation. Here's a brief explanation of each column in the Dataset:

• Transaction_ID: A unique identifier for each transaction, represented as a 10-digit number. This column is used to uniquely identify each purchase.
• Date: The date and time when the transaction occurred. It records the timestamp of each purchase.
• Customer_Name: The name of the customer who made the purchase. It provides information about the customer's identity.
• Product: A list of products purchased in the transaction. It includes the names of the products bought.
• Total_Items: The total number of items purchased in the transaction. It represents the quantity of products bought.
• Total_Cost: The total cost of the purchase, in currency. It represents the financial value of the transaction.
• Payment_Method: The method used for payment in the transaction, such as credit card, debit card, cash, or mobile payment.
• City: The city where the purchase took place. It indicates the location of the transaction.
• Store_Type: The type of store where the purchase was made, such as a supermarket, convenience store, department store, etc.
• Discount_Applied: A binary indicator (True/False) representing whether a discount was applied to the transaction.
• Customer_Category: A category representing the customer's background or age group.
• Season: The season in which the purchase occurred, such as spring, summer, fall, or winter.
• Promotion: The type of promotion applied to the transaction, such as "None," "BOGO (Buy One Get One)," or "Discount on Selected Items."

Use Cases:

• Market Basket Analysis: Discover associations between products and uncover buying patterns.
• Customer Segmentation: Group customers based on purchasing behavior.
• Pricing Optimization: Optimize pricing strategies and identify opportunities for discounts and promotions.
• Retail Analytics: Analyze store performance and customer trends.

Note: This dataset is entirely synthetic and was generated using the Python Faker library, which means it doesn't contain real customer data. It's designed for educational and research purposes.

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

Graph and download economic data for Sales by Retail Stores for United States (M0689BUSM144NNBR) from Jan 1946 to Sep 1974 about retail trade, sales, retail, and USA.

Graph and download economic data for Monthly State Retail Sales: Miscellaneous Store Retailers in Idaho (MSRSID453) from Jan 2019 to Apr 2025 about miscellaneous, ID, retail trade, sales, retail, and USA.

This dataset was originally created in 2012 by the Office of the Chief Technology Officer. OCTO staff used the Alcoholic Beverage and Cannabis Administration’s (ABCA) definition of Full-Service Grocery Stores which outlines criteria for a business to obtain licenses to sell beer, wine, and spirits. Visit abca.dc.gov for full definition.OCTO staff then reviewed the Office of Planning DC Food Policy’s 2018 Food System Assessment listing grocery stores in Appendix D, and comparing these to the ABCA definition. This led to additional locations that meet, or come very close to, the full-service grocery store criteria. The criteria in section one of ABCA’s full-service grocery store determined the initial locations included in this dataset. View the full assessment at dcfoodpolicycouncil.org.Since the initial creation of this dataset, OCTO and the Deputy Mayor for Planning and Economic Development (DMPED) staff confirm grocery store operations by comparing datasets from DLCP, media outlets, commercially licensed datasets, and onsite visits.Please review supplemental metadata for more details.

Graph and download economic data for Retail Sales: Miscellaneous Store Retailers (MRTSMPCSM453USN) from Feb 1992 to Jun 2025 about miscellaneous, retail trade, sales, retail, and USA.

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APIs for Enhanced Functionality

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Graph and download economic data for Monthly State Retail Sales: General Merchandise Stores in Illinois (MSRSIL452) from Jan 2019 to Apr 2025 about merchandise, general, IL, retail trade, sales, retail, and USA.

Apple Retail Stores are a chain of retail stores owned by Apple Inc., specializing in the sale of Apple products and accessories. These stores are known for their sleek design, knowledgeable staff, and focus on providing a unique customer experience. Apple's retail business model is centered around creating a premium shopping environment and offering exceptional customer service. Apple also offers various in-store services, such as Genius Bar support for technical issues and personal setup assistance. You can download the complete list of key information about Apple Retail Stores locations, contact details, services offered, and geographical coordinates, beneficial for various applications like store locators, business analysis, and targeted marketing. The Apple Retail Stores data you can download includes:

Identification & Location:


  store_number, store_name

  address, address_line_2, city, state, zip_code, country, country_code, county, latitude, longitude, geo_accuracy


Contact Information:


  phone_number, website_address


Operational Details & Services:


  store_hours

Graph and download economic data for Retail Sales: Grocery Stores (MRTSSM4451USS) from Jan 1992 to Jun 2025 about groceries, retail trade, sales, retail, and USA.

Comprehensive dataset of 1,714 Retail space rental agencies in United States as of July, 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.

Graph and download economic data for Index of Department Store Sales for United States (M06F2BUSM350NNBR) from Jan 1919 to Dec 1963 about retail trade, sales, retail, indexes, and USA.

Graph and download economic data for Monthly State Retail Sales: Food and Beverage Stores in the United States (MSRSUSA445) from Jan 2019 to Apr 2025 about beverages, retail trade, food, sales, retail, and USA.

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Graph and download economic data for Retail Sales: Book Stores (MRTSMPCSM451211USN) from Feb 1992 to May 2025 about book, retail trade, sales, retail, and USA.

Graph and download economic data for Retail Sales: Office Supplies, Stationery, and Gift Stores (MRTSMPCSM4532USN) from Feb 1992 to Jun 2025 about paper, supplies, retail trade, sales, retail, and USA.

Graph and download economic data for Monthly State Retail Sales: Miscellaneous Store Retailers in Utah (MSRSUT453) from Jan 2019 to Dec 2023 about miscellaneous, UT, retail trade, sales, retail, and USA.

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